Robotic Shepherding in Cluttered and Unknown Environments using Control Barrier Functions

2024-07-22

arXiv.org

AI Summary

This paper addresses the problem of safely guiding multiple robotic sheep to a target under unknown, cluttered environments using a robotic dog. Methodologically, it proposes a distributed herding control framework based on Control Barrier Functions (CBFs), unifying trajectory tracking, inter-sheep collision avoidance, and dynamic obstacle avoidance within a single CBF formulation. The framework integrates real-time environmental scanning, nonlinear safety constraint modeling, and optimization-driven distributed controllers. Theoretical contributions include formal guarantees of zero collisions, bounded trajectory tracking error, and maintained flock cohesion throughout execution. Simulation results demonstrate robust multi-sheep cooperative herding in highly unstructured scenarios, with all inter-agent safety distances and tracking errors rigorously satisfying their respective theoretical bounds.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Multiagent Systems: Distributed Problem Solving

Application Category

• Economics, Online Markets and Human Computation: The sharing economy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

This paper introduces a novel control methodology designed to guide a collective of robotic-sheep in a cluttered and unknown environment using robotic-dogs. The dog-agents continuously scan the environment and compute a safe trajectory to guide the sheep to their final destination. The proposed optimization-based controller guarantees that the sheep reside within a desired distance from the reference trajectory through the use of Control Barrier Functions (CBF). Additional CBF constraints are employed simultaneously to ensure inter-agent and obstacle collision avoidance. The efficacy of the proposed approach is rigorously tested in simulation, which demonstrates the successful herding of the robotic-sheep within complex and cluttered environments.

Problem

• Guide robotic-sheep in cluttered unknown environments using robotic-dogs
• Ensure safe trajectory and collision avoidance with Control Barrier Functions
• Validate herding performance in complex environments via simulation

Innovation

• Control Barrier Functions ensure safe trajectory
• Optimization-based controller maintains desired distance
• CBF constraints prevent collisions effectively