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Related Concept Videos

Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
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Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
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Virtual Work for a System of Connected Rigid Bodies01:06

Virtual Work for a System of Connected Rigid Bodies

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One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

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Planar Rigid-Body Motion01:22

Planar Rigid-Body Motion

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Relative Motion Analysis using Rotating Axes-Problem Solving

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Related Experiment Video

Updated: Jul 10, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Spatial multi-vector and multi-rigid-body obstacle avoidance planning for multi-robot coordinated suspension system.

Xiangtang Zhao1, Zhigang Zhao1, Cheng Su1

  • 1School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China.

ISA Transactions
|July 15, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new multi-robot system for obstacle avoidance, improving efficiency and safety in complex industrial tasks. The proposed method significantly reduces trajectory length and enhances computational speed while preventing collisions.

Keywords:
Hierarchical-search and step-optimizationMulti-robot systemMulti-strategy geyser-inspired algorithmObstacle avoidance planningTelescopic pyramidal configuration

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Last Updated: Jul 10, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

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Published on: October 1, 2019

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

Area of Science:

  • Robotics
  • Control Systems
  • Artificial Intelligence

Background:

  • Multi-robot coordinated suspension systems (MCSS) face significant challenges including strong coupling in dynamics, high-dimensional state spaces leading to computational complexity, and limited obstacle avoidance strategies for multi-rigid-body systems.
  • Existing methods struggle with efficient decoupling and real-time planning in dynamic, non-convex environments, hindering the application of MCSS in industrial settings.

Purpose of the Study:

  • To develop an effective obstacle avoidance planning method for multi-robot coordinated suspension systems (MCSS).
  • To address challenges of decoupling, computational complexity, and collision prevention in multi-rigid-body systems.
  • To enhance the efficiency and scalability of MCSS for industrial applications like lifting tasks.

Main Methods:

  • Proposed a telescopic pyramidal configuration (TPC) and a multi-strategy geyser-inspired algorithm (MGEA) within a hierarchical-search and step-optimization (HSSO) framework.
  • MGEA incorporates chaotic mapping initialization, Lévy flights, differential evolution, and stability constraints to improve global search capabilities.
  • Hierarchical cooperative planning was implemented to prevent cable entanglement and decouple multi-robot motion.

Main Results:

  • MGEA demonstrated superior performance compared to benchmark algorithms, achieving a 16.35% reduction in trajectory length and an 18.60% improvement in minimum fitness.
  • A 13.74% increase in computational speed was observed, indicating enhanced efficiency.
  • The system maintained zero collisions in cluttered 3D environments, validating its effectiveness in obstacle avoidance.

Conclusions:

  • The proposed TPC and MGEA provide an efficient and scalable solution for multi-robot coordinated suspension systems, particularly for industrial lifting tasks.
  • The HSSO framework successfully enables multi-vector and multi-rigid-body obstacle avoidance planning.
  • This research lays a theoretical foundation for real-time planning in dynamic non-convex environments, advancing the field of multi-robot systems.