一种可切换形态的力感知末端执行器，兼具行走与抓取功能。
Mechanisms and Computational Design of Multi-Modal End-Effector with Force Sensing using Gated Networks
- 通过门控网络融合霍尔传感器实现八轴力感知，支持接触与触觉测量。
- 设计框架考虑噪声干扰，生成理想逆模型，实测验证了力感知精度。
- 适合需要多功能末端执行器的仿生机器人研究者参考。
在多足机器人中，末端执行器需同时承担行走与抓取双重功能，带来设计挑战。本文提出一种多模态末端执行器MAGPIE，可在平面足与线状足形态间切换，并具备抓取能力。MAGPIE采用自研机制集成8轴力传感，结合霍尔效应传感器，实现接触力与触觉力的同步测量。我们构建了计算设计框架，考虑噪声与干扰因素，优化灵敏度与量程，生成理想的逆模型。硬件实现经实验验证，证实其作为足部使用的能力，且力感测机制、理想模型及基于门控网络的模型性能均得到验证。
原文摘要 · Abstract (English)
In limbed robotics, end-effectors must serve dual functions, such as both feet for locomotion and grippers for grasping, which presents design challenges. This paper introduces a multi-modal end-effector capable of transitioning between flat and line foot configurations while providing grasping capabilities. MAGPIE integrates 8-axis force sensing using proposed mechanisms with hall effect sensors, enabling both contact and tactile force measurements. We present a computational design framework for our sensing mechanism that accounts for noise and interference, allowing for desired sensitivity and force ranges and generating ideal inverse models. The hardware implementation of MAGPIE is validated through experiments, demonstrating its capability as a foot and verifying the performance of the sensing mechanisms, ideal models, and gated network-based models.
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