RI: Small: Learning Biped Locomotion

RI：小：学习两足动物运动

• 批准号: 0917318
• 负责人: Stefan Schaal
• 金额: $ 45万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0917318&HistoricalAwards=false
• 关键词: RI; Small; Learning; Biped; Locomotion

In a not too distant future, assistive robots will become a natural part of the human society, in hospitals, schools, elder care facilities, inner city urban areas, and eventually homes. While wheeled robots, e.g., a humanoid torso on a mobile platform, can cover a range of tasks that assistive robots will be needed for, eventually, legged robots will be the most suitable, as legs increase the effective workspace of a robot and allow maneuvering more complex terrains like steps, curbs, and cluttered and rough terrains in general.This project investigates biped locomotion with a Sarcos humanoid robot. In contrast to most other projects in biped locomotion, it emphasizes walking over uneven and rough terrain, obstacle avoidance, recovery from unexpected perturbation, and learning methods for motor control, as these issues seem to be the most important for working in dynamic and partially unpredictable human environments. Another focus is on dexterous movement control, i.e., control with a maximal amount of compliance and minimal negative feedback gains, using advanced operational space controllers with internal model control. Dexterous, compliant control will increase safety of the robot when accidentally impacting with humans or obstacles, and it will also allow the robot to recover more easily from external perturbation simply by ?giving in?. Such a control approach requires departing from the traditional high-gain position controlled humanoid systems, and focuses on torque control, reactive instantaneous control instead of finite horizon optimization, as well as efficient motion planning and learning methods.

在不久的将来，辅助机器人将成为人类社会的一个自然组成部分，在医院，学校，老年人护理设施，市中心城区，并最终家庭。虽然轮式机器人，例如，在移动的平台上的人形躯干，可以覆盖一系列的任务，辅助机器人将需要，最终，腿机器人将是最合适的，因为腿增加了机器人的有效工作空间，并允许操纵更复杂的地形，如步骤，路边，和混乱和粗糙的地形一般。与大多数其他项目相比，它强调在不平坦和粗糙的地形上行走，避免障碍物，从意外干扰中恢复，以及学习运动控制方法，因为这些问题对于在动态和部分不可预测的人类环境中工作似乎是最重要的。另一个焦点是灵巧的运动控制，即，使用具有内部模型控制的先进操作空间控制器，以最大的顺应性和最小的负反馈增益进行控制。灵巧，顺应性控制将增加安全的机器人时，意外影响到人类或障碍物，它也将使机器人更容易恢复从外部扰动简单？屈服？这种控制方法需要脱离传统的高增益位置控制的仿人系统，并专注于扭矩控制，反应瞬时控制，而不是有限时域优化，以及有效的运动规划和学习方法。