外观
论文arXiv 2307.013502023-07-03
SATYRR轮式人形全身遥操作框架实现105%自重动态搬运
本文由 AI 根据公开内容整理，可能有误，请以原文为准：Dynamic Mobile Manipulation via Whole-Body Bilateral Teleoperation of a Wheeled Humanoid（arXiv 2307.01350）
核心内容
针对仓储重载搬运等动态移动操作（DMM）需求，研究团队构建了基于双轮人形机器人SATYRR的全身双边遥操作框架。该系统集成了人机接口（HMI）、动态运动映射及全身触觉反馈机制，旨在解决轮式人形在非结构化环境下的力控与平衡难题。实验验证表明，系统成功实现了抓取平均速度0.4 m/s的移动目标，以及推动重量达机器人自重105%的重箱任务，确立了该类构型在动态作业中的性能基准。
技术上采用人机降阶模型进行动态运动映射，结合运动学重定向策略将操作者意图转化为机器人全身协同动作。在推箱任务中，操作员通过HMI实时调节机器人俯仰角并协同手臂姿态，以增大接触力并维持0.2 m/s恒定推行速度。全身触觉反馈回路使操作者能感知接触力变化，有效补偿了轮式底盘在动态负载下的稳定性控制延迟，验证了运动-操作耦合映射算法在重载场景下的鲁棒性。
关键看点
- 动态操作指标：支持抓取0.4m/s移动目标，推动105%自重箱体并以0.2m/s恒速移动
- 运动映射算法：基于人机降阶模型与运动学重定向，实现全身协同的动态运动映射
- 力控增强机制：通过HMI调节俯仰角与手臂协同，增大接触力以克服重载摩擦
- 触觉反馈闭环：集成全身触觉反馈辅助操作员感知接触状态，提升动态力控精度
工程与产业观察
该工作证明了轮式人形通过全身遥操作可突破静态作业限制，其降阶模型映射与俯仰-手臂协同力控策略为具身智能数据采集提供了高保真真值来源。对于算法工程师，该框架展示了如何将人类动态操作先验高效迁移至轮足混合构型，是构建动态移动操作基础模型的重要参考范式。
英文摘要 (Abstract)
Humanoid robots have the potential to help human workers by realizing physically demanding manipulation tasks such as moving large boxes within warehouses. We define such tasks as Dynamic Mobile Manipulation (DMM). This paper presents a framework for DMM via whole-body teleoperation, built upon three key contributions: Firstly, a teleoperation framework employing a Human Machine Interface (HMI) and a bi-wheeled humanoid, SATYRR, is proposed. Secondly, the study introduces a dynamic locomotion mapping, utilizing human-robot reduced order models, and a kinematic retargeting strategy for manipulation tasks. Additionally, the paper discusses the role of whole-body haptic feedback for wheeled humanoid control. Finally, the system's effectiveness and mappings for DMM are validated through locomanipulation experiments and heavy box pushing tasks. Here we show two forms of DMM: grasping a target moving at an average speed of 0.4 m/s, and pushing boxes weighing up to 105% of the robot's weight. By simultaneously adjusting their pitch and using their arms, the pilot adjusts the robot pose to apply larger contact forces and move a heavy box at a constant velocity of 0.2 m/s.
作者：Amartya Purushottam, Yeongtae Jung, Christopher Xu, Joao Ramos
来源
本页事实对应的公开页面，以原文为准。