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Related Concept Videos

State Space Representation01:27

State Space Representation

The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
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Related Experiment Video

Updated: Jun 11, 2026

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

Motion planning and coordination for robot systems based on representation space.

Jianbo Su1, Wenlong Xie

  • 1Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China. jbsu@sjtu.edu.cn

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|July 14, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a novel motion planning and coordination strategy for robot systems using a representation space (RS). It enables robots to plan tasks, adapt to constraints, and optimize execution for improved robotic system design and operation.

Related Experiment Videos

Last Updated: Jun 11, 2026

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

Area of Science:

  • Robotics
  • Artificial Intelligence
  • Control Systems

Background:

  • Robot systems require effective strategies for motion planning and coordination.
  • Existing methods may struggle with complex constraints and multi-robot systems.
  • Defining a robot's capabilities and task feasibility is crucial for autonomous operation.

Purpose of the Study:

  • To propose a general motion planning and coordination strategy for diverse robot systems.
  • To develop a framework for analyzing task realizability and system capabilities.
  • To enable adaptive task reassignment and system reconfiguration for optimal performance.

Main Methods:

  • Constructing a representation space (RS) to model robot system attributes and their distributions.
  • Defining the reachable area within the RS to represent system capabilities under constraints.
  • Transforming task realization into finding trajectories within the RS for attribute transitions.

Main Results:

  • Demonstrated the ability to determine task realizability based on system configurations and constraints.
  • Showcased the optimization of task execution strategies when tasks are realizable.
  • Validated the proposed method through experiments in path planning, formation movement, and mobile manipulator coordination.

Conclusions:

  • The proposed representation space strategy offers a unified approach to robot motion planning and coordination.
  • The method is effective in designing, planning, and coordinating robotic tasks across various systems.
  • Experimental results confirm the validity and generalizability of the approach for complex robotic applications.