Force-Safe Environment Maps and Real-Time Detection for Soft Robot Manipulators

2025-11-07

AI Summary

Traditional obstacle avoidance methods for soft robotic manipulators neglect contact force safety constraints, posing risks in delicate and sensitive environments. To address this, this paper proposes a real-time obstacle avoidance framework based on force-safety mapping. The core contribution is the first rigorous mapping of task-space force-threshold constraints into configuration space via forward kinematics, yielding a provably force-safe configuration criterion and enabling construction of a force-safe environmental map. The method supports online force-safety verification and motion planning without requiring complex dynamic modeling or high-fidelity force sensing. Evaluated on a pneumatic two-segment soft arm in both simulation and physical experiments, the approach significantly improves force safety and operational robustness during interactions with deformable obstacles, demonstrating effectiveness, reliability, and real-time performance.

Technology Category

• Intelligent Robots: Manipulation
• Natural Language Processing: Safety and Robustness
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Security and Privacy: Large-scale security measurements

Abstract

Soft robot manipulators have the potential for deployment in delicate environments to perform complex manipulation tasks. However, existing obstacle detection and avoidance methods do not consider limits on the forces that manipulators may exert upon contact with delicate obstacles. This work introduces a framework that maps force safety criteria from task space (i.e. positions along the robot's body) to configuration space (i.e. the robot's joint angles) and enables real-time force safety detection. We incorporate limits on allowable environmental contact forces for given task-space obstacles, and map them into configuration space (C-space) through the manipulator's forward kinematics. This formulation ensures that configurations classified as safe are provably below the maximum force thresholds, thereby allowing us to determine force-safe configurations of the soft robot manipulator in real-time. We validate our approach in simulation and hardware experiments on a two-segment pneumatic soft robot manipulator. Results demonstrate that the proposed method accurately detects force safety during interactions with deformable obstacles, thereby laying the foundation for real-time safe planning of soft manipulators in delicate, cluttered environments.

Problem

• Mapping force safety criteria from task space to configuration space
• Enabling real-time detection of force-safe configurations for soft robots
• Ensuring contact forces remain below thresholds with delicate obstacles

Innovation

• Mapping force safety criteria from task to configuration space
• Real-time detection of force-safe configurations for soft robots
• Incorporating contact force limits into forward kinematics mapping