Real-Time Adaptive Motion Planning

实时自适应运动规划

• 批准号: 0742610
• 负责人: Jing Xiao
• 金额: --
• 依托单位: University of North Carolina at Charlotte
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2009-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0742610&HistoricalAwards=false
• 关键词: Real; Time; Adaptive; Motion; Planning

This SGER project addresses the largely open problem of motion planning of a high-degree-of-freedom robot (such as a manipulator, a mobile manipulator, or a humanoid robot, etc.) working in a mostly unknown or uncertain and dynamic environment with unknown obstacle motions. A novel real-time adaptive motion planning approach is proposed to tackle the problem. The project focuses on investigating key issues to make the approach feasible beyond simulation in the real world with imperfect sensing. Real-world experiments will be conducted for validation. The proposed research will significantly advance the state of the art in robot motion planning to enable more adaptive and autonomous robots and promise to broaden the application potential of robotics. This project will provide comprehensive training to student researchers in robotics. The research results could be used to attract students of all levels, especially under-represented groups, to science and technology. This project will also help enhancing outreach activities of the PI's lab related to high school students.

该SGER项目解决了高自由度机器人（如机械手，移动的机械手或人形机器人等）的运动规划的大部分开放问题。在大多数未知或不确定的动态环境中工作，具有未知的障碍物运动。提出了一种新的实时自适应运动规划方法来解决这个问题。该项目的重点是调查关键问题，使该方法在感知不完善的真实的世界中超越模拟。将进行真实世界实验进行验证。 拟议的研究将显着推进机器人运动规划的最新技术水平，以实现更具适应性和自主性的机器人，并有望扩大机器人技术的应用潜力。 该项目将为学生研究人员提供机器人技术的全面培训。研究结果可用于吸引各级学生，特别是代表性不足的群体，学习科学和技术。该项目还将有助于加强PI实验室与高中生有关的外展活动。