Auto-Platoon : Freight by example

TL;DR

This paper presents a bio-inspired leader-follower system for autonomous freight transportation, utilizing software latching for real-time coordination, deep learning for environment handling, and layered architecture for robust multi-robot navigation.

Contribution

It introduces a novel software latching mechanism and layered architecture for improved coordination and obstacle avoidance in multi-robot freight systems.

Findings

Effective real-time leader-follower coordination demonstrated

Successful obstacle avoidance in dynamic environments

Layered architecture enhances system robustness

Abstract

The work introduces a bio-inspired leader-follower system based on an innovative mechanism proposed as software latching that aims to improve collaboration and coordination between a leader agent and the associated autonomous followers. The system utilizes software latching to establish real-time communication and synchronization between the leader and followers. A layered architecture is proposed, encompassing perception, decision-making, and control modules. Challenges such as uncertainty, dynamic environments, and communication latency are addressed using Deep learning and real-time data processing pipelines. The follower robot is equipped with sensors and communication modules that enable it to track and trace the agent of interest or avoid obstacles. The followers track the leader and dynamically avoid obstacles while maintaining a safe distance from it. The experimental results demonstrate the proposed system's effectiveness, making it a promising solution for achieving success in tasks that demand multi-robot systems capable of navigating complex dynamic environments.