A Realization of Haptic Training System by Multilateral Control

In recent years, the realization of a haptic system has been desired strongly in the fields of medical treatment and expert's skill acquisition. An integrated system design of the analysis of the interaction between a robot and the environment required for stable contact operation, an observation method of the reaction force from the environment, and the architecture of a bilateral control system are absolutely essential for acquisition and reproduction of a vivid tactile sensation. In this paper, a haptic training system is realized based on multilateral control. The law of action and reaction is attained by three robots. Bilateral control is extended, and multilateral control is introduced. Multilateral control is designed similarly as bilateral control based on modal decomposition; force is controlled in the common mode, and position is controlled in the differential mode. The scaling factors of position and force are set independently. Therefore, it is possible to change a trainer's assistant force according to a trainee's skill level. The proposed training system based on multilateral control will be a fundamental technology for the evolution of haptic devices     

Behavior-based artificial intelligence in miniature mobile robot

An intelligent mobile robot that implements concepts of mechatronics, mobile robotics, and behavior-based artificial intelligence has been developed. The design process for such a mobile robot employs a concept of simple trade-off between the mechanical, electrical, and computational systems for the benefit of improving the robots overall system performance. The main features of the robot, named SCAVENGER, are to navigate freely in a controlled environment, search for one or more target objects with known characteristics (colored golf balls), and avoid the other objects as obstacles. A combination of infrared sensors, color detectors, and bumper skirts is used to facilitate navigation and object recognition. The robots brain consists of an on-board MC68HC11 microcontroller, which is programmed in C. The control software implements behavior-based artificial intelligence, where the robots overall intelligence is made up of layers of several simple and primitive behaviors similar to those observed in insects. In this work, the design of the robots subsystems, where the implementation of mechatronics is most in effect, is covered in more detail with a particular interest in object recognition and collection systems.     

Design and control of robotic highway safety markers

Proper traffic control is critical in highway work zone safety. Traffic control devices such as signs, barricades, cones, and safety barrels are used. Accidents can occur because of improper work zone design, improper work zone housekeeping, and driver negligence. Automated safety devices could improve work zone design and housekeeping and therefore increase safety. This paper presents a mobile safety barrel robot. The robotic safety barrels can self-deploy and self-retrieve-removing workers from this dangerous task. The robots move independently so they can be deployed in parallel and can quickly reconfigure as the work zone changes. The system must be reliable and have a low per-robot cost. A robot that malfunctions could create a significant hazard. Also, multiple barrels are used and they are often struck by vehicles, therefore a high replacement cost is not practical. A six-robot system, which consists of a lead robot and five low-cost barrel robots, is described. A distributed planning and control approach is presented that reduces the per-robot cost by centralizing the intelligence and sensing while keeping communication bandwidth low by distributing local control. Test results are presented including a statistical analysis of the performance of the local robot controllers and field tests of the full system.     

Optimal control at energy performance index of the mobile robots following dynamically created trajectories

In practice, the problem of motion control of the wheeled mobile robots is often neglected. Wheeled mobile robots are strongly nonlinear systems and restricted by non-holonomic constraints. Motion control of such systems is not trivial task and usage of non-optimal control signals can lead to deterioration of the overall robot system's performance. In case of autonomous application of the mobile robots all parts of its control system should work perfectly. The paper presents the theory and application of the optimal control method at the energy performance index towards motion control of the two-wheeled mobile robot during the realisation of complex, dynamically created trajectories. With the use of the proposed control method the two-wheeled mobile robot can realise effectively the desired trajectory, which is generated ad-hoc by the navigation system of the robot. Thus the proposed method can be used for motion control of autonomous or semi-autonomous wheeled mobile robots. The presented results of both computer simulations and experiments indicate that the proposed method works effectively from the point of view of the motion control of two-wheeled mobile robot. Movement of the mobile robot appeared reliable and predictable during all the tests.     

Implementation and experimental study of a multiprocessor system for real-time model-based robot motion control

This paper presents the design and implementation of a multiprocessor system for real-time robot motion control. Full inverse dynamics compensation control laws in both joint and Cartesian spaces are used for developing parallel computation algorithms. The algorithms are divided into subtasks which are distributed among a fixed number of processors based on heuristic scheduling algorithms. The control laws are real-time tested on an experimental robot. The results present a feasible way for improving controller performance of current industrial robots.<>     

Autonomous decentralized control for formation of multiple mobile robots considering ability of robot

The purpose of this study is to control multiple mobile robots in formation considering the ability of a robot using the "Leader-Following" strategy. There are three features of this study. First, a performance index that shows mobile robot ability is quantified. Specifically, maximum acceleration and maximum velocity of a robot are defined by maximum admissible rotation and maximum continuous torque of a motor. The performance index is quantified from arrival time on the destination using these parameters. Second, a new controller is proposed based on the performance index, so that robots can be controlled according to robot ability. Third, a compliance controller using a virtual repulsion is suggested in this paper, so that each robot can avoid collision. Finally, simulation and experiments are done in a real-time system using RT-Messenger. RT-Messenger allows robots to transmit information regarding their positions to each other in real time. These results shows the validity of the proposed method.     

Controller design and implementation for industrial robots withflexible joints

A control strategy which consists of feedforward and feedback compensation loops is proposed to improve the performance of industrial robots. The feedforward loop is similar to the usual inverse-dynamics compensation. The feedback control loop uses a frequency-domain optimal controller. The design starts from the single-link case and is extended to the control of multilinkage flexible-joint robots. An experimental system consisting of a single-link robot is constructed for verifying the proposed control strategies. Experiments show good performance of the proposed control strategy in stiffening the flexible joint and in tracking desired polynomial-type trajectories     

Human-following mobile robot in a distributed intelligent sensor network

The robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, humans and robots need to be in close proximity to each other as much as possible. Moreover, it is necessary for their interactions to occur naturally. It is desirable for a robot to carry out human following, as one of the human-affinitive movements. The human-following robot requires several techniques: the recognition of the target human, the recognition of the environment around the robot, and the control strategy for following a human stably. In this research, an intelligent environment is used in order to achieve these goals. An intelligent environment is a space in which many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents providing humans with services. A mobile robot is controlled to follow a walking human using distributed intelligent sensors as stably and precisely as possible. The control law based on the virtual spring model is proposed to mitigate the difference of movement between the human and the mobile robot. The proposed control law is applied to the intelligent environment and its performance is verified by the computer simulation and the experiment.     

A Multidirectional Locomotion Light-Driven Soft Crawling Robot

Soft robots based on bionics with multi-freedom and communication abilities have attracted extensive attention in recent years. However, the solutions for soft robots with multidirectional locomotion currently concentrate on complex drive modes and exhibit application unfriendliness. In this work, an untethered multidirectional locomotion light-driven soft crawling robot is proposed with the integration of communication module, which can traverse in four directions with a fixed near-infrared (NIR) light source and is also capable of positioning and perception. Owing to the photothermal response of graphene oxide and ingenious structural design, the critical states of robot deformation can be determined simply by controlling the duration of NIR light, ultimately resulting in different crawling directions. Furthermore, a communication module is integrated into the robot enabling the robot to locate and sense humidity by magnetic coupling. The proposed robot provides an innovative strategy for the design and integration of multidirectional locomotion soft crawling robots, showing great potential in intelligent robots.     

Global localization of multirobot formations using ceiling vision SLAM strategy

Global localization is an important matter in multirobot formations, but the issue has not been sufficiently studied yet. In this paper, we successfully extend the single robot ceiling vision SLAM to multirobot formations for addressing global localization problem. Each robot is equipped with a monocular camera that looks upward to the ceiling. The monocular camera system used for ceiling observation appears to be more convenient than other active sensors such as laser and panoramic camera. A public global map shared by every robot is developed for positioning update. Two global localization strategies are proposed. The first strategy is to globally localize one robot only and then localize the others based on the relative poses amongst the robots. The second strategy is to globally localize all the robots simultaneously. The former requires less computational resource, and the later exhibits better localization performance. A feature-based matching approach is utilized to calculate the relative poses amongst the robots. Simulation experiments are finally performed to demonstrate the effectiveness of the proposed approach.     

基于分布式的移动机器人控制系统设计与实现

移动机器人是近年来研究的热点,针对机器人系统自由度多,可靠性和实时性要求高的特点,提出了一种基于分布式的移动机器人控制系统。利用多借点连接方式的网络拓扑机构,将其他设备和多个机器人连接组成机器人控制系统,以控制芯片ARM Cortex-A9和STM32F407为基础,将开源操作系统植入到开源嵌入式系统中,设计分布式上位机控制软件和下拉机程序,设计了基于分布式的移动机器人控制系统的搭建,实现对分布式移动机器人的控制。该分布式移动机器人软硬件开源、性能高、成本低、具有很好的可扩展性、实时性和稳定性。     

Sensor-based design of a Delta parallel robot

This paper proposes a sensor-based design methodology in order to design a Delta robot with guaranteed accuracy performance for a dedicated sensor-based controller. This sensor-based design methodology takes into account the accuracy performance of the controller in the design process in order to find optimal geometric parameters of the robot. Three types of controllers are envisaged to be applied to the Delta robot, leading to three different optimal designs: leg-direction-based visual servoing, line-based visual servoing and image moment visual servoing. Based on these three controllers, positioning error models taking into account the error of observation coming from the camera are developed, and the controller singularities are analyzed. Then, design optimization problems are formulated in order to find the optimal geometric parameters and relevant parameters of the camera for the Delta robot for each type of controller. Prototypes of Delta robots have been manufactured based on the obtained optimum design parameters in order to test the performance of the pair {robot-controller}.     

Neurofuzzy control of modular and reconfigurable robots

In recent years, the concept of modular and reconfigurable robotics emerged as a means for flexible and versatile automation. This concept allows for the execution of many complex tasks that cannot be performed by fixed-configuration manipulators. Nevertheless, reconfigurable robots introduce a challenging level of complexity to the problem of design of controllers that can handle a wide range of robot configurations with reliable performance. This paper addresses the position control of modular and reconfigurable robots. We develop a practical intelligent-control architecture that can be easily used in the presence of dynamic parameter uncertainty and unmodeled disturbances. The architecture requires no a priori knowledge of the system-dynamics parameters. Adaptive control is provided using fuzzy gain tuning of proportional-integral-derivative parameters in the presence of external disturbances. The architecture also provides learning control using feedforward neural networks. Moreover, the architecture has the capability of updating the adaptive control under reconfigurability. Experiments on a modular robot test bed are reported to validate the effectiveness of the control methodology.     

A novel ball handling mechanism for the RoboCup middle size league

This paper presents the hardware design and control design of a novel ball handling mechanism in the RoboCup Middle Size League used by team Tech United Eindhoven. The ball handling mechanism consist of two levers with two actively driven wheels attached to it, to exert forces on the ball in order to control its position relative to the robot. The proposed design is fully compliant to the rules and regulations imposed by the RoboCup Middle Size League community. The control design consists of a cascaded velocity and position feedback loop in combination with a feedforward controller which compensates for the robots ego motion. The proposed design is validated on a robot used by the Tech United Eindhoven team.     

Adaptive sliding mode fuzzy control for unknown robots with arbitrarily-switched constraints

This article addresses the control problem of robots with unknown dynamics and arbitrarily-switched unknown constraints. Such kind of robots will be shown to be unknown hybrid systems with arbitrary switching and an Adaptive Sliding Mode Fuzzy Control (ASMFC) strategy is proposed that handles the unknown dynamics of the robot along with the unknown constraints arbitrary switching. The ASMFC is a synergy of finding a Common Lyapunov Function (CLF) between the resulted switched subsystems of the considered robots, employing the Fuzzy Logic Systems (FLS), and the use of the Sliding Mode Control (SMC). The CLF accommodates the constraints arbitrary switching, the SMC adds robustness against possible parameters drift, and the FLS approximates the unknown robot dynamics. All unknown parameters are adapted online and all closed loop signals are guaranteed to be bounded. The proposed strategy is validated by conducting an experiment on a KUKA Lightweight Robot (LWR) doing a typical force-guided peg-in-hole assembly task that falls in the category of robot systems under consideration. Excellent tracking performance is obtained when using the ASMFC strategy. Comparison is conducted with the performance of a PD controller that is widely used in commanding industrial robots and the superiority of the proposed strategy is shown.     

A systematic design procedure of force controllers for industrialrobots

In this paper, the problem of designing a force controller for industrial robots with a positional interface is addressed. A systematic design procedure to compute structures and parameters of the controller is devised, to provide a useful tool for rapid and robust setup of force control at the industrial level. The proposed method for synthesis of the force controller simply requires technology parameters provided by the robot manufacturer and desired performance expressed in non-technical terms by the user. The automated design algorithm is described in detail and its effectiveness was proved by experiments on two different industrial robots. On the first robotic setup, the performance of the designed controllers was evaluated by analyzing the experimental results of responses to canonical reference signals; on the second setup, the controller reliability and applicability at the industrial level were demonstrated through the results of a mechanical parts mating task     

Development and Implementation of a Collaborative Workspace for Industrial Robots Utilizing a Practical Path Adaptation Algorithm and Augmented Reality

The idea of humans and robots coexisting in manufacturing environments has increased the importance of personnel safety. Current practice to provide human safety in a conventional industrial robotic application is to put the robot in a cell enclosed by fences that occupies a large area in the environment. If someone enters this robotic cell, the robot ceases its movement immediately that leads to significant delays in the production cycle. In this paper, we present a new collaborative workspace concept for conventional industrial robots in order to eliminate fences and to avoid delays as much as possible. The proposed concept relies on a novel path adaptation algorithm and an augmented reality-based warning system. The algorithm, which makes the robot adaptable to human interventions, is unique in a sense that it can be applied to variety of industrial robots without requiring changes in the robot controller. Besides, the warning system provides additional safety features to the collaborative workspace through a projector and a head-mounted display. We demonstrate the feasibility of the proposed concept with an industrial robot in a realistic palletizing application. Several experiments were carried out to test the performance along with a user study. Performance test results indicate that the robot is able to perform three actions according to the minimum distance between the human and the robot in case of a human violation: slowdown, avoidance, and full stop. Qualitative performance tests results show that augmented reality improves the perception of safety and collaboration but negatively affects physical comfort. Overall, the proposed concept provides a practical and implementable solution for conventional industrial robots missing collaborative features.     

Adaptive impedance control of a haptic interface

Teleoperation enables an operator to manipulate remote objects. One of the main goals in teleoperation research is to provide the operator with the feeling of the telepresent object and of being present at the remote site. In order for this to happen, a master robot must be designed as a bilateral control system that can transmit position commands to a slave robot and reflect the interaction force. A newly proposed adaptive impedance algorithm is applied to the force control of a haptic interface that has been developed as a master robot. With the movement of the haptic interface for position command generation, the impedance between an operator and the haptic interface varies dynamically. When the impedance parameters and the dynamics of the haptic interface are known precisely, many model based control theories and methods can be used to control the interface accurately. However, due to the parameters’ variations and the uncertainty in the dynamic model, it is difficult to control the interface precisely. Therefore, this paper proposes a new adaptive impedance control algorithm and experimentally verifies the effectiveness of the algorithm for control of the haptic interface.     

Novel Biological Based Method for Robot Navigation and Localization

The capability and reliability are crucial characteristics of mobile robots while navigating in complex environments. These robots are expected to perform many useful tasks which can improve the quality of life greatly. Robot localization and decision-making are the most important cognitive processes during navigation. However, most of these algorithms are not efficient and are challenging tasks while robots navigate through complex environments. In this paper, we propose a biologically inspired method for robot decision-making, based on rat’s brain signals. Rodents accurately and rapidly navigate in complex spaces by localizing themselves in reference to the surrounding environmental landmarks. Firstly, we analyzed the rats’ strategies while navigating in the complex Y-maze, and recorded local field potentials (LFPs), simultaneously. The recorded LFPs were processed and different features were extracted which were used as the input in the artificial neural network (ANN) to predict the rat’s decision-making in each junction. The ANN performance was tested in a real robot and good performance is achieved. The implementation of our method on a real robot, demonstrates its abilities to imitate the rat’s decision-making and integrate the internal states with external sensors, in order to perform reliable navigation in complex maze.     

Spiral-Shape Fast-Moving Soft Robots

Soft robots typically exhibit limited agility due to inherent properties of soft materials. The structural design of soft robots is one of the key elements to improve their mobility. Inspired by the Archimedean spiral geometry in nature, here, a fast-moving spiral-shaped soft robot made of a piezoelectric composite with an amorphous piezoelectric vinylidene fluoride film and a layer of copper tape is presented. The soft robot demonstrates a forward locomotion speed of 76 body length per second under the first-order resonance frequency and a backward locomotion speed of 11.26 body length per second at the third-order resonance frequency. Moreover, the multitasking capabilities of the soft robot in slope climbing, step jumping, load carrying, and steering are demonstrated. The soft robot can escape from a relatively confined space without external control and human intervention. An untethered robot with a battery and a flexible circuit (a payload of 1.665 g and a total weight of 1.815 g) can move at an absolute speed of 20 mm s⁻¹ (1 body length per second). This study opens a new generic design paradigm for next-generation fast-moving soft robots that are applicable for multifunctionality at small scales.