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Self-organizing behavior of a multi-robot system by a neural network approach

Self-organizing behavior of a multi-robot system by a neural...

引用

IEEE International Workshop on Intelligent Robots and systems (IROS)

作者： Anmin Zhu S.X. Yang Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph ONT Canada

In this paper, a novel neural network approach to self-organizing behavior of a multi-robot system is proposed, which is capable of controlling a group of mobile robots to achieve multiple tasks at several different locations, such that the desired number of robots will arrive at every target location from any arbitrary initial robot locations. The proposed model is based on a self-organizing map (SOM) neural network. Unlike some conventional approaches to multi-robot path planning for multiple tasks where the task assignment and path planning are handled separately, this model combines the robot task requirement and motion planning together, such that the robots can start to move once the total tasks are set. The robot navigation can be dynamically adjusted to guarantee each target location will have the desired number of robots, even under unexpected uncertainties, such as one robot breaks down. In addition, unlike the conventional models that are suitable for static environment only, the proposed approach is also capable of dealing with changing environment. The effectiveness of the proposed approach is demonstrated by simulation studies.

关键词： Multirobot systems Neural networks Robot kinematics Mobile robots Robot sensing systems Intelligent robots Path planning Control systems Costs Intelligent systems

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Genetic algorithm based path planning for a mobile robot

Genetic algorithm based path planning for a mobile robot

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jianping Tu S.X. Yang Advanced Robotics and Intelligent Systems ARIS Laboratory School of Engineering University of Guelph Guelph ONT Canada

In this paper, a novel genetic algorithm based approach to path planning of a mobile robot is proposed. The major characteristic of the proposed algorithm is that the chromosome has a variable length. The location target and obstacles are included to find a path for a mobile robot in an environment that is a 2D workplace discretized into a grid net. Each cell in the net is a gene. The number of genes in one chromosome depends on the environment. The locations of the robot, the target and the obstacle are marked in the workplace. The proposed algorithm is capable of generating collision-free paths for a mobile robot in both static and dynamic environments. In a static environment, the generated robot path is optimal in the sense of the shortest distance. The effectiveness of the proposed model is demonstrated by simulation studies.

关键词： Genetic algorithms Path planning Mobile robots Biological cells Fuzzy logic Evolutionary computation Intelligent robots Employment Robot sensing systems Fuzzy systems

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A neuro-fuzzy approach to obstacle avoidance of a nonholonomic mobile robot

A neuro-fuzzy approach to obstacle avoidance of a nonholonom...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Xiaochuan Wang S.X. Yang Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph ONT Canada

In this paper, a neuro-fuzzy control system is developed for obstacle avoidance of nonholonomic mobile robot built in the ARIS lab. A combination of four infrared sensors is equipped to detect the distance to obstacles around the mobile robot. The distance information is processed by the proposed neuro-fuzzy controller to adjust the velocities of two separate driven wheels of the robot. Eighteen fuzzy rules are developed for the obstacle avoidance. Experiments demonstrate the effectiveness of the developed neuro-fuzzy controller.

关键词： Mobile robots Fuzzy logic Intelligent robots Control systems Wheels Neural networks Automatic control Robot sensing systems Service robots Orbital robotics

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A fuzzy neural dynamics based tracking controller for a nonholonomic mobile robot

A fuzzy neural dynamics based tracking controller for a nonh...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Yanrong Hu S.X. Yang Advanced Robotics and Intelligent Systems (AFUS) Laboratory School of Engineering University of Guelph Guelph ONT Canada

In this paper, a fuzzy neural dynamics based tracking controller for nonholonomic wheeled mobile robots is proposed. The nonholonomic kinematic constraints are considered in the development of the controller. The proposed model is suitable for both continuous and discrete paths. Fuzzy rules are formulated to deal with the discontinuity in path directions. This model is capable of generating smooth velocity commands to drive the robot to track the desired paths. In the situation with large initial errors, the proposed model can automatically generate a smooth curve to reach the desired robot path from an arbitrary initial configuration without any explicit algorithms for the connection curve. At sharp turns, this model can automatically round off the sharp turns with a smooth curve. The effectiveness of the proposed tracking controller is demonstrated by simulation studies.

关键词： Fuzzy control Mobile robots robotics and automation Robot kinematics Wheels Intelligent robots Intelligent systems Control systems Navigation Councils

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Tracking control of a nonholonomic mobile robot by integrating feedback and neural dynamics techniques

Tracking control of a nonholonomic mobile robot by integrati...

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Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS 2003) (Cat. No.03CH37453)

作者： Haowen Yang S.X. Yang G.S. Mittal Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph ONT Canada

Mobile robots have been one of the challenging topics of control due to their nonholonomic property and restricted mobility. This paper presents the design of a novel tracking controller for a mobile robot by integrating the neural dynamics model into a conventional feedback controller. The proposed controller is capable of generating real-time smooth velocities, and driving the mobile robot to track desired trajectories. It resolves the speed jump problem existing in some previous tracking controllers. Lyapunov stability theory is used to prove the stability of the control system and the convergence of tracking errors to zero. The effectiveness of the proposed controller is demonstrated by simulation and comparison studies.

关键词： Mobile robots Neurofeedback Adaptive control Velocity control Trajectory Lyapunov method Stability Control systems Convergence Error correction

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Analysis and optimization of a non-time based motion controller for a nonholonomic mobile robot

Analysis and optimization of a non-time based motion control...

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IEEE International Symposium on Computational Intelligence in robotics and Automation (CIRA)

作者： Hao Li S.X. Yang F. Karray Advanced Robotics and Intelligent Systems (AFUS) Laboratory School of Engineering University of Guelph Canada Pattem Analysis and Machine Intelligence (PAMI) Laboratory Department of Systems Design Engineering University of Waterloo Canada

In this paper, a non-time based tracking controller of a nonholonomic mobile robot is first analyzed. Non-time based motion controllers have been successfully applied to many areas such as robot motion control, multi-robot coordination, force control, robotic teleoperation and manufacturing automation. However, by the traditional non-time based motion controller many suffer from oscillations in both the linear and angular velocities when there is a large initial tracking error. In this paper, a traditional non-time based tracking controller is optimized using a genetic algorithm, which is used to generate the model parameters that could guarantee the system stability and convergence of tracking error. Simulations using a nonholonomic mobile robot model with a four degree of freedom are conducted to investigate the performance of the proposed controller. The results using the proposed model is compared to those of the conventional model. Generally the proposed model performs better than the conventional model because the genetic algorithm can provide better parameters to minimize tracking error and the oscillation.

关键词： Motion analysis Motion control Mobile robots Automatic control Force control Error correction Genetic algorithms Robot motion Robot control Robot kinematics

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Influence of inclining angle of a slope to optimal locomotion curves of a snake-like robot

Influence of inclining angle of a slope to optimal locomotio...

引用

IEEE International Conference on robotics, Intelligent systems and Signal Processing

作者： Shugen Ma N. Tadokoro K. Inoue Bin Li Robotics Laboratory Shenyang Institute of Automation Shenyang China Department of Systems Engineering Ibaraki University Hitachi Japan

ISBN: (纸本)078037925X

Snakes perform many kinds of movement adapted to environments. Utilizing the snake as a model, we have developed a 2-dimensional snake-like robot that emulates a snakes' function. To make our robot move optimally while adapting to the slope environment, in this study we discussed the influence of the inclining angle of the slope to the creeping locomotion of the robot and derived its optimal creeping locomotion curves that adapted to the given slopes.

关键词： Robots robotics and automation Shape systems engineering and theory Content addressable storage Ice Motion analysis Computational modeling Analytical models

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Intelligent autonomy for remote characterization of hazardous environments

Intelligent autonomy for remote characterization of hazardou...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： D.J. Bruemmer M.O. Anderson J.L. Marble D.D. Dudenhoeffer D.A. Few M.D. Mckay Human Factors Robotics and Remote Systems Group Idaho National Engineering and Environmental Laboratory Idaho Falls ID USA

Remote characterization of high radiation environments is a pressing application area where robots have the potential to provide benefits in terms of time, cost, safety and quality of data. However, the ability to design robots that can be used effectively has proven to be no easy task. In 2001, the Idaho National engineering and Environmental laboratory (INEEL) successfully deployed a teleoperated robotic system coupled with a Gamma Locating and Isotopic Identification Device (RGL&IID) to characterize an area that had been closed to human entry for many years. This paper examines the limitations to the control strategy used and discusses how current efforts at the INEEL are developing intelligent controls that can actively mediate between the human and the robotic elements of the system. The resulting, mixed-initiative control architecture allows the user to shift the level of robot initiative throughout the task as needed. This system offers the opportunity for the human and robot to become a team where each can support the capabilities and limitations of the other.

关键词： Human robot interaction Intelligent robots Costs Instruments Robot sensing systems Human factors Pressing Safety Intelligent control Chemical elements

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Ground condition sensing of a snake-like robot

Ground condition sensing of a snake-like robot

引用

IEEE International Conference on robotics, Intelligent systems and Signal Processing

作者： Yang Lu Shugen Ma Bin Li Li Chen Robotics Laboratory Shenyang Institute of Automation Chinese Academy of Sciences China Department of Systems Engineering Ibaraki University Japan

ISBN: (纸本)078037925X

Snake-like robot has its unique locomotion mode and can change its locomotion form while the ground condition changed, to achieve the best velocity and efficiency. We first analyze the snake-like robot's locomotion on different terrains simply, then point out the significance to sense the ground status that is the base of choosing different locomotion form on different ground. Last we use force sensors to distinguish the different ground status.

关键词： Robot sensing systems Propulsion Friction Mobile robots Orbital robotics Prototypes Legged locomotion Kinematics Wheels Crawlers

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Real world implementation of fuzzy anti-swing control for behavior-based intelligent crane system

Real world implementation of fuzzy anti-swing control for be...

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IEEE International Workshop on Intelligent Robots and systems (IROS)

作者： Jiaming Wang Hao Li F. Karray O. Basir PAMIR Pattem Analysis Machine Intelligence and Robotics Laboratory Systems Design Engineering University of Waterloo Waterloo ONT Canada

There exist several industrial applications for large crane systems. Most of them experience serious problems with load swing. This paper presents a fuzzy based control scheme to minimize load swing for crane systems while maintaining continuous payload transportation. The control system of the crane is built using behavior-based approaches. In the control system developed, each module generates behaviors, and improvement in the performance of the system proceeds by adding new modules to the system. In order to develop the anti-swing module, fuzzy logic controller is applied using information extracted from potentiometers. The fuzzy controller provides a mechanism for dealing with imprecise sensor data. The anti-swing behaviors are successfully implemented by formulating a set of fuzzy rules. The performance of the developed system is illustrated by both simulations and experiments. The simulation and experimental results of the system show that the system remains stable under several operating situations.

关键词： Fuzzy control Fuzzy systems Control systems Intelligent systems Intelligent control Cranes Electrical equipment industry Payloads Transportation Fuzzy logic

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