Potential field method to navigate several mobile robots

Navigation of mobile robots remains one of the most challenging functions to carry out. Potential Field Method (PFM) is rapidly gaining popularity in navigation and obstacle avoidance applications for mobile robots because of its elegance. Here a modified potential field method for robots navigation has been described. The developed potential field function takes care of both obstacles and targets. The final aim of the robots is to reach some pre-defined targets. The new potential function can configure a free space, which is free from any local minima irrespective of number of repulsive nodes (obstacles) in the configured space. There is a unique global minimum for an attractive node (target) whose region of attraction extends over the whole free space. Simulation results show that the proposed potential field method is suitable for navigation of several mobile robots in complex and unknown environments. Saroj Kumar Pradhan is faculty of Mechanical Engineering Department with N.I.T., Hamirpur, HP, India. He has received his B.E. degree in Mechanical Engineering from Utkal University and M.E. in Machine Design and Analysis from NIT Rourkela. He has published more than 17 technical papers in international journals and conference proceedings. His areas of research include mobile robots navigation and vibration of multilayred beams. Dayal R. Parhi is working as Assistant Professor at NIT Rourkela, India. He has obtained his first Ph.D. degree in “Mobile Robotics” from United Kingdom and Second Ph.D. in “Mechanical Vibration” from India. He has visited CMU, USA as a “Visiting Scientist” in the field of “Mobile Robotics”. His main areas of current research are “Robotics” and “Mechanical Vibration”. He is supervising five Ph.D. students in the fields of Robotics and Vibration. Email: dayalparhi@yahoo.com. Anup Kumar Panda Received his M.Tech degree from IIT, Kharagpur in 1993 and Ph.D. degree from Utkal University in 2001. He is currently an assistant professor in the Department of Electrical Engineering at National Institute of Technology, Rourkela, India. His areas of research include robotics, Machine Drives, harmonics and power quality. He has published more than 30 technical papers in journals and conference proceedings. He is now involved in two R&D projects funded by Government of India. R. K. Behera is a Senior Lecturer of Mechanical Engineering at National Institute of Technology, Rourkela, India. He has been working as lecturer for more than 10 years. He obtained his BE degree from IGIT, Sarang, of Utkal University. He obtained his ME and Ph.D degrees, both in the field of mechanical engineering from NIT Rourkela.     

Balance control of a biped robot using camera image of reference object

This paper presents a new balance control scheme for a biped robot. Instead of using dynamic sensors to measure the pose of a biped robot, this paper uses only the visual information of a specific reference object in the workspace. The zero moment point (ZMP) of the biped robot can be calculated from the robot’s pose, which is measured from the reference object image acquired by a CCD camera on the robot’s head. For balance control of the biped robot a servo controller uses an error between the reference ZMP and the current ZMP, estimated by Kalman filter. The efficiency of the proposed algorithm has been proven by the experiments performed on both flat and uneven floors with unknown thin obstacles. Recommended by Editorial Board member Dong Hwan Kim under the direction of Editor Jae-Bok Song. This work was supported by the Korea Research Foundation Grant funded by the Korean Government (MOEHRD). This research was supported by the MKE(The Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITA(Institute for Information Technology Advancement) (IITA-2008-C1090-0803-0006). Sangbum Park received the B.S. and M.S. degrees from Electronic Engineering of Soongsil University, Seoul, Korea, in 2004 and 2006 respectively. He has been with School of Electronic Engineering, Soongsil University since 2006, where he is currently pursuing a Ph.D. His current research interests include biped walking robot, robotics vision. Youngjoon Han received the B.S., M.S. and Ph.D. degrees in Electronic Engineering from Soongsil University, Seoul, Korea, in 1996, 1998, and 2003, respectively. He is currently an Assistant Professor in the School of Electornic Engineering at Soongsil University. His research interests include robot vision system, and visual servo control. Hernsoo Hahn received the B.S. and M.S. degrees in Electronic Engineering at Soongsil University and Younsei University, Korea in 1982 and 1983 respectively. He received the Ph.D. degree in Computer Engineering from University of Southern California in 1991, and became an Assistant Professor at the School Electroncis Engneering in Soongsil University in 1992. Currently, he is a Professor. His research interests include application of vision sensors to mobile robots and measurement systems.     

A systematic approach to the problem of odour source localisation

Although chemical sensing is far simpler than vision or hearing, navigation in a chemical diffusion field is still not well understood. Biological studies have already demonstrated the use of various search methods (e.g., chemotaxis and biased random walk), but robotics research could provide new ways to investigate principles of olfactory-based search skills (Webb, 2000; Grasso, 2001). In previous studies on odour source localisation, we have tested three biologically inspired search strategies: chemotaxis, biased random walk, and a combination of these methods (Kadar and Virk, 1998; Lytridis et al., 2001). The main objective of the present paper is to demonstrate how simulation and robot experiments could be used conjointly to systematically study these search strategies. Specifically, simulation studies are used to calibrate and test our three strategies in concentric diffusion fields with various noise levels. An experiment with a mobile robot was also conducted to assess these strategies in a real diffusion field. The results of this experiment are similar to those of simulation studies showing that chemotaxis is a more efficient but less robust strategy than biased random walk. Overall, the combined strategy seems to be superior to chemotaxis and biased random walk in both simulation and robot experiment. Christodoulos Lytridis received a BEng degree in electronic and computer engineering, MSc degree in mobile robotics and PhD in Olfactory based navigation for mobile robots from the University of Portsmouth. His research interests include odor-based cooperative navigation, biologically inspired navigational methods, and odor sensors for mobile robots. He is an associate member of the Institution of Electrical Engineering. Endre E. Kadar is a senior lecturer in psychology at the University of Portsmouth. He began his academic career as a theoretical mathematician at the Institute of Hydraulic Planning, working in applied modelling on a variety of problems in engineering. Then he moved to the University of Connecticut to work as a teaching and research assistant and received his PhD in experimental psychology in 1996. His PhD research project has dealt with the problem of ecological foundation of perceptual control of locomotion. After moving to Portsmouth in 1996, his theoretical work provided the basis for a productive collaboration with engineers in robotics. Also, these novel field theoretical ideas have resulted in radically new approaches to exploratory learning and visual control of high speed driving. Application of these approaches has been supported by several ESRC grants. Gurvinder S. Virk graduated with first class honours in electrical and electronic engineering (University of Manchester) and received a PhD in control theory (Imperial College, London). He has followed an academic career working at Sheffield City Polytechnic, Universities of Southampton, Sheffield and Bradford, Portsmouth and is now professor of control and robotics at the University of Leeds. His main research interests include robotics, building and energy management systems, and application of advanced model-based control systems. He has held several grants from national and European sources, as well as industry (the total value of ￡11M). He has more then 200 publications, including four books. He coordinated the European thematic network CLAWAR and has been involved in developing robots for exploring volcanic environments, inspection of highway bridges and dams, and biomedical applications. He is chairman of the ISO TC184/SC2 Advisory Group on Standards for mobile service robots. He is Fellow of the Institution of Engineering and Technology, Fellow of the Chartered Institution of Building Services Engineers, Fellow of the Institution of Applied Mathematics and Its Applications. He is Charted Engineer and a Charted Mathematician. He has been awarded the Freedom of the City of London for his work in promoting Information Technology.     

Relative localization using path odometry information

All mobile bases suffer from localization errors. Previous approaches to accommodate for localization errors either use external sensors such as lasers or sonars, or use internal sensors like encoders. An encoder’s information is integrated to derive the robot’s position; this is called odometry. A combination of external and internal sensors will ultimately solve the localization error problem, but this paper focuses only on processing the odometry information. We solve the localization problem by forming a new odometry error model for the synchro-drive robot then use a novel procedure to accurately estimate the error parameters of the odometry error model. This new procedure drives the robot through a known path and then uses the shape of the resulting path to estimate the model parameters. Experimental results validate that the proposed method precisely estimates the error parameters and that the derived odometry error model of the synchro-drive robot is correct. Nakju Lett Doh received his BS, his MS, and his Ph.D. degree in Mechanical Engineering from Pohang University of Science and Technology (POSTECH), KOREA, in 1998, 2000, and 2005, respectively. Since then, he is a senior researcher in Intellgient Robot Reserarch Division, Electronics and Telecommunications Research Institute (ETRI), KOREA. He received the glod prize in Intelligent Robot Contest hosted by Northern KyoungSang Province at 2000 and the gold prize in Humantech Thesis Competition hosted by Samsung Electronics at 2005. In 2003, he got the best student paper award in IEEE International Conference on Robotics and Automation held in Taiwan. His research interests are the localization and navigation of mobile robots and ubiquitous robotic space for intelligent robot navigation. Howie Choset is an Associate Professor of Robotics at Carnegie Mellon University where he conducts research in motion planning and design of serpentine mechanisms, coverage path planning for de-mining and painting, mobile robot sensor based exploration of unknown spaces, and education with robotics. In 1997, the National Science Foundation awarded Choset its Career Award to develop motion planning strategies for arbitrarily shaped objects. In 1999, the Office of Naval Research started supporting Choset through its Young Investigator Program to develop strategies to search for land and sea mines. Recently, the MIT Technology Review elected Choset as one of its top 100 innovators in the world under 35. Choset directs the Undergraduate Robotics Minor at Carnegie Mellon and teaches an overview course on Robotics which uses series of custom developed Lego Labs to complement the course work. Professor Choset’s students have won best paper awards at the RIA in 1999 and ICRA in 2003. Finally, Choset is a member of an urban search and rescue response team using robots with the Center for Robot Assisted Search and Rescue. Now, he is active in extending the mechanism design and path planning work to medical mechatronics. Wan Kyun Chung received his BS degree in Mechanical Design from Seoul National University in 1981, his MS degree in Mechanical Engineering from KAIST in 1983, and his Ph.D. in Production Engineering from KAIST in 1987. He is Professor in the school of Mechanical Engineering, POSTECH (he joined the faculty in 1987). In 1988, he was a visiting professor at the Robotics Institute of Carnegie-Mellon University. In 1995 he was a visiting scholar at the university of California, Berkeley. His research interests include the localization and navigation for mobile robots, underwater robots and development of robust controller for precision motion control. He is a director of National Research Laboratory for Intelligent Mobile Robot Navigation. He is serving as an Associate Editor for IEEE Tr. on Robotics, international editorial board for Advanced Robotics.     

Sliding mode control for trajectory tracking of mobile robot in the RFID sensor space

This paper presents a sliding mode control method for wheeled mobile robots. Because of the nonlinear and nonholonomic properties, it is difficult to establish an appropriate model of the mobile robot system for trajectory tracking. A robust control law which is called sliding mode control is proposed for asymptotically stabilizing the mobile robot to a desired trajectory. The posture of the mobile robot (including the position and heading direction) is presented and the kinematics equations are established in the two-dimensional coordinates. According to the kinematics equations, the controller is designed to find an acceptable control law so that the tracking error will approximate 0 as the time approaches infinity with an initial error. The RFID sensor space is used to estimate the real posture of the mobile robot. Simulation and experiment demonstrate the efficacy of the proposed system for robust tracking of mobile robots. Recommended by Sooyong Lee under the direction of Editor Jae-Bok Song. This work was supported by the Korea Science and Engineering (KOSEF) grant funded by the Korea government (MOST) (No. R01-2007-000-10171-0). Jun Ho Lee received the M.S degree in Mechanical Engineering from Pusan National University. His research interests include factory automation and sliding mode control. Cong Lin received the B.S. degree in Electrical Engineering from Jilin University and the M.S degree in Electrical Engineering from Pusan National University. His research interests include neural network and sliding mode control. Hoon Lim is currently a M.S student in Electrical Engineering of Pusan National University. His research interests include mobile manipulator and sliding mode control. Jang Myung Lee received the B.S. and M.S degrees in Electronics Engineering from Seoul National University, Korea. He received the Ph.D. degree in Computer from the University of Southern California, Los Angeles. Now, he is a Professor in Pusan National University. His research interests include integrated manufacturing systems and intelligent control.     

Mobile robot localization based on effective combination of vision and range sensors

Most localization algorithms are either range-based or vision-based, but the use of only one type of sensor cannot often ensure successful localization. This paper proposes a particle filter-based localization method that combines the range information obtained from a low-cost IR scanner with the SIFT-based visual information obtained from a monocular camera to robustly estimate the robot pose. The rough estimation of the robot pose by the range sensor can be compensated by the visual information given by the camera and the slow visual object recognition can be overcome by the frequent updates of the range information. Although the bandwidths of the two sensors are different, they can be synchronized by using the encoder information of the mobile robot. Therefore, all data from both sensors are used to estimate the robot pose without time delay and the samples used for estimating the robot pose converge faster than those from either range-based or vision-based localization. This paper also suggests a method for evaluating the state of localization based on the normalized probability of a vision sensor model. Various experiments show that the proposed algorithm can reliably estimate the robot pose in various indoor environments and can recover the robot pose upon incorrect localization. Recommended by Editorial Board member Sooyong Lee under the direction of Editor Hyun Seok Yang. This research was conducted by the Intelligent Robotics Development Program, one of the 21st Century Frontier R&D Programs funded by the Ministry of Knowledge Economy of Korea. Yong-Ju Lee received the B.S. degree in Mechanical Engineering from Korea University in 2004. He is now a Student for Ph.D. of Mechanical Engineering from Korea University. His research interests include mobile robotics. Byung-Doo Yim received the B.S. degree in Control and Instrumentation Engineering from Seoul National University of Technology in 2005. Also, he received the M.S. degree in Mechatroncis Engineering from Korea University in 2007. His research interests include mobile robotics. Jae-Bok Song received the B.S. and M.S. degrees in Mechanical Engineering from Seoul National University in 1983 and 1985, respectively. Also, he received the Ph.D. degree in Mechanical Engineering from MIT in 1992. He is currently a Professor of Mechanical Engineering, Korea University, where he is also the Director of the Intelligent Robotics Laboratory from 1993. His current research interests lie mainly in mobile robotics, safe robot arms, and design/control of intelligent robotic systems.     

In-pipe robot based on selective drive mechanism

This paper presents an in-pipe robot, called MRINSPECT V (Multifunctional Robotic crawler for In-pipe inSPECTion V), which is under development for the inspection of pipelines with a nominal 8-inch inside diameter. To travel freely in every pipeline element, the robot adopts a differential driving mechanism that we have developed. Furthermore, by introducing clutches in transmitting driving power to the wheels, MRINSPECT V is able to select the suitable driving method according to the shape of the pipeline and save the energy to drive in pipelines. In this paper, the critical points in the design and construction of the proposed robot are described with the preliminary results that yield good mobility and increased efficiency. Recommended by Editorial Board member Dong Hwan Kim under the direction of Editor Jae-Bok Song. This work was supported by the Postdoctoral Research Program of Sungkyunkwan University (2008). Se-gon Roh received the B.S., M.S., and Ph.D degrees in Mechatronics Engineering from Sungkyunkwan University, Korea, in 1997, 1999, and 2006 respectively, and is currently a Researcher of the School of Mechanical Engineering also at Sungkyunkwan University. His research interests include mechanism design, applications of mobile robots, and in-pipe robots. Do Wan Kim received the B.S. degree in Mechanical Engineering from Sungkyunkwan University, Korea, in 2007. He is currently working toward a M.S. degree in Mechanical Engineering also at Sungkyunkwan University. His research interests include field robotics, in-pipe robots, and autonomous mobile robots. Jung-Sub Lee received the B.S. degree in Mechanical Engineering in 2008 from Sungkyunkwan University, Suwon, Korea, where he is currently working toward a M.S. degree in mechatronics engineering. His research interests include robot mechanism design, automation, and in-pipe robot. Hyungpil Moon received the B.S. and M.S. degrees in Mechanical Engineering from POSTECH in 1996 and 1998 respectively, and Ph.D. degree in Mechanical Engineering from University of Michigan in 2005. He joined the faculty of School of Mechanical Engineering in Sungkyunkwan University as a Full-time Lecturer in 2008. He was a Post-doctoral fellow at Carnegie Mellon University, Robotics Institute until November 2007. His research interests include distributed manipulation, multiple robot navigation, SLAM, and biomimetic robotics. Hyouk Ryeol Choi received the B.S. degree from Seoul National University in 1984, the M.S. degree from Korea Advanced Technology of Science and Technology (KAIST) in 1986, and the Ph.D. degree from Pohang University of Science and Technology (POSTECH) in 1994, Korea. Since 1995, he has been with Sungkyunkwan University, where he is currently a Professor of the School of Mechanical Engineering. He worked as an Associate Engineer with LG Electronics Central Research Laboratory from 1986 to 1989. From 1993 to 1995, he was with Kyoto University as a grantee of a scholarship from the Japanese Educational Ministry. He visited Advanced Institute of Industrial Science Technology (AIST), Japan as the JSPS Fellow, from 1999 to 2000. He is now an Associate Editor of IEEE Transactions on Robotics, International Journal of Control, System, Automation(IJCAS), and International Journal of Intelligent Service Robots (JISR). His interests include dexterous mechanisms, field applications of robots, and artificial muscle actuator.     

Trajectory tracking with a 6R serial industrial robot with ordinary and non-ordinary singularities

This work presents a trajectory control for non-redundant serial-link manipulators that is valid for trajectories with ordinary singularities of codimension one and non-ordinary singularities of any codimension. For this purpose, several singularity classifications are considered and a procedure is developed in order to solve the indeterminate motion of non-ordinary singularities. The proposed trajectory control is validated by simulation and by experiments with the six-revolute (6R) industrial robot KUKA KR 15/2. Recommended by Editor Jae-Bok Song. This work was supported by the Spanish Government: Research Project BIA2005-09377-C03-02. The authors would like to thank the anonymous reviewers for their time and valuable comments that helped us to improve the quality of this paper. Luis Gracia received the B.Sc., M.Sc., and Ph.D. degrees in Control Systems Engineering, from the Technical University of Valencia (UPV), Spain, in 1998, 2000, and 2006, respectively. He is currently an Associate Professor at Department of Systems Engineering and Control (DISA) of the UPV. His research interests include wheeled mobile robots, robotic manipulators, system modeling and control. Javier Andres received the B.Sc. and M.Sc. degrees in Mechanical Engineering from the UPV in 2003 and 2006, respectively. He is currently working on his Ph.D. His research interests include CAD/CAM/Robotics integration and robot post-processing. Josep Tornero received the M.S. Degree in Systems and Control from the University of Manchester in 1982, and the Ph.D. in Electrical Engineering at the UPV in 1985. He is currently a Professor at the DISA of the UPV and responsible for the ‘Automation in Manufacture and Mobile Robotics’ Group and the ‘Design Institute for the Manufacture and Automated Production’, both at the UPV. He is interested in modeling, control and simulation of auto-guided vehicles, robot arms, and multirate sampled data systems.     

Visual wheel sinkage measurement for planetary rover mobility characterization

Wheel sinkage is an important indicator of mobile robot mobility in natural outdoor terrains. This paper presents a vision-based method to measure the sinkage of a rigid robot wheel in rigid or deformable terrain. The method is based on detecting the difference in intensity between the wheel rim and the terrain. The method uses a single grayscale camera and is computationally efficient, making it suitable for systems with limited computational resources such as planetary rovers. Experimental results under various terrain and lighting conditions demonstrate the effectiveness and robustness of the algorithm. Christopher Brooks is a graduate student in the Mechanical Engineering department of the Massachusetts Institute of Technology. He received his B.S. degree with honor in engineering and applied science from the California Institute of Technology in 2000, and his M.S. degree from the Massachusetts Institute of Technology in 2004. He is a student collaborator on the Mars Exploration Rover science mission. His research interests include mobile robot control, terrain sensing, and their application to improving autonomous robot mobility. He is a member of Tau Beta Pi. Karl Iagnemma is a research scientist in the Mechanical Engineering department of the Massachusetts Institute of Technology. He received his B.S. degree summa cum laude in mechanical engineering from the University of Michigan in 1994, and his M.S. and Ph.D. from the Massachusetts Institute of Technology, where he was a National Science Foundation graduate fellow, in 1997 and 2001, respectively. He has been a visiting researcher at the Jet Propulsion Laboratory. His research interests include rough-terrain mobile robot control and motion planning, robot-terrain interaction, and robotic mobility analysis. He is author of the monograph Mobile Robots in Rough Terrain: Estimation, Motion Planning, and Control with Application to Planetary Rovers (Springer, 2004). He is a member of IEEE and Sigma Xi. Steven Dubowsky received his Bachelor's degree from Rensselaer Polytechnic Institute of Troy, New York in 1963, and his M.S. and Sc.D. degrees from Columbia University in 1964 and 1971. He is currently a Professor of Mechanical Engineering at M.I.T and Director of the Mechanical Engineering Field and Space Robotics Laboratory. He has been a Professor of Engineering and Applied Science at the University of California, Los Angeles, a Visiting Professor at Cambridge University, Cambridge, England, and Visiting Professor at the California Institute of Technology. During the period from 1963 to 1971, he was employed by the Perkin-Elmer Corporation, the General Dynamics Corporation, and the American Electric Power Service Corporation. Dr. Dubowsky's research has included the development of modeling techniques for manipulator flexibility and the development of optimal and self-learning adaptive control procedures for rigid and flexible robotic manipulators. He has authored or co-authored nearly 300 papers in the area of the dynamics, control and design of high performance mechanical and electromechanical systems. Professor Dubowsky is a registered Professional Engineer in the State of California and has served as an advisor to the National Science Foundation, the National Academy of Science/Engineering, the Department of Energy, and the US Army. He is a fellow of the ASME and IEEE and is a member of Sigma Xi and Tau Beta Pi.     

Multimode locomotion via SuperBot reconfigurable robots

One of the most challenging issues for a self-sustaining robotic system is how to use its limited resources to accomplish a large variety of tasks. The scope of such tasks could include transportation, exploration, construction, inspection, maintenance,in-situ resource utilization, and support for astronauts. This paper proposes a modular and reconfigurable solution for this challenge by allowing a robot to support multiple modes of locomotion and select the appropriate mode for the task at hand. This solution relies on robots that are made of reconfigurable modules. Each locomotion mode consists of a set of characteristics for the environment type, speed, turning-ability, energy-efficiency, and recoverability from failures. This paper demonstrates a solution using the SuperBot robot that combines advantages from M-TRAN, CONRO, ATRON, and other chain-based and lattice-based robots. At the present, a single real SuperBot module can move, turn, sidewind, maneuver, and travel on batteries up to 500 m on carpet in an office environment. In physics-based simulation, SuperBot modules can perform multimodal locomotions such as snake, caterpillar, insect, spider, rolling track, H-walker, etc. It can move at speeds of up to 1.0 m/s on flat terrain using less than 6 W per module, and climb slopes of no less 40 degrees. Harris Chi Ho Chiu is a PhD Student in Computer Science at the University of Southern California and a research assistant in Polymorphic Robotics Laboratory of Information Science Institute. He received his Master in Computer Science from the University of Southern California and his Bachelor of Engineering from the University of Hong Kong. His research interests include intelligent automated systems, modular self-reconfigurable systems, artificial intelligence, and machine learning. Michael Rubenstein is currently a PhD student at the Polymorphic Robotics Laboratory, working on the CONRO and Superbot self-reconfigurable robotic systems. He has received his bachelors in Electrical Engineering from Purdue University, and his masters in Electrical Engineering from the University of Southern California, and is currently working towards his PhD in Computer Science from the University of Southern California. His interests include modular self-reconfigurable systems, autonomous robots, self-healing systems, and self-replicating systems. Jagadesh B Venkatesh is a member of the Polymorphic Robotics Laboratory at the Information Sciences Institute. He is currently a Master’s candidate in the Product Development Engineering program at the University of Southern California. He received his MS in Computer Science with specialization in Intelligent Robotics, also at the University of Southern California in 2005. His current interest is the commercialization of robotic technologies, specifically in the consumer robotics sector.     

Application of perturbation/correlation based gradient estimation for environment exploration

Mobile robots are increasingly being used to perform tasks in unknown environments. The potential of robots to undertake such tasks lies in their ability to intelligently and efficiently search in an environment. This paper introduced an algorithm for robots that explore the environment so that they can measure physical properties (dust in this paper). While the robot is moving, it measures the amount of dust and registers the value in the corresponding grid cell. At first, the robot moves from local maximum to local minimum, then to another local maximum, and repeats. To reach the local maximum or minimum, the robot simply follows the gradient which is estimated using perturbation/correlation. By introducing the probability of each grid cell, and considering the probability distribution, the robot doesn’t have to visit all the grid cells in the environment while still providing fast and efficient sensing. Robust estimation of the gradient using perturbation/correlation, which is very effective when an analytical solution is not available, is described. To verify the effectiveness of perturbation/correlation based estimation, the simulation results of gradient estimation which were compared to three other numerical methods are presented. The proposed algorithm was performed by the simulation and the comparison of exploration results according to the gradient estimation method is shown. Recommended by Editor Jae-Bok Song. This work was supported by the IT R&D program of MKE/IITA [2008-F-045-01, Development of Obstacle Detection and Indoor Localization System for the Blind] and also by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MEST) (NO. R01-2007-000-20977-0). Jungyun Bae received the B.S. and M.S degrees from Hongik University in Seoul, Korea, in 2003 and 2005, respectively. She worked for one year for Division of Applied Robot Technology of Korea Institute of Industrial Technology (KITECH) in Ansan, Korea. Presently, she is pursuing a Ph.D. in the Department of Mechanical Engineering in Texas A&M University. Her interested research areas are Mobile Robotics and Intelligence Robots. Gon Woo Kim received the B.S. degree in Electrical Engineering from Chung-Ang University, Korea in 2000, and the M.S. and Ph.D. degrees in the School of Electrical Engineering from Seoul National University in 2002 and 2006, respectively. Since 2008, he has been with Wonkwang University, where he is currently an Assistant Professor of Division of Electrical Electronic and Information Engineering. He worked as a Researcher with Korea Institute of Industrial Technology (KITECH) from 2006 to 2008. His research interests include mobile robotics, sensor fusion/integration, map building, and SLAM. Sooyong Lee received the B.S. and M.S. degrees in Mechanical Engineering from Seoul National University, Seoul, Korea in 1989, and 1991, respectively, and the Ph.D. degree from MIT, Cambridge, MA, in 1996. He worked as a Senior Research Scientist at KIST and then as an Assistant Professor in the Department of Mechanical Engineering at Texas A&M University. He joined Hongik University, Seoul, Korea in 2003 and is currently an Associate Professor in the Mechanical and System Design Engineering Department. His current research includes mobile robot localization and navigation, and active sensing.     

Fast training for object recognition with structure-from-motion

In this paper we present a system for statistical object classification and localization that applies a simplified image acquisition process for the learning phase. Instead of using complex setups to take training images in known poses, which is very time-consuming and not possible for some objects, we use a handheld camera. The pose parameters of objects in all training frames that are necessary for creating the object models are determined using a structure-from-motion algorithm. The local feature vectors we use are derived from wavelet multiresolution analysis. We model the object area as a function of 3D transformations and introduce a background model. Experiments made on a real data set taken with a handheld camera with more than 2500 images show that it is possible to obtain good classification and localization rates using this fast image acquisition method. The text was submitted by the authors in English. Marcin Grzegorzek, born in 1977, obtained his Master’s Degree in Engineering from the Silesian University of Technology Gliwice (Poland) in 2002. Since December 2002 he has been a PhD candidate and member of the research staff of the Chair for Pattern Recognition at the University of Erlangen-Nuremberg, Germany. His fields are 3D object recognition, statistical modeling, and computer vision. He is an author or coauthor of seven publications. Michael Reinhold, born in 1969, obtained his degree in Electrical Engineering from RWTH Aachen University, Germany, in 1998. Later, he received a Doctor of Engineering from the University of Erlangen-Nuremberg, Germany, in 2003. His research interests are statistical modeling, object recognition, and computer vision. He is currently a development engineer at Rohde & Schwarz in Munich, Germany, where he works in the Center of Competence for Digital Signal Processing. He is an author or coauthor of 11 publications. Ingo Scholz, born in 1975, graduated in computer science at the University of Erlangen-Nuremberg, Germany, in 2000 with a degree in Engineering. Since 2001 he has been working as a research staff member at the Institute for Pattern Recognition of the University of Erlangen-Nuremberg. His main research focuses on the reconstruction of light field models, camera calibration techniques, and structure from motion. He is an author or coauthor of ten publications and member of the German Gesellschaft für Informatik (GI). Heinrich Niemann obtained his Electrical Engineering degree and Doctor of Engineering degree from Hannover Technical University, Germany. He worked with the Fraunhofer Institut für Informationsverarbeitung in Technik und Biologie, Karlsruhe, and with the Fachhochschule Giessen in the Department of Electrical Engineering. Since 1975 he has been a professor of computer science at the University of Erlangen-Nuremberg, where he was dean of the engineering faculty of the university from 1979 to 1981. From 1988 to 2000, he was head of the Knowledge Processing research group at the Bavarian Research Institute for Knowledge-Based Systems (FORWISS). Since 1998, he has been a spokesman for a “special research area” with the name of “Model-Based Analysis and Visualization of Complex Scenes and Sensor Data” funded by the German Research Foundation. His fields of research are speech and image understanding and the application of artificial intelligence techniques in these areas. He is on the editorial board of Signal Processing, Pattern Recognition Letters, Pattern Recognition and Image Analysis, and the Journal of Computing and Information Technology. He is an author or coauthor of seven books and about 400 journal and conference contributions, as well as editor or coeditor of 24 proceedings volumes and special issues. He is a member of DAGM, ISCA, EURASIP, GI, IEEE, and VDE and an IAPR fellow.     

Climbing Robots’ Mobility for Inspection and Maintenance of 3D Complex Environments

For complex climbing robots, which work in difficult 3D outdoor environments, the gravity force has an important influence with respect the robots changes during its motion. This type of climbing robots is self-supported in the complex 3D structures (bridges, skeleton of the buildings, etc.) which require periodic, manually performed inspections and maintenance. The use of non-conventional climbing robots for this type of operation is highly appropriate. Their locomotion system commonly comprises arms/legs that permit the robots 3D mobility (gait). These mechanisms also enable the robot to support itself and guarantee its stability. This paper presents the main features of non-conventional climbing robots mobility on complex 3D environments: power supply, number of DOFs, lightweight structure, gait, speed, secure grasp, etc. It also covers the general theory underlying the design of climbing robots, their kinematics, with its specific, unconventional mobility. The paper not only describes the climbing robot mobility theory but also provides several examples taken from the ROMA and MATS robots families. The developed robots have high degree of autonomy with totally on-board control system. These autonomous robots demonstrate in the course of real experimentation that the criteria for design, control strategy and path planning are accurate. Finally, the paper examines trends in climbing robot technology.Carlos Balaguer received his Ph.D. in Automation from the Polytechnic University of Madrid (UPM), Spain in 1983. From 1983–1994 he was with the Department of Systems Engineering and Automation of the UPM as Associated Professor. Since 1994, he has been a Full Professor of the Robotics Lab at the University Carlos III of Madrid. Prof. Balaguers research has included robot design and development, robot control, path & task planning, force-torque control, assistive and service robots, climbing robots, legged and humanoid robots, and human-robot interaction. He has published more than 120 papers in journals and conference proceedings, and several books in the field of robotics. He is a member of IEEE and IFAC, and former President of IAARC.Antonio Gimenez studied Electrical Engineering at the Polytechnic University of Madrid and received his PhD from the University Carlos III of Madrid in 2000. Currently he is Associated Professor at the Robotics Lab atthe University Carlos III of Madrid. He participated in numerous national and international R&D projects in robotics and automation. His research interest includes design and robot development, rehabilitation robots, climbing robots, and automation in construction. Recently he is very active in the field of computer-aided mechatronics design. He has published numerous refereed publications in international journals, and conference proceedings.Alberto Jardón Huete is currently finishing his Ph.D. degree in Automation Engineering. He received his B.Sc. in electronics engineering (1998) and is graduated in Electrical Engineering (2002) at University Carlos III of Madrid. He is an active member of the Robotics Lab since 1997, and has collaborated in the development of the climbing robots ROMA I, ROMA II, and other research projects of relevance. Currently he is focused in the design and development of light weight service robots. His interests include assistive robotic design, mechatronics, robotic research, the development of tools to perform this research and the transfer of robotics technology to industry.     

A method of model improvement for spotting recognition of gestures using an image sequence

We have developed a real-time gesture recognition system whose models can be taught by only one instruction. Therefore the system can adapt to new gesture performer quickly but it can not raise the recognition rates even if we teach gestures many times. That is because the system could not utilize all the teaching data. In order to cope with the problem, averages of teaching data are calculated. First, the best frame correspondence of the teaching data and the model is obtained by Continuous DP. Next the averages and variations are calculated for each frame of the model. We show the effectiveness of our method in the experiments. Takuichi Nishimura: He is a researcher of Multi-modal Function Tsukuba Laboratory and Information Basis Function Laboratory at the Real World Computing Partnership. He has engaged in motion image understanding, multi-modal human computer interface, multi-modal information retrieval, and mobile robot navigation. He completed the master’s course of the University of Tokyo in 1992. Hiroaki Yabe: He is from SHARP corporation working as a researcher of Multi-modal Function Tsukuba Laboratory and Information Basis Function Tsukuba Laboratory at the Real World Computing Partnership. He has engaged in motion image understanding, multi-modal human computer interface, multi-modal information retrieval. He completed the master’s course of the University of Tokyo in 1995. Ryuichi Oka, Ph.D.: He is a chief of Multi-modal Function Tsukuba Laboratory and Information Basis Function Laboratory at Tsukuba Research Center of the Real World Computing Partnership (RWC Japan) which started in 1992. His research interests include motion image understanding, spontaneous speech understanding, self-organisation information base, multi-modal human computer interface, multi-modal information retrieval, mobile robot, integration of symbol and pattern, and super parallel computation. He received his Ph.D degree in Engineering from the University of Tokyo.     

Abstracting Vehicle Shape and Kinematic Constraints from Obstacle Avoidance Methods

Most obstacle avoidance techniques do not take into account vehicle shape and kinematic constraints. They assume a punctual and omnidirectional vehicle and thus they are doomed to rely on approximations when used on real vehicles. Our main contribution is a framework to consider shape and kinematics together in an exact manner in the obstacle avoidance process, by abstracting these constraints from the avoidance method usage. Our approach can be applied to many non-holonomic vehicles with arbitrary shape. For these vehicles, the configuration space is three-dimensional, while the control space is two-dimensional. The main idea is to construct (centred on the robot at any time) the two-dimensional manifold of the configuration space that is defined by elementary circular paths. This manifold contains all the configurations that can be attained at each step of the obstacle avoidance and is thus general for all methods. Another important contribution of the paper is the exact calculus of the obstacle representation in this manifold for any robot shape (i.e. the configuration regions in collision). Finally, we propose a change of coordinates of this manifold so that the elementary paths become straight lines. Therefore, the three-dimensional obstacle avoidance problem with kinematic constraints is transformed into the simple obstacle avoidance problem for a point moving in a two-dimensional space without any kinematic restriction (the usual approximation in obstacle avoidance). Thus, existing avoidance techniques become applicable. The relevance of this proposal is to improve the domain of applicability of a wide range of obstacle avoidance methods. We validated the technique by integrating two avoidance methods in our framework and performing tests in the real robot. Javier Minguez received the physics science degree in 1996 from the Universidad Complutense de Madrid, Madrid, Spain, and the Ph.D. degree in computer science and systems engineering in 2002 from the University of Zaragoza, Zaragoza, Spain. During his student period, in 1999 he was a research visitor in the Robotics and Artificial Intelligence Group, LAASCNRS, Toulouse, France. In 2000, he visited the Robot and ComputerVision Laboratory (ISR-IST), Technical University of Lisbon, Lisbon, Portugal. In 2001, he was with the Robotics Laboratory, Stanford University, Stanford, USA. He is currently a fulltime Researcher in the Robot, Vision, and Real Time Group, in the University of Zaragoza. His research interests are obstacle avoidance, motion estimation and sensor-based motion systems for mobile robots. Luis Montano was born on September 6, 1958 in Huesca, Spain. He received the industrial engineering degree in 1981 and the PhD degree in 1987 from the University of Zaragoza, Spain. He is an Associate Professor of Systems Engineering and Automatic Control at the University of Zaragoza (Spain). He has been Head of the Computer Science and Systems Engineering Department of the University of Zaragoza. Currently he is the coordinator of the Production Technologies Research in the Aragon Institute of Engineering Research and of the Robotics, Perception and Real Time group of the University of Zaragoza. He is principal researcher in robotic projects and his major research interests are mobile robot navigation and cooperative robots. José Santos-Victor received the PhD degree in Electrical and Computer Engineering in 1995 from Instituto Superior Técnico (IST - Lisbon, Portugal), in the area of Computer Vision and Robotics. He is an Associate Professor at the Department of Electrical and Computer Engineering of IST and a researcher of the Institute of Systems and Robotics (ISR), at the Computer and Robot Vision Lab - VisLab. (http://vislab.isr.ist.utl.pt) He is the scientific responsible for the participation of IST in various European and National research projects in the areas of Computer Vision and Robotics. His research interests are in the areas of Computer and Robot Vision, particularly in the relationship between visual perception and the control of action, biologically inspired vision and robotics, cognitive vision and visual controlled (land, air and underwater) mobile robots. Prof. Santos-Victor is an IEEE member and an Associated Editor of the IEEE Transactions on Robotics.     

Multisensor Demining Robot

The paper describes an advanced multisensor demining robot. The robot transport system is based on a simple structure using pneumatic drive elements. The robot has robust design and can carry demining equipment up to 100 kg over rough terrains. Due to the adaptive possibilities of pedipulators to obstacles, the robot can adjust the working position of the demining sensors while searching for mines. The detection block consists of a metal detector, an infrared detector, and a chemical explosive sensor. The robot is controlled by means of an on-board processor and by an operator remote station in an interactive mode. Experimental results of the transport, control, and detection systems of the robot are presented.Michael Yu. Rachkov is Professor of Automation at the Moscow State Industrial University. He graduated in Automatic Control Systems from Moscow Higher Technical School, 1979. He held academic posts at the Institute for Problems in Mechanics, Russian Academy of Sciences. In 1986 he completed his PhD in industrial robotics and received his DSc in mobile robotics in 1997. Professor Rachkov has been leading in several international projects like EUREKA and REMAPHOS. He has published over 170 papers and several books in the field of automation, robotics and optimal control. He is a member of Russian Cosmonautics Academy and International Informatization Academy.Lino Marques is a research engineer at the Institute of Systems and Robotics of the University of Coimbra. He received the Engineering and MsC. degrees in Electrical Engineering from the Faculty of Science and Technology of this University in 1992 and 1997 respectively. He is currently working toward the Ph.D. degree and teaching in the Electrical and Computer Engineering Department. His current research interests include sensors, mechatronics, mobile robotics and industrial automation.Anábal T. De Almeida graduated in Electrical Engineering, University of Porto, 1972, and received a Ph.D. in Electrical Engineering, from Imperial College, University of London, 1977. Currently he is a Professor in the Department of Electrical Engineering, University of Coimbra, and he is the Director of the Institute of Systems and Robotics since 1993. Professor De Almeida is a consultant of the European Commission Framework Programmes. He is the co-author of five books and more than one hundred papers in international journals, meetings and conferences. He has coordinated several European and national research projects.     

Evolvable hardware: A robot navigation system testbed

Recently there has been great interest in the design and study of evolvable systems based on Artificial Life principles in order to monitor and control the behavior of physically embedded systems such as mobile robots, plants and intelligent home devices. At the same time new integrated circuits calledsoftware-reconfigurable devices have been introduced which are able to adapt their hardware almost continuously to changes in the input data or processing. When the configuration phase and the execution phase are concurrent, the software-reconfigurable device is calledevolvable hardware (EHW). This paper examines an evolutionary navigation system for a mobile robot using a Boolean function approach implemented on gate-level evolvable hardware (EHW). The task of the mobile robot is to reach a goal represented by a colored ball while avoiding obstacles during its motion. We show that the Boolean function approach using dedicated evolution rules is sufficient to build the desired behavior and its hardware implementation using EHW allows to decrease the learning time for on-line training. We demonstrate the effectiveness of the generalization ability of the Boolean function approach using EHW due to its representation and evolution mechanism. The results show that the evolvable hardware configuration learned off-line in a simple environment creates a robust robot behavior which is able to perform the desired behaviors in more complex environments and which is insensitive to the gap between the real and simulated world. Didier Keymeulen, Ph.D.: He currently works as a senior research engineer at the Computer Science Division of Electrotechnical Laboratory, AIST, MITI, Japan. His research interests are in the design of adaptive physically embedded systems using biologically inspired complex dynamical systems. He studied electrical and computer science engineering at the Universite Libre de Bruxelles in 1987. He obtained his M. Sc. and PH. D. in Computer Science from the Artificial Intelligence Laboratory of the Vrije Universiteit Brussel, directed by Dr. Luc Steels, respectively in 1991 and 1994. He was the Belgium laureate of the Japanese JSPS Postdoctoral Fellowship for Foreign Researchers in 1995. Masaya Iwata, Ph.D.: He currently works as a researcher at the Computer Science Division of Electrotechnical Laboratory, AIST, MITI, Japan. His research interests are in developing adaptive hardware devices using genetic algorithms, and in their applications to pattern recognition and image compression. He received his B. E. in 1988, his M. E. in 1990, and his Ph. D. in 1993 in applied physics from the Osaka University. He was a postdoctoral fellow in optical computing at ONERA-CERT, Toulouse, France in 1993. Kenji Konaka: He is currently working as a software research engineer at the Humanoid Interaction Laboratory of the Intelligent Systems Division of Electrotechnical Laboratory, AIST, MITI, Japan. His current research interest is on real-time vision-based mobile robots working in cooperative mode. He has developped a highly interactive distributed real-time software and hardware platform for controlling a group of robots. Yasuo Kuniyoshi, Ph.D.: He is currently a senior research scientist and head of the Humanoid Interaction Laboratory at the Intelligent Systems Division of Electrotechnical Laboratory, AIST, MITI, Japan. His current research interest is on emergence of stable structures out of complex sensory-motor interactions by a humanoid robot. He received IJCAI93 Outstanding Paper A ward and several other awards in the field of intelligent robotics. He received the B. Eng. in applied physics in 1985, M. Eng. and Ph. D. in information engineering in 1988 and 1991 respectively, all from the University of Tokyo. Tetsuya Higuchi, Ph.D.: He heads the Evolvable Systems Laboratory in Electrotechnical Laboratory, AIST, MITI, Japan. He received B. E., M. E., Ph. D. degrees all in electrical engineering from Keio University in 1978, 1980, and 1984, respectively. His current interests include envolvable hardware systems, parallel processing architecture in artificial intelligence, and adaptive systems. He is also in charge of the adaptive devices group in the MITI national project, Real World Computing Project.     

Development of the multi-functional indoor service robot PSR systems

This paper discusses the development of the multi-functional indoor service robot PSR (Public Service Robots) systems. We have built three versions of PSR systems, which are the mobile manipulator PSR-1 and PSR-2, and the guide robot Jinny. The PSR robots successfully accomplished four target service tasks including a delivery, a patrol, a guide, and a floor cleaning task. These applications were defined from our investigation on service requirements of various indoor public environments. This paper shows how mobile-manipulator typed service robots were developed towards intelligent agents in a real environment. We identified system integration, multi-functionality, and autonomy considering environmental uncertainties as key research issues. Our research focused on solving these issues, and the solutions can be considered as the distinct features of our systems. Several key technologies were developed to satisfy technological consistency through the proposed integration scheme. Woojin Chung was born in Seoul, Korea, in 1970. He received the B.S. at the department of mechanical design and production engineering, Seoul National University in 1993. He received the M.S. degree in 1995 and Ph.D degree in 1998 at the department of Mechano-Informatics, the University of Tokyo. He was a senior research scientist at the Korea Institute of Science and Technology from 1998 to 2005. He joined the department of mechanical engineering, Korea University in 2005 as an assistant professor. He received an excellent paper award from the Robotics Society of Japan in 1996 and a best transactions paper award from the IEEE robotics and automation society in 2002. His research interests include the design and control of nonholonomic underactuated mechanical systems, trailer system design and control, mobile robot navigation, a dexterous robot hand and a system integration of intelligent robots. He is a member of the IEEE, the robotics society of Japan, the institute of control, automation and systems engineers and the Korea robotics society. Gunhee Kim received the B.S. and M.S. degrees at the department of mechanical engineering, Korea Advanced Institute of Science and Technology (KAIST), Korea, in 1999 and 2001, respectively. He was a research scientist in Intelligent Robotics Research Center, at Korea Institute of Science and Technology (KIST), Korea, from 2001 to 2006. Currently, he is a graduate student in the Robotics Institute, Carnegie Mellon University. His research interests include computer vision, artificial intelligence, mobile robot navigation, and discrete event systems. He is a member of the IEEE. Munsang Kim received the B.S. and M.S degree in Mechanical Engineering from the Seoul National University in 1980 and 1982 respectively and the Dr.-Ing. degree in Robotics from the Technical University of Berlin, Germany in 1987. Since 1987 he has been working as a research scientist at Korea Institute of Science and Technology. He has led the Intelligent Robotics Research Center since 2000 and became the director of the “Intelligent Robot—The Frontier 21 Program” since Oct. 2003. His current research interests are design and control of novel mobile manipulation systems, haptic device design and control, and sensor application to intelligent robots.     

MFR (Multipurpose Field Robot) for installing construction materials

The objective of the study was to propose a MFR (Multipurpose Field Robot) in hazardous operation environments. This system combines a basic system composed of a multi-DOF (Degree Of Freedom) manipulator and a mobile platform with an additional module for construction, national defense and emergency-rescue. According to an additional module type combined with a basic system, it can be used in a various fields. In this study, we describe a prototype of construction robot which helps a human operator handle easily construction materials in case of using the cooperation system on construction site. This study introduces an additional module for construction and a robot control algorithm for a HRC (Human-Robot Cooperation). In addition, it proposes a novel construction method to install construction materials with robot on construction site. Seung Yeol Lee received the B.S. degree from the Department of Mechanical Engineering, Myungji University, Seoul, Korea in 2002, and the M.S. degree from the Department of Mechatronics Engineering, Hanyang University, Seoul, Korea in 2005. He is a Ph.D. degree candidate from the Department of Mechanical Engineering, Hanyang University, Seoul, Korea. From 2003, He is currently a visiting researcher in the Research Institute of Technology, Construction Group at the Samsung Corporation, Korea conducting the design and implementation of construction robot and automation system for construction project. His research interests include design, control, and application of construction robots, field robotic systems and ergonomic design of robotic systems. He is a member of the Korea Society of Mechanical Engineers, Architectural Institute of Korea, and Ergonomics Society of Korea. Yong Seok Lee received the B.S. degree from the Department of Precision Mechanical Engineering, Kunsan national University, Kunsan, Korea in 2002, and the M.S. degree from the Department of Precision Mechanical Engineering, Hanyang University, Seoul, Korea in 2005. Currently, he is the Post Master in Hanyang University, Korea. His major interests include design and kinematic/dynamic analysis on multi-purpose field robots and service robots. He is a member of the Architectural Institute of Korea. Bum Seok Park received the B.S. degree from the Department of Mechanical Engineering, Hanyang University, Ansan, Kyung-gi Do, Korea in 1993, and the M.S. degree from the Department of Mechatronics Engineering, Hanyang University, Seoul, Korea in 1998. He is a Ph.D. from the Department of Mechatronics System Engineering, Hanyang University, Seoul, Korea From 2006. He is currently the post-doctor in Hanyang University, Korea. His major interests include embedded robot control system on multi-purpose field robot and service robot. He is a member of the Korea Society of Mechanical Engineers, Korean Society of Machine Tool Engineers. Sang Heon Lee graduated with the B.S. degree in Precision Mechanical Engineering from Hanyang University, Seoul, Korea in 1992. He received the M.S. degree in Precision Engineering from KAIST, Taejon, Korea in 1994 and the Ph.D. degree in Mechanical Engineering from KAIST in 2001. Currently, he is a senior researcher in Samsung Corporation, Korea. His major interests include the kinematic/dynamic analysis on multi-body system, application of field robots, and automation in construction. ChangSoo Han received the B.S. degree from the Department of Mechanical Engineering, Seoul National University Technology, Seoul, Korea in 1983, and the M.S. and Ph.D. degrees from the Department of Mechanical Engineering, University of Texas at Austin, in 1985 and 1989, respectively. From May 1988 to September 1989, he was a Research Assistant, Robotics Lab in Mechanical Engineering about manufacturing of the high resolution micro manipulator module. In March 1990, he joined Hanyang University, Ansan, Kyungki-Do, Korea as a Professor, Department of Mechanical Engineering. From March 1993 to February 1995, he was a Vice President, The Research Institute of Engineering & Technology of the Hanyang University. From August 1996 to July 1997, he was a Visiting Professor, Univ. of California at Berkeley. From September 1997 to February 1999, he was a Director, Hanyang Business Incubator. In August 2000, he joined a Branch President, The Korean Society of Mechanical Engineers. In January 2002, he joined a Committee Member, The Korean Society of Mechanical Engineers. From January 2001 to December 2001, he was an International Cooperation Director, The Institute of Control, Automation and Systems, Korea. His research interests include design, control, and application of robot, automation systems, and advanced vehicle.