RI: Small: Pose and Trajectory Optimization with Pervasive Contact

RI：小：通过普遍接触进行位姿和轨迹优化

• 批准号: 1911087
• 负责人: Kris Hauser
• 金额: $ 50万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1911087&HistoricalAwards=false
• 关键词: RI; Small; Pose; Trajectory; Optimization

Robots traditionally avoid making contact with objects, except during deliberate and careful motions. This stands in stark contrast with how humans and other organisms treat contact as a fact of life. A big reason for this gap is that robots lack adequate mathematical and computational methods for decision-making while touching. The goal of this project is to help close this gap by investigating new mathematical models and software algorithms for robots to reason about contact forces, geometry, and motion. The new capabilities enabled by this research will help multi-fingered robots manipulate complex objects, legged robots to use all parts of their body to move about in rough terrain and human environments, and soft robots that can slide through tight spaces. The project will also release open-source software to help disseminate research results to the broader research community and accelerate the pace of robotics research. Other impacts include contributions to undergraduate education in robotics, and involvement of students from underrepresented groups as part of this research.The technical goal of this project is to investigate numerically-stable and computationally efficient models for pervasive, intimate contact between multiple objects through interactions such as stacking, sliding, rolling, and jamming. The approaches under study have the potential to overcome longstanding limitations in several fields including robotics, animation, computer-aided design, virtual reality, and operations research, which in the current state of practice view contact as a complicating factor to be avoided whenever possible. Specific aims include 1) to expand contact-implicit optimization methods to use scalable and numerically-stable semi-infinite constraints, 2) to develop fast robust stability prediction methods under geometric and friction uncertainty, and 3) to integrate knowledge of contact physics with data in order to perform probabilistic inference more accurately than physics or data alone. These methods will be tested on several realistic scenarios, including legged robot trajectory planning, simulation of object piles for bin-packing problems, and estimation of contact state from manipulation observations.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.

机器人传统上避免与物体接触，除非在故意和小心的运动中。 这与人类和其他生物如何将接触视为生活事实形成鲜明对比。 造成这种差距的一个重要原因是，机器人在触摸时缺乏足够的数学和计算方法来做出决策。 该项目的目标是通过研究机器人的新数学模型和软件算法来帮助缩小这一差距，以推断接触力，几何形状和运动。这项研究所带来的新功能将有助于多指机器人操纵复杂的物体，腿式机器人使用身体的所有部分在粗糙的地形和人类环境中移动，以及可以在狭窄空间中滑动的软机器人。该项目还将发布开源软件，以帮助将研究成果传播给更广泛的研究界，并加快机器人研究的步伐。其他影响包括对机器人本科教育的贡献，以及作为本研究一部分的来自代表性不足群体的学生的参与。本项目的技术目标是研究数字稳定和计算效率高的模型，用于多个对象之间通过堆叠，滑动，滚动和干扰等交互作用进行普遍的亲密接触。正在研究的方法有可能克服长期存在的局限性，在几个领域，包括机器人，动画，计算机辅助设计，虚拟现实和运筹学，在目前的实践状态下，视图接触作为一个复杂的因素，尽可能避免。具体目标包括：1）扩展接触隐式优化方法，以使用可扩展和数值稳定的半无限约束，2）开发几何和摩擦不确定性下的快速鲁棒稳定性预测方法，以及3）将接触物理知识与数据相结合，以便比单独的物理或数据更准确地执行概率推理。这些方法将在几个现实场景中进行测试，包括腿式机器人轨迹规划、装箱问题的物体堆模拟以及从操作观察中估计接触状态。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

项目成果

Implicit Integration for Articulated Bodies with Contact via the Nonconvex Maximal Dissipation Principle

通过非凸最大耗散原理对接触铰接体进行隐式积分

• 发表时间: 2021
• 期刊: IEEE International Conference on Robotics and Automation
• 作者: Pan, Zherong;Hauser, Kris
• 通讯作者: Hauser, Kris

Simultaneous Trajectory Optimization and Contact Selection for Multi-Modal Manipulation Planning

多模态操纵规划的同步轨迹优化和接触选择

• 发表时间: 2023
• 期刊: Robotics science and systems
• 作者: Zhang, Mengchao;Jha, Devesh;Raghunathan, Arvind;Hauser, Kris
• 通讯作者: Hauser, Kris

Semi-infinite programming for trajectory optimization with non-convex obstacles

非凸障碍物轨迹优化的半无限规划

• DOI: 10.1177/0278364920983353
• 发表时间: 2021
• 期刊: The International Journal of Robotics Research
• 作者: Hauser, Kris

Non-Penetration Iterative Closest Points for Single-View Multi-Object 6D Pose Estimation

• DOI: 10.1109/icra46639.2022.9812043
• 发表时间: 2022-05
• 期刊: 2022 International Conference on Robotics and Automation (ICRA)
• 作者: Mengchao Zhang;Kris K. Hauser

Semi-Infinite Programming with Complementarity Constraints for Pose Optimization with Pervasive Contact

• DOI: 10.1109/icra48506.2021.9561609
• 发表时间: 2021-05
• 期刊: 2021 IEEE International Conference on Robotics and Automation (ICRA)
• 作者: Mengchao Zhang;Kris K. Hauser