Maneuvering over Deformable Terrain: Long-horizon Task and Motion Planning of Bipedal Locomotion via Contact Sensing and Terrain Adaptation

在可变形地形上操纵：通过接触传感和地形适应进行双足运动的长视野任务和运动规划

• 批准号: 2328254
• 负责人: Ye Zhao
• 金额: $ 95.64万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2328254&HistoricalAwards=false
• 关键词: Maneuvering; over; Deformable; Terrain; Long

The main aim of this grant is to enhance the planning abilities of robots with legs. Specifically, the team will equip robots with the necessary tools to walk on challenging and ever-changing surfaces, like construction sites filled with loose rocks and debris. This task is quite difficult because robots with legs have many moving parts, and they struggle to plan their movements for such complex terrain. It becomes even more challenging when the ground is soft or unstable, as the robot must maintain its balance and control how it interacts with the surface. To achieve this goal, the PIs aim to enable robots to plan their actions in advance and adjust in real-time while walking on demanding surfaces. They are taking inspiration from biology to design better robots while bringing together different fields of study, such as understanding the dynamics of robots with legs and how they make contact with surfaces, as well as planning tasks and movements. This research will train a diverse group of students, including undergraduate students through the Georgia Tech Vertically Integrated Program, and underrepresented high-school students via the Engaging New Generation at Georgia Tech through Engineering & Science (ENGAGES) program. In addition, this award will support the inclusion of a graduate-level curriculum initiative integrated into a cross-disciplinary class to train PhD students at the interface of physics and robotics and broaden participation in computing, engineering, and science disciplines. If successful, the outcomes of this research could lead to the deployment of legged robots in various fields, including construction, agriculture, and urban environments. Ultimately, the project's overarching goal is to enhance the capabilities of bipedal robots, enabling them to navigate challenging terrains and contribute to various real-world applications, thereby making our lives easier and safer.Long-horizon, real-time, versatile bipedal robot locomotion over highly complex and deformable terrain is largely underexplored. This research aims to integrate deformable terrain physics, adaptive contact mechanism design, and multi-modal contact sensing into a unified task and motion planning framework and enable bipedal legged machines to maneuver over various harsh terrain. Particularly, this award will employ a convergent approach including: (i) multi-modal terrain contact mechanism for austere terrain classification and adaptation, (ii) physics-based granular terrain dynamics modeling and deformable patch contact modeling, and (iii) long-horizon planning algorithms solving terrain-adaptive distributed trajectory optimization while symbolically reasoning about versatile gaits and contact decisions. The PIs will uncover fundamental locomotion principles through extensive and representative robot-terrain interaction experiments at various spatiotemporal scales. This research will enable breakthroughs in the understanding of integrating complex terrain dynamics and rich contact sensing into bipedal locomotion planning and decision-making in a principled manner.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项拨款的主要目的是增强有腿机器人的规划能力。具体来说，该团队将为机器人配备必要的工具，以便在具有挑战性和不断变化的表面上行走，比如充满松散岩石和碎片的建筑工地。这项任务相当困难，因为有腿的机器人有许多运动部件，它们很难在如此复杂的地形上规划自己的运动。当地面很软或不稳定时，机器人必须保持平衡并控制它与地面的相互作用，这就变得更具挑战性了。为了实现这一目标，pi的目标是使机器人能够提前计划他们的行动，并在苛刻的表面上行走时实时调整。他们从生物学中获得灵感，设计出更好的机器人，同时将不同领域的研究结合在一起，比如了解有腿机器人的动力学，以及它们如何与表面接触，以及规划任务和运动。这项研究将培养多样化的学生群体，包括通过佐治亚理工学院垂直整合项目培养的本科生，以及通过佐治亚理工学院工程与科学（接合）项目培养的新一代高中生。此外，该奖项将支持将研究生水平的课程计划整合到跨学科课程中，以培养物理和机器人界面的博士生，并扩大计算机，工程和科学学科的参与。如果成功，这项研究的结果可能会导致有腿机器人在各个领域的部署，包括建筑、农业和城市环境。最终，该项目的总体目标是增强双足机器人的能力，使它们能够在具有挑战性的地形上行驶，并为各种现实世界的应用做出贡献，从而使我们的生活更轻松、更安全。长视距、实时、多用途双足机器人在高度复杂和可变形地形上的运动在很大程度上尚未得到充分的研究。本研究旨在将可变形地形物理、自适应接触机构设计和多模态接触传感集成到统一的任务和运动规划框架中，使双足足机器人能够在各种恶劣地形上机动。特别是，该合同将采用一种收敛方法，包括：(i)用于严格地形分类和适应的多模态地形接触机制，（ii）基于物理的颗粒地形动力学建模和可变形斑块接触建模，以及（iii）解决地形自适应分布式轨迹优化的长期规划算法，同时象征性地推理通用步态和接触决策。pi将通过在不同时空尺度上广泛和具有代表性的机器人-地形相互作用实验揭示基本的运动原理。本研究将突破对复杂地形动力学和丰富接触传感在两足运动规划和决策中的原则性理解。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。