ABSTRACT

A main objective of the Mars 2020 rover mission (Perseverance) is to collect and preserve samples of rock and soil from the Martian surface. To accomplish this task, the Perseverance Rover carries a Sampling and Caching Subsystem outfitted with Coring Drill mounted on a 5 degree-of-freedom (DoF) robotic arm. Safe operation of the Robotic Arm and its tools relies on force feedback, provided by a custom Force-Torque Sensor (FTS) which is positioned to sense end-effector external loads. This work describes the methods and algorithms used in the calibration of the Robotic Arm FTS to achieve the required force-feedback accuracy over all expected Mars and Earth operating environments. Specifically, we use a two-stage, least-squares optimization process to generate an FTS calibration model that is fit to both sensor-level and system-level calibration data, while implicitly compensating for offset, scaling, and thermal errors observed during sensor integration into the robotic arm system. This technique is compatible with remote FTS re-calibration while the rover is operating on Mars. Data collection strategies, standalone versus system-integrated sensor findings, results of validation exercises in Earth-ambient and Mars-like environments, and initial FTS commissioning data on Mars are all included.

摘要

火星 2020 漫游车任务（毅力）的一个主要目标是从火星表面收集和保存岩石和土壤样本。为了完成这项任务，毅力漫游者携带了一个采样和缓存子系统，该子系统配备了安装在 5 自由度 (DoF) 机械臂上的取心钻。机械臂及其工具的安全操作依赖于力反馈，力反馈由定制的力-扭矩传感器 (FTS) 提供，该传感器被定位为感测末端执行器的外部负载。这项工作描述了用于校准机械臂 FTS 的方法和算法，以在所有预期的火星和地球操作环境中实现所需的力反馈精度。具体来说，我们使用两阶段，最小二乘优化过程以生成适合传感器级和系统级校准数据的 FTS 校准模型，同时隐式补偿在传感器集成到机械臂系统期间观察到的偏移、缩放和热误差。当火星车在火星上运行时，该技术与远程 FTS 重新校准兼容。数据收集策略、独立与系统集成传感器的发现、地球环境和类火星环境中的验证练习结果以及火星上的初始 FTS 调试数据都包括在内。