一种编队控制的动态调整与规划方法

This article is concerned with cooperative control problems in formation of mobile robots under the nonholonomic constraints that certain geometrical constraints are imposed on multiple mobile robots throughout their travel. For this purpose, a new method of motion control for formation is presented, which is based on the dynamic regulation and scheduling scheme. It is attractive for its adaptability to the formation structure and desired trajectory. The quality of formation keeping can be evaluated by the instantaneous errors of formation offset and spacing distance. Some kinematics laws are developed to regulate and maintain the formation shape. Simulation results and data analysis show the validity of the proposed approach for a group of robots.     

Distributed active fault tolerant control design against actuator faults for multiple mobile robots

This paper investigates the active fault tolerant cooperative control problem for a team of wheeled mobile robots whose actuators are subjected to partial or severe faults during the team mission. The cooperative robots network only requires the interaction between local neighbors over the undirected graph and does not assume the existence of leaders in the network. We assume that the communication exists all the time during the mission. To avoid the system''s deterioration in the event of a fault, a set of extended Kalman filters (EKFs) are employed to monitor the actuators'' behavior for each robot. Then, based on the online information given by the EKFs, a reconfigurable sliding mode control is proposed to take an appropriate action to accommodate that fault. In this research study, two types of faults are considered. The first type is a partial actuator fault in which the faulty actuator responds to a partial of its control input, but still has the capability to continue the mission when the control law is reconfigured. In addition, the controllers of the remaining healthy robots are reconfigured simultaneously to move within the same capability of the faulty one. The second type is a severe actuator fault in which the faulty actuator is subjected to a large loss of its control input, and that lead the exclusion of that faulty robot from the team formation. Consequently, the remaining healthy robots update their reference trajectories and form a new formation shape to achieve the rest of the team mission.     

In-hand haptic perception in dexterous manipulations

Dexterous in-hand manipulation with multi-finger robotic hands is a hot topic in robotics.Recently many famous multi-finger robotic hands have been developed.Though a lot of research has been done on them;in-hand manipulation is still a challenge.One of its issues lies in the uncertainty of interaction states.In this paper we research robot-object interaction from a novel angle called haptic exploration.This method helps robots acquire the ability to explore the robot-object interaction.In in-hand manipulation tasks,haptic exploration is a process where the robot pushes on in-hand objects slightly in different directions,and meanwhile perceives the haptic feedback to estimate the interaction state.In this paper a new single finger push model is proposed for analyzing the haptic feedback,which is similar to traditional impedance control of robot arm.In this model the stiffness of fingers,the deformation on contact surface,and the change of object’s pos(position and attitude)are considered.Furthermore,a push resistance is given to describe the haptic feedback acquired from a slight push.Finally,real robotic experiments are conducted to verify the feasibility of proposed method.     

Coordination of multiple mobile robots with limited communication range in pursuit of single mobile target in cluttered environment

This paper addresses the problem of coordinating multiple mobile robots in searching for and capturing a mobile target, with the aim of reducing the capture time. Compared with the previous algorithms, we assume that the target can be detected by any robot and captured successfully by two or more robots. In this paper, we assume that each robot has a limited communication range. We maintain the robots within a mobile network to guarantee the successful capture. In addition, the motion of the target is modeled and incorporated into directing the motion of the robots to reduce the capture time. A coordination algorithm considering both aspects is proposed. This algorithm can greatly reduce the expected time of capturing the mobile target. Finally, we validate the algorithm by the simulations and experiments.     

Searching a Polygonal Region by Two Guards

We study the problem of searching for a mobile intruder in a polygonal region P by two guards. The objective is to decide whether there should exist a search schedule for the two guards to detect the intruder, no matter how fast the intruder moves, and if so, generate a search schedule. During the search, the two guards are required to walk on the boundary of P continuously and be mutually visible all the time. We present a characterization of the class of polygons searchable by two guards in terms of non-redundant components, and thus solve a long-standing open problem in computational geometry. Also, we give an optimal O(n) time algorithm to determine the two-guard searchability in a polygon, and an O(nlog n m) time algorithm to generate a search schedule, if it exists, where n is the number of vertices of P and m (≤n2) is the number of search instructions reported.     

Creative Strategies to Teach Healthcare Professionals Using iPad Technology

PUCRS University has been promoting the use of iPads in its classrooms in the light of student familiarity with these mobile devices. The opportunity then arises to use such resources to improve and stimulate the teaching and learning processes. Competence in manual skills and critical thinking are expected from health professionals in order to carry out their work. However, the development of these skills is restricted to real opportunities in the field of practice at a time when the student is experiencing supervised assisted practice. The objective of this article is to report an experience with the use of iPads in the teaching of nursing and nutrition undergraduates, as a creative educational methodology and a tool for the simulation of skills and critical thinking, helping to increase general and specific cognitive abilities in support of problem solving.     

Editorial: Special issue on cyber-physical systems and intelligent control in honor of the 65th birthday of Professor Bijoy K. Ghosh

It is our great pleasure to organize this special issue in Control Theory and Technology in honor of the 65th birthday of Professor Bijoy K. Ghosh, who has made many truly outstanding contributions to the field of systems and control through the years, which include robust and nonlinear control, robotics and machine vision in his earlier research period, and his recent focus on biology and biomedical modeling, learning control and multi-agent systems to name a few. Professor Ghosh obtained his Bachelor’s degree and Master’s degree in Electrical Engineering at Birla Institute of Technology and Science, Pilani, India, in 1977, and at Indian Institute of Technology, Kanpur, India, in 1979, respectively. In 1983, he obtained his Ph.D. in Engineering at Harvard University. Then, he worked at Washington University in Saint Louis for 23 years. In 2007, he became a Regent Professor of Mathematics and Statistics at Texas Tech University, Lubbock, Texas. In 2018, he joined the School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China. In the early research period, he followed Professors Roger W. Brockett and Y. C. Ho and interacted with other control theorists, such as Prof. H. Kimura, Profs. M. Hazewinkel and J. C. Willems, Profs. K. S. Narendra and Steve Morse, Prof. Clyde Martin and Prof. H. F. Chen. He applied his research to Aerospace Control, while interacting with engineers in McDonell Douglas Aerospace Company in St. Louis, USA. This research culminated the Donald P. Eckmann Award in 1988 with citation “in recognition of his outstanding contributions in the field of Automatic Control”. Starting from 1990, he started working in the field of Robotics and Machine Vision. As an active member of the IEEE, he established the Technical Committee on Sensor Guided Manipulation in Automation (SGMA). In 2000, he became a Fellow of the IEEE with citation “for fundamental contributions to system theory with applications to robust control, vision and multisensory fusion”. During 2001–2006, he established the IEEE Technical Committee on Bio Systems and Control. He became a Fellow of IFAC in 2014 with citation “for seminal contributions to dynamic modeling in machine vision, biology and biomedical science”.     

Heuristic dynamic programming-based learning control for discrete-time disturbed multi-agent systems

Owing to extensive applications in many fields, the synchronization problem has been widely investigated in multi-agent systems. The synchronization for multi-agent systems is a pivotal issue, which means that under the designed control policy, the output of systems or the state of each agent can be consistent with the leader. The purpose of this paper is to investigate a heuristic dynamic programming (HDP)-based learning tracking control for discrete-time multi-agent systems to achieve synchronization while considering disturbances in systems. Besides, due to the difficulty of solving the coupled Hamilton– Jacobi–Bellman equation analytically, an improved HDP learning control algorithm is proposed to realize the synchronization between the leader and all following agents, which is executed by an action-critic neural network. The action and critic neural network are utilized to learn the optimal control policy and cost function, respectively, by means of introducing an auxiliary action network. Finally, two numerical examples and a practical application of mobile robots are presented to demonstrate the control performance of the HDP-based learning control algorithm.     

Introduction to the Six Leading Editors简

Wen-Guang Ohen is a professor and associate head in Department of Computer ScieI~ce and Technology, Tsinghua University, Beijing, where he has been teaching since 2003. He received the B.S. and Ph.D. degrees in computer science from Tsingtma University in 1995 and 20（}（} respectively. His research interest is in parallel and distributed computing. He is a China Computer Federation （CCF） Distinguished Member and CCF Distinguished Speaker, ACM member and vice chair of ACM China Council. He has served in program committees of a w~riety of major conferences in the parallel and distributed computing area, inchlding PLDI, PPoPP, CGO, CCGrid, IPDPS, APSYS and ICPP. He is the editor-in-chief of Communication of ACM China Edition and sectioH editor- in-chief of the Communications of CCF Translation Section. He also serves as editor of Journal ofSoftware and Journal of Chinese Computer Systems.     

Mobile agent-enabled framework for structuring and building distributed systems on the internet

Mobile agent has shown its promise as a powerful means to complement and enhance existing technology in various application areas. In particular, existing work has demonstrated that MA can simplify the development and improve the performance of certain classes of distributed applications, especially for those running on a wide-area, heterogeneous, and dynamic networking environment like the Internet. In our previous work, we extended the application of MA to the design of distributed control functions, which require the maintenance of logical relationship among and/or coordination of proc- essing entities in a distributed system. A novel framework is presented for structuring and building distributed systems, which use cooperating mobile agents as an aid to carry out coordination and cooperation tasks in distributed systems. The framework has been used for designing various distributed control functions such as load balancing and mutual ex- clusion in our previous work. In this paper, we use the framework to propose a novel ap- proach to detecting deadlocks in distributed system by using mobile agents, which dem- onstrates the advantage of being adaptive and flexible of mobile agents. We first describe the MAEDD (Mobile Agent Enabled Deadlock Detection) scheme, in which mobile agents are dispatched to collect and analyze deadlock information distributed across the network sites and, based on the analysis, to detect and resolve deadlocks. Then the design of an adaptive hybrid algorithm derived from the framework is presented. The algorithm can dynamically adapt itself to the changes in system state by using different deadlock detec- tion strategies. The performance of the proposed algorithm has been evaluated using simulations. The results show that the algorithm can outperform existing algorithms that use a fixed deadlock detection strategy.     

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.     

Particle swarm-based olfactory guided search

This article presents a new algorithm for searching odour sources across large search spaces with groups of mobile robots. The proposed algorithm is inspired in the particle swarm optimization (PSO) method. In this method, the search space is sampled by dynamic particles that use their knowledge about the previous sampled space and share this knowledge with other neighbour searching particles allowing the emergence of efficient local searching behaviours. In this case, chemical searching cues about the potential existence of upwind odour sources are exchanged. By default, the agents tend to avoid each other, leading to the emergence of exploration behaviours when no chemical cue exists in the neighbourhood. This behaviour improves the global searching performance. The article explains the relevance of searching odour sources with autonomous agents and identifies the main difficulties for solving this problem. A major difficulty is related with the chaotic nature of the odour transport in the atmosphere due to turbulent phenomena. The characteristics of this problem are described in detail and a simulation framework for testing and analysing different odour searching algorithms was constructed. The proposed PSO-based searching algorithm and modified versions of gradient-based searching and biased random walk-based searching strategies were tested in different environmental conditions and the results, showing the effectiveness of the proposed strategy, were analysed and discussed. Lino Marques is an auxiliary professor in the Department of Electrical Engineering, University of Coimbra, and he is a researcher in the Institute for Systems and Robotics (ISR-UC). He received his Licenciatura, MSc. and Ph.D. degrees in Electrical Engineering from the University of Coimbra, Portugal. His main research interests include embedded systems, mechatronics, robotics for risky environments, optical range sensors, artificial olfaction systems and mobile robot olfaction. Urbano Nunes is an associate professor of the University of Coimbra and a researcher of the Institute for Systems and Robotics (ISR-UC), where he has been involved in research and teaching since 1983. He received his Licenciatura and Ph.D. degrees in Electrical Engineering from the University of Coimbra, Portugal, in 1983 and 1995, respectively. He is the coordinator of the Mechatronics Laboratory of ISR-UC, and had been responsible for several funded projects in the areas of mobile robotics and intelligent vehicles. His research interests include mobile robotics, intelligent vehicles, and mechatronics. Professor Urbano Nunes serves on the Editorial Board of the Journal on Machine Intelligence and Robotic Control, and currently he is co-chair of the IEEE RAS TC on Intelligent Transportation Systems. Currently he is the Program Chair of the IEEE ITSC2006. He has served as General Co-Chair of ICAR 2003 and as member of several program committees of international conferences. Aníbal 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.     

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.     

Mobile robot interception using human navigational principles: Comparison of active versus passive tracking algorithms

We examined human navigational principles for intercepting a projected object and tested their application in the design of navigational algorithms for mobile robots. These perceptual principles utilize a viewer-based geometry that allows the robot to approach the target without need of time-consuming calculations to determine the world coordinates of either itself or the target. Human research supports the use of an Optical Acceleration Cancellation (OAC) strategy to achieve interception. Here, the fielder selects a running path that nulls out the acceleration of the retinal image of an approaching ball, and maintains an image that rises at a constant rate throughout the task. We compare two robotic control algorithms for implementing the OAC strategy in cases in which the target remains in the sagittal plane headed directly toward the robot (which only moves forward or backward). In the “passive” algorithm, the robot keeps the orientation of the camera constant, and the image of the ball rises at a constant rate. In the “active” algorithm, the robot maintains a camera fixation that is centered on the image of the ball and keeps the tangent of the camera angle rising at a constant rate. Performance was superior with the active algorithm in both computer simulations and trials with actual mobile robots. The performance advantage is principally due to the higher gain and effectively wider viewing angle when the camera remains centered on the ball image. The findings confirm the viability and robustness of human perceptual principles in the design of mobile robot algorithms for tasks like interception. Thomas Sugar works in the areas of mobile robot navigation and wearable robotics assisting gait of stroke survivors. In mobile robot navigation, he is interested in combining human perceptual principles with mobile robotics. He majored in business and mechanical engineering for his Bachelors degrees and mechanical engineering for his Doctoral degree all from the University of Pennsylvania. In industry, he worked as a project engineer for W. L. Gore and Associates. He has been a faculty member in the Department of Mechanical and Aerospace Engineering and the Department of Engineering at Arizona State University. His research is currently funded by three grants from the National Sciences Foundation and the National Institutes of Health, and focuses on perception and action, and wearable robots using tunable springs. Michael McBeath works in the area combining Psychology and Engineering. He majored in both fields for his Bachelors degree from Brown University and again for his Doctoral degree from Stanford University. Parallel to his academic career, he worked as a research scientist at NASA—Ames Research Center, and at the Interval Corporation, a technology think tank funded by Microsoft co-founder, Paul Allen. He has been a faculty member in the Department of Psychology at Kent State University and at Arizona State University, where he is Program Director for the Cognition and Behavior area, and is on the Executive Committee for the interdisciplinary Arts, Media, and Engineering program. His research is currently funded by three grants from the National Sciences Foundation, and focuses on perception and action, particularly in sports. He is best known for his research on navigational strategies used by baseball players, animals, and robots.     

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.     

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.     

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.     

Formation Planning and Control of UGVs with Trailers

This paper provides a framework for planning and control of formations of multiple unmanned ground vehicles with trailers to traverse between goal points in an idealized, disturbance-free environment. This framework allows on-line planning of the formations using the A* search algorithm based on current sensor data. The formation is allowed to dynamically change in order to avoid obstacles in the environment while minimizing a cost function aimed at obtaining collision-free and deadlock-free paths. Based on a feasible path for a leader of the group and the differential flatness property of a truck-tractor-trailer system, the trajectory planner satisfies the kinematic constraints of the individual vehicles while accounting for inter-vehicle collisions and path constraints. Also, optimization techniques are used to on-line change the path of the truck-tractor-trailer system. Illustrative simulations with simplified models of John Deere vehicles with trailers in formations are presented. Laboratory experiments are also performed on a 2-wheel differential drive mobile vehicle attached with a trailer cart on a flat, smooth floor using overhead cameras for precise references. The concluding section of the paper discusses some of the additional work needed to make the results applicable in a real-world environment. Yongxing Hao received the Ph.D. degree in Mechanical Engineering with specialty in Automatic Control and Robotics from the University of Delaware, Newark, DE, in 2004. Prior to joining Hurco Companies, Inc. in 2005, he was a Research Assistant Professor of Electrical and Computer Engineering at West Virginia University Institute of Technology. He received his M.S. and B.S. in Electrical Engineering from Beijing University of Technology and North China University of Technology in 1998 and 1995, respectively.He is a member of IEEE. His research interests include motion planning, controls, robotics, optimization, multi-agent systems and their applications in planning and control of UGVs, UAVs and CNC machines. Sunil K. Agrawal received the Ph.D. degree in Mechanical Engineering from Stanford University, Stanford, CA, in 1990. He has worked in universities, government laboratories, and industries throughout the world. He is currently a Professor of Mechanical Engineering at the University of Delaware, Newark. His research has made contributions in robotics and control, including novel designs of robots and autonomous systems, computational algorithms for planning and optimization of dynamic systems. His work has yielded over 140 technical publications and two books. Dr. Agrawal received the National Science Foundation Presidential Faculty Fellowship from the White House and a Freidrich Wilheim Bessel prize from Alexander von Humboldt Foundation in Germany. He was elected to be a Fellow of American Society of Mechanical Engineers in February 2004.     

Towards Autonomous Indoor Micro VTOL

Recent progress in sensor technology, data processing and integrated actuators has made the development of miniature flying robots fully possible. Micro VTOL¹ systems represent a useful class of flying robots because of their strong capabilities for small-area monitoring, building exploration and intervention in hostile environments. In this paper, we emphasize the importance of the VTOL vehicle as a candidate for the high-mobility system emergence. In addition, we describe the approach that our lab² has taken to micro VTOL evolving towards autonomy and present the mechanical design, dynamic modelling, sensing, and control of our indoor VTOL autonomous robot OS4.³Samir Bouabdallah is research assistant and Ph.D. student at the Autonomous Systems Lab (ASL) at the Swiss Federal Institute of Technology, Lausanne, (EPFL). He got his Masters in Electrical Engineer from Abu Bakr Belkaid University (ABBU) Tlemcen, Algeria in 2001. His master thesis was the development of an autonomous mobile robot for academic research. His current research interests are control systems and design optimization of VTOL flying robots.Pierpaolo Murrieri is a Ph.D. student at the Centro Interdipartimentale E. Piaggio and Dipartimento Sistemi Elettrici ed Automazione (DSEA) at the University of Pisa. He got his Master in Electrical Engineer from University of Pisa in 2000. His master thesis was about the registration of biomedical images. His current research interests are mobile robotics, nonlinear control and artificial vision.Roland Siegwart is director of the Autonomous Systems Lab (ASL) at the Swiss Federal Institute of Technology Lausanne (EPFL). He received his Masters in Mechanical Engineering in 1983 and his Ph.D. in 1989 at the Swiss Federal Institute of Technology Zurich (ETH). In 1989/90 he spent one year as postdoc at Stanford University. From 1991 to 1996 he worked part time as R&D director at MECOS Traxler AG and as a lecturer and deputy head at the Institute of Robotics, ETH. In 1996 he joined EPFL as full professor where he is working in robotics and mechatronics, namely mobile robot navigation, space robotics, human-robot interaction, all terrain locomotion and micro-robotics. Roland Siegwart is member of various scientific committees and cofounder of several spin-off companies.     

A biomimetic robot for tracking specific odors in turbulent plumes

Two basic tasks must be performed by an olfactory robot tracking a specific odor source: navigate in a turbulent odor plume and recognize an odor regardless of its concentration. For these two tasks, we propose simple biologically inspired strategies, well suited for building dedicated circuits and for on-board implementation on real robots. The odor recognition system is based on a spiking neural network using a synchronization coding scheme. The robot navigation system is based on the use of bilateral comparison between two spatially separated gas sensors arrays at either side of the robot. We propose binary or analog navigation laws depending on the nature of the available sensory information extracted from the plume structure (isolated odor patches or smoother concentration field). Dominique Martinez received his PhD degree in electrical and electronic engineering from the University Paul Sabatier in Toulouse, France, in 1992. He was a post-doctoral fellow at MIT, Dept. Brain and Cog. Sciences, and Harvard, VLSI group, in Cambridge, MA, USA, in 1992 and 1994, respectively. From 1993 to 1999 he worked at LAAS-CNRS in Toulouse where his research interests were concerned with machine learning (artificial neural networks, support vector machines). In 2000 he joined LORIA in Nancy and his research interests currently focus on biologically-plausible spiking neural networks for sensory processing, with particular application to artificial olfaction (neuromorphic electronic noses). Olivier Rochel obtained his PhD from the LORIA/Université H. Poincaré, in Nancy, France, where he was working on modelling large and complex networks of biological neurons, and bio-inspired robotics. Now working in the Biosystems Group at the university of Leeds, his research interests lie in multi-disciplinary studies in computational neuroscience, modelling and simulation techniques in general, and biological data analysis. Etienne Hugues has received his Ph.D. in theoretical physics from Paris XI University (Orsay). He has been a postdoctoral researcher at INRIA where he worked on olfactory perception in animals and robots. He is now a postdoctoral researcher in the Physics Department of SUNY at Buffalo. His main research interest is in computational neuroscience.