Leader-Follower Vehicle Control for Noise-Robust Source Seeking
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Solution Overview
Problem
Existing multi-robot formation control systems are vulnerable to noise and obstacles in communication channels, leading to instability and potential collisions, as they rely on wireless communication for coordination.
Innovation Solution
A robust vehicle control system with sensors for measuring source intensity and obstacle distance, using a leader-follower algorithm to autonomously navigate towards a source while avoiding obstacles, employing a hybrid-extreme-seeker algorithm and formation control algorithm for distributed communication and obstacle avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wireless communication is used for multi-robot formation control, then coordination between robots is achieved, but the system becomes vulnerable to noise and hacking attacks causing instability and collisions
Solution Approach 1:
The patent applies robust control theory to convert the harmful effect of noise into a beneficial property by designing controllers that are inherently robust to communication uncertainties. The control algorithm treats noise and uncertainties as bounded disturbances and designs the formation control to maintain stability within these bounds, effectively converting the harmful noise into a manageable parameter rather than a system failure cause
Solution Approach 2:
The patent introduces a robust control algorithm as an intermediary layer between the wireless communication channel and the formation control execution. This intermediary processes the noisy communication data and transforms it into reliable control commands, filtering out the harmful effects of noise and hacking attempts while preserving the essential coordination information
2Ease of operation
If existing formation control algorithms are used, then multi-robot coordination is achieved, but slight additive noise on communication channels causes the formation to get stuck or hit obstacles
Solution Approach 1:
The patent implements beforehand cushioning by designing the control algorithm with built-in robustness margins that anticipate and cushion against the effects of noise. The controller is designed with uncertainty bounds that preemptively account for communication noise, preventing the formation from getting stuck or hitting obstacles even when noise is present, rather than reacting after problems occur
3Reliability
If robust control algorithm is designed to be noise-resistant, then formation stability is improved, but communication and coordination complexity increases
Solution Approach 1:
The patent achieves robustness through parameter changes by modifying the control law to include uncertainty bounds and robustness margins as additional parameters. Rather than fundamentally changing the control architecture, the approach incorporates noise resistance through parameter adjustments in the control algorithm, maintaining relative simplicity while improving reliability
Data Source
AI summary
A vehicle control system for driving a vehicle toward a source while avoiding an obstacle includes a first sensor to measure a first intensity of a source signal from the source, a second sensor to detect an obstacle and a second vehicle. The system includes an interface to receive data of a second intensity of the source signal measured by the second vehicle and transmit the data of the first and second intensities via a wireless channel, a memory to store the data of the first and second intensities, an autonomous program, a leader algorithm and a follower algorithm for autonomously driving the vehicle, a processor to select and perform one of the leader algorithm and the follower algorithm and generate control signals, and a machinery control circuit to drive a machinery of the vehicle according the control signals.