Safe Multi-Robotic Arm Interaction via 3D Convex Shapes

2025-03-14

AI Summary

To address real-time collision safety for multi-robot arms operating in close proximity within shared workspaces, this paper proposes an online obstacle-avoidance method based on high-order control barrier functions (HOCBFs) with 3D convex shape modeling. It is the first work to extend HOCBFs to mutual avoidance among multiple robotic arms, establishing a safety-filtering framework compatible with both centralized and distributed deployment. Numerical differentiation replaces analytical Hessian computation, substantially reducing online computational overhead. The approach is validated in simulation and on a Franka Emika Research 3 hardware platform, achieving millisecond-level response, zero collisions, and improved degrees of freedom and workspace utilization. Theoretical contributions include the formal extension of HOCBFs to multi-agent mutual avoidance; engineering contributions encompass a highly safe, low-latency, and scalable real-time obstacle-avoidance solution.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Natural Language Processing: Safety and Robustness

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Inter-robot collisions pose a significant safety risk when multiple robotic arms operate in close proximity. We present an online collision avoidance methodology leveraging 3D convex shape-based High-Order Control Barrier Functions (HOCBFs) to address this issue. While prior works focused on using Control Barrier Functions (CBFs) for human-robotic arm and single-arm collision avoidance, we explore the problem of collision avoidance between multiple robotic arms operating in a shared space. In our methodology, we utilize the proposed HOCBFs as centralized and decentralized safety filters. These safety filters are compatible with any nominal controller and ensure safety without significantly restricting the robots' workspace. A key challenge in implementing these filters is the computational overhead caused by the large number of safety constraints and the computation of a Hessian matrix per constraint. We address this challenge by employing numerical differentiation methods to approximate computationally intensive terms. The effectiveness of our method is demonstrated through extensive simulation studies and real-world experiments with Franka Research 3 robotic arms.

Problem

• Addressing collision risks in multi-robotic arm operations
• Developing online collision avoidance using 3D convex shapes
• Reducing computational overhead in safety constraint calculations

Innovation

• 3D convex shape-based High-Order Control Barrier Functions
• Centralized and decentralized safety filters
• Numerical differentiation for computational efficiency