Group Robot Formation Control Using Virtual Temperature Forces
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Solution Overview
Problem
Existing multi-robot systems face challenges in controlling collective movement, particularly when centralized control is compromised, and struggle with balancing autonomous distributed control and strong robot connections.
Innovation Solution
A multi-robot system utilizing a thermodynamics mathematical model to calculate virtual attractive-repulsive forces based on robot and object positions, allowing for autonomous movement and phase transitions to manage group formation and obstacle avoidance with low calculation load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If centralized control is used to manage group robot formation and movement, then control precision and formation stability are improved, but system reliability deteriorates because the system becomes vulnerable to centralized control section breakdown
Solution Approach 1:
The control system is segmented into multiple independent control sections distributed across different robots. Each control section can independently execute control algorithms and make decisions, eliminating the single point of failure in centralized control. The group robot control is divided into formation control functions and movement control functions that can be distributed to different robots or control sections.
Solution Approach 2:
Control parameters and formation configurations are pre-calculated and stored in each control section before operation. When operation begins, each control section directly executes pre-prepared control commands without requiring real-time computation or communication with a central controller, enabling fast response and maintaining control precision while ensuring reliability through distributed architecture.
2Reliability
If autonomous distributed control is used to improve system reliability and reduce calculation load, then robot connection strength and formation stability deteriorate
Solution Approach 1:
Each robot is equipped with sensors that continuously detect the positions and states of other robots in the group. This real-time feedback information is fed into the control algorithm, which dynamically adjusts each robot's movement to maintain formation stability. The feedback mechanism enables autonomous distributed control while preserving formation coherence through local interactions.
Solution Approach 2:
The control algorithm dynamically changes parameters such as attraction and repulsion forces between robots based on real-time formation state and environmental conditions. By adjusting these parameters, the system maintains stable formation under normal conditions while adapting to disturbances, achieving both autonomous operation and formation stability through parameter optimization.
3Stability of the object's composition
If complex control algorithms are used to maintain strong connections among robots, then formation stability is improved, but calculation load increases
Solution Approach 1:
Each robot independently executes the control algorithm using its own processor and sensors, without requiring complex inter-robot communication or centralized computation. The control logic is designed to be computationally efficient, using simple distance-based attraction and repulsion calculations that each robot can perform autonomously with minimal energy consumption while maintaining formation stability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables a combination of autonomous distributed and centralized control, allowing the system to adapt formation and navigate obstacles efficiently while minimizing computational requirements.
Implementation Method 1
calculates a virtual robot temperature, which changed by a virtual heat transfer, from the virtual object temperature, the virtual initial robot temperature, and a distance between the robot and the object
Implementation Method 2
calculates virtual attractive-repulsive force from a distance between the robots to keep the distance between the robots and virtual repulsive force acting between the object and the robot from a virtual robot temperature by using a thermodynamics mathematical model
Data Source
AI summary
A group robot and a method for controlling a collective movement of a group robot that realize a combination of autonomous distributed control and centralized control according to the environment are provided. A group robot is formed of at least two robots that have powers and autonomously move obtains mutual position information among the robots and with respect to an object that exists in a movable area of the robots, presets a virtual object temperature for the object and a virtual initial robot temperature that is lower than the virtual object temperature for the robot, calculates a virtual robot temperature, which changed by a virtual heat transfer, from the virtual object temperature, the virtual initial robot temperature, and a distance between the robot and the object, calculates virtual attractive-repulsive force from a distance between the robots to keep the distance between the robots and virtual repulsive force acting between the object and the robot from a virtual robot temperature by using a thermodynamics mathematical model, and controls a movement direction and velocity of the robot by using a sum of the virtual attractive-repulsive force and the virtual repulsive force.