Leader Follower Formation Control of Ground Vehicles Using Camshift Based Guidance

TL;DR

This paper presents a novel visual guidance control algorithm for ground vehicle formation using real-time image processing with Camshift, integrating vision and control subsystems for effective leader-follower coordination.

Contribution

It introduces the first use of Camshift-based vision algorithms in leader-follower formation control for ground vehicles, combining simple, effective computer vision techniques with sliding mode control.

Findings

Effective real-time leader detection and tracking

Successful simulation and practical experiments

Improved formation stability using the proposed method

Abstract

Autonomous ground vehicles have been designed for the purpose of that relies on ranging and bearing information received from forward looking camera on the Formation control . A visual guidance control algorithm is designed where real time image processing is used to provide feedback signals. The vision subsystem and control subsystem work in parallel to accomplish formation control. A proportional navigation and line of sight guidance laws are used to estimate the range and bearing information from the leader vehicle using the vision subsystem. The algorithms for vision detection and localization used here are similar to approaches for many computer vision tasks such as face tracking and detection that are based color-and texture based features, and non-parametric Continuously Adaptive Mean-shift algorithms to keep track of the leader. This is being proposed for the first time in the leader follower framework. The algorithms are simple but effective for real time and provide an alternate approach to traditional based approaches like the Viola Jones algorithm. Further to stabilize the follower to the leader trajectory, the sliding mode controller is used to dynamically track the leader. The performance of the results is demonstrated in simulation and in practical experiments.