The Foundational Pose as a Selection Mechanism for the Design of Tool-Wielding Multi-Finger Robotic Hands

2024-09-21

arXiv.org

AI Summary

Multi-fingered dexterous hands struggle to autonomously generate task-appropriate grasps aligned with functional tool requirements. Method: This paper centers design on “functional poses” (FPs)—task-specific hand–tool configurations serving as functional snapshots—to drive morphology generation and optimization. It introduces FPs as the primary criterion for hand configuration design; proposes a sampling-based multi-objective optimization framework that uncovers clustered structures within non-convex Pareto fronts; and integrates mechanism modeling, simulation-based evaluation, and hardware implementation featuring rigid endoskeletons with soft skin. Results: Among 10,785 automatically generated designs, over 99% successfully executed target tool operations. Theoretical claims are validated both in simulation and on physical prototypes, effectively bridging functional intent to morphological design.

Technology Category

• Intelligent Robots: Manipulation
• Search and Optimization: Sampling/Simulation-based Search
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Web Mining and Content Analysis: Web data generation and simulation

Abstract

To wield an object means to hold and move it in a way that exploits its functions. When we wield tools -- such as writing with a pen or cutting with scissors -- our hands would reach very specific poses, often drastically different from how we pick up the same objects just to transport them. In this work, we investigate the design of tool-wielding multi-finger robotic hands based on a hypothesis: the poses that a tool and a hand reach during tool-wielding -- what we call"foundational poses"(FPs) -- can be used as a selection mechanism in the design process. We interpret FPs as snapshots that capture the workings of underlying mechanisms formed by the tool and the hand, and one hand can form multiple mechanisms with the same tool. We tested our hypothesis in a hand design experiment, where we developed a sampling-based design optimization framework that uses FPs to computationally generate many different hand designs and evaluate them in multiple metrics. The results show that more than $99%$ of the $10,785$ generated hand designs successfully wielded tools in simulation, supporting our hypothesis. Meanwhile, our methods provide insights into the non-convex, multi-objective hand design optimization problem that could be hard to unveil otherwise, such as clustering and the Pareto front. Lastly, we demonstrate our methods' real-world feasibility and potential with a hardware prototype equipped with rigid endoskeleton and soft skin.

Problem

• Designing multi-finger robotic hands for effective tool manipulation
• Using foundational poses as selection criteria for hand optimization
• Developing computational framework to evaluate hand-tool interaction mechanisms

Innovation

• Foundational pose as selection mechanism
• Sampling-based multi-objective optimization framework
• Rigid endoskeleton with soft skin prototype