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International Conference on Information and Automation (ICIA)

作者： X. Xue S.X. Yang M.Q.-H. Meng Advanced Robotics and Intelligent Systems Laboratory University of Guelph Guelph ONT Canada Department of Electronic Engineering Chinese University of Hong Kong New Territories Hong Kong China

Teleoperations are desirable when robots are not able to deal with a certain task autonomously. On the other hand, using mobile robots equipped with sensors provide a way to acquire the information in a hazardous environment. With the mature and universal Internet technology, Internet-based teleoperation of robotic system has created new opportunities in resources sharing, long-distance learning, and remote experimentation. This paper introduces a network-enabled teleoperation system with a wireless mobile robot, which involves TCP/IP, socket and le cache technology. The operator can receive the dynamic sensor information and teleoperate the mobile robot via the Internet through a control panel. Experiments on wall-following in an indoor environment demonstrated the effectiveness of this teleoperation system.

关键词： Remote sensing Mobile robots Internet Robot sensing systems Control systems intelligent robots Humans Hardware Telerobotics Vehicle dynamics

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A MEMS micro force sensor for drosophila flight characterization

A MEMS micro force sensor for drosophila flight characteriza...

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IEEE International Conference on robotics and Biomimetics

作者： Yun Sun C.F. Graetzel S.N. Fry B.J. Nelson Advanced Micro and Nanosystems Laboratory University of Toronto Canada Institute of Robotics and Intelligent Systems Swiss Federal Institute of Technology Switzerland Institute of Neuroinformatics University of Zürich Switzerland

This paper reports a MEMS micro force sensor with a novel configuration of differential tri-plate comb drives suitable for bulk micromachining. A high-yield fabrication process using DRIE on SOI wafers is utilized to construct the high aspect ratio devices. The sensor has a high sensitivity, good linearity, and a large bandwidth, which are required for characterizing flight behavior of fruit flies (Drosophila). The technique allows for the instantaneous measurements of flight forces, which result from a combination of aerodynamic and inertial forces generated by the wings. The potential impact of this research extends beyond gathering flight data on Drosophila melanogaster by demonstrating how MEMS technology can be used to provide valuable tools for biomechanical investigations

关键词： Micromechanical devices Force sensors Force measurement Insects Biological system modeling intelligent robots intelligent systems Turning Organisms Biomechanics

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Real-time Map Building and Area Coverage in Unknown Environments

Real-time Map Building and Area Coverage in Unknown Environm...

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IEEE International Conference on robotics and Automation (ICRA)

作者： C. Luo S.X. Yang M.Q.-H. Meng Advanced Robotics and Intelligent Systems Laboratory University of Guelph Guelph ONT Canada Department of Electronic Engineering Chinese University of Hong Kong New Territories Hong Kong China

Area-covering operation is a special kind of path planning, which requires the robot path to cover every part of the workspace. In this paper, a neural dynamics based algorithm is proposed for real-time map building and area-covering operations. A local map composed of squared cells is built through the proposed neural dynamics during area-covering operations with limited sensory information in unknown environments. The robot is able to dynamically build an accurate map of its immediate limited surroundings for its navigation. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation derived from Hodgkin and Huxley’s membrane equation. The robot can only sense a limited measurable range and the obtained sensory information are used for its navigation. The feasibility of the proposed algorithm is validated by simulation studies on cases under unknown environments.

关键词： Robot sensing systems Vehicle dynamics robotics and automation Path planning Navigation Neural networks Cleaning Fuzzy logic intelligent robots Equations

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Humanoid motion planning for dynamic tasks

Humanoid motion planning for dynamic tasks

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IEEE-RAS International Conference on Humanoid Robots

作者： E. Yoshida I. Belousov C. Esteves J.-P. Laumond Intelligent Systems Research Institute National Institute of Advanced Industrial Science and Technology (AIST) AIST/ISRI-CNRS/STIC Joint French-Japanese Robotics Laboratory Tsukuba Ibaraki Japan AIST/ISRI-CNRS/STIC Joint French-Japanese Robotics Laboratory (JRL) LAAS CNRS Toulouse France

This paper addresses an integrated humanoid motion planning scheme including both advanced algorithmic motion planning technique and dynamic pattern generator so that the humanoid robot achieve tasks including dynamic motions. A two-stage approach is proposed for this goal. First, geometric and kinematic motion planner first computes collision-free paths for the humanoid robot. Then the dynamic pattern generator provides dynamically feasible humanoid motion including both locomotion and task execution such as object transportation or manipulation. If the generated dynamic motion causes collision due to dynamic movements, the planner go back to the planning stage to remove the collision by path reshaping. This iterative planning scheme enables robust planning against variation of task dynamics. Simulation results are provided to validate the proposed planning method

关键词： Motion planning Humanoid robots Kinematics Legged locomotion Transportation Robustness intelligent robots Manipulator dynamics Motion control Humans

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Three Characterizations of 3D Reconstruction Uncertainty with Bounded Error

Three Characterizations of 3D Reconstruction Uncertainty wit...

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IEEE International Conference on robotics and Automation (ICRA)

作者： B. Telle O. Stasse K. Yokoi T. Ueshiba F. Tomita AIST/ISRI 3D Vision Group Intelligent Systems Research Institute (ISRI) National Institute for Advanced Industrial Science and Technology Tsukuba Ibaraki Japan AIST/IS-CNRS/STIC Joint Japanese-French Robotics Laboratory (JRL) Intelligent Systems Research Institute (ISRI) National Institute for Advanced Industrial Science and Technology Tsukuba Ibaraki Japan

Considering a stereoscopic visual system, this paper deals with the error involved by a 3D reconstruction process. If image pixels are seen as surfaces instead of points, interval analysis provides bounding boxes in which the reconstructed 3D point lies with certainty. This paper presents a method which refine this bounding box and gives a tighter approximation of the error. Using bisection, and a reprojection test in the image planes, the space in which the 3D reconstructed point may be located is given as an octree. This is achieved through the resolution of a set inversion problem using the SIVIA algorithm. For a lighter manipulation of the result, an englobing ellipsoid is deduced from this approximation. Finally the three models are tested on a recognition process for a humanoid robot.

关键词： Uncertainty Image reconstruction Cameras Ellipsoids Robot vision systems intelligent robots Testing Gaussian distribution Shape Service robots

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GA BASED SENSOR PLACEMENT AND CONTROL DESIGN FOR REACTIVE NAVIGATION OF MOBILE ROBOTS

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International Journal of Information Acquisition 2005年第2期2卷 77-91页

作者： XIAOCHUAN WANG SIMON X. YANG MAX Q.-H. MENG Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph ON Canada N1G 2W1 Canada Department of Electronic Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong China

In this paper, a novel genetic algorithm based approach is proposed for optimal sensor placement and controller design of a mobile robot to facilitate its reactive navigation and obstacle avoidance in unknown environments. The mobile robots considered in this paper have flexible sensor and control structure. A genetic algorithm is developed to evolve the parameters of optimal sensor placement and controller design simultaneously. The effectiveness of the proposed GA based co-evolution approach to robot sensor placement and control design is demonstrated by simulation studies.

关键词： Sensor placement control design mobile robots obstacle avoidance genetic algorithm co-evolution

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A knowledge based genetic algorithm for path planning of a mobile robot

A knowledge based genetic algorithm for path planning of a m...

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IEEE International Conference on robotics and Automation (ICRA)

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

In this paper, a knowledge based genetic algorithm (GA) for path planning of a mobile robot is proposed, which uses problem-specific genetic algorithms for robot path planning instead of the standard GAs. The proposed knowledge based genetic algorithm incorporates the domain knowledge into its specialized operators, where some also combine a local search technique. The proposed genetic algorithm also features a unique and simple path representation and a simple but effective evaluation method. The knowledge based genetic algorithm is capable of finding an optimal or near-optimal robot path in both complex static and dynamic environments. The effectiveness and efficiency of the proposed genetic algorithm is demonstrated by simulation studies. The irreplaceable role of the specialized genetic operators in the proposed GA for solving robot path planning problem is demonstrated by a comparison study.

关键词： Genetic algorithms Path planning Mobile robots Biological cells intelligent robots Encoding intelligent systems Genetic engineering Knowledge engineering Neural networks

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Using a non-prior training active feature model

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 3333卷 69-78页

作者： Kim, Sangjin Kang, Jinyoung Shin, Jeongho Lee, Seongwon Paik, Joonki Kang, Sangkyu Abidi, Besma Abidi, Mongi Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University 221 Huksuk-Dong Tongjak-Ku Seoul 156-756 Korea Republic of Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville TN 27996-2100 United States

This paper presents a feature point tracking algorithm using optical flow under the non-prior training active feature model (NPT-AFM) framework. The proposed algorithm mainly focuses on analysis of deformable objects, and provides real-time, robust tracking. The proposed object tracking procedure can be divided into two steps: (i) optical flow-based tracking of feature points and (ii) NPT-AFM for robust tracking. In order to handle occlusion problems in object tracking, feature points inside an object are estimated instead of its shape boundary of the conventional active contour model (ACM) or active shape model (ASM), and are updated as an element of the training set for the AFM. The proposed NPT-AFM framework enables the tracking of occluded objects in complicated background. Experimental results show that the proposed NPT-AFM-based algorithm can track deformable objects in real-time. © Springer-Verlag 2004.

关键词： Optical flows

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Path planning of multi-robot systems with cooperation

Path planning of multi-robot systems with cooperation

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

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

In this paper, a novel gated dipole based approach is proposed for path planning of a multi-robot system, where the cooperative control strategy is based on the multi-agent systems. The system stability is guaranteed by a Lyapunov stability theory. The proposed approach is capable of generating collision-free paths for a multi-robot system in various situations, such as robots with different speed, with limited measurable sensor information, and in completely unknown environments. The effectiveness and efficiency of the proposed approach is demonstrated by simulation studies.

关键词： Path planning Multirobot systems Robot kinematics Orbital robotics Mobile robots intelligent robots Robot sensing systems Stability State-space methods Genetic algorithms

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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...

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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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