Machine learning and control for advanced planetary rover operations

用于先进行星漫游器操作的机器学习和控制

• 批准号: 565309-2021
• 负责人: Skonieczny, KrzysztofK
• 金额: $ 1.46万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=751967
• 关键词: Machine; learning; control; advanced; planetary

This research program studies space robots, and their ability to traverse challenging planetary terrains. As robotic space exploration targets more and more extreme terrains on the Moon and Mars an accurate understanding of how robots can recognize and predict risks improves chances of success. The entrapment of the Mars Exploration Rover Spirit in soft soil and the tears and punctures in the Mars Science Laboratory Curiosity rover's wheels demonstrate some of the current challenges of roving on Mars that this research will address.The goal of this research is to make advances in artificial intelligence and optimal control to produce better-informed risk analysis and energy-efficiency for rovers. In addition to addressing current challenges, this research also opens new opportunities for space exploration. Advanced rovers able to drive on steeper sandy slopes, for example, open exploration to a significant number of new craters and mountains. Efficient planning of robot routes can get more out of power-starved space missions.These areas of research will help maintain Canada's global leadership in space robotics, which provides the economy with a supply of high-tech jobs and inspires the next generation of Canadians to pursue science and engineering. The development of AI technology for space robotics will lead to significant socio-economic impact in Canada by training highly qualified personnel, attracting and retaining outstanding talent in Canada, further strengthening the AI ecosystem in Canada, creating new employment or entrepreneurship opportunities, and creating new revenue streams for the use of data in space exploration space industry.

这个研究项目研究太空机器人，以及它们穿越具有挑战性的行星地形的能力。随着机器人太空探索越来越多地瞄准月球和火星上的极端地形，对机器人如何识别和预测风险的准确理解提高了成功的机会。“勇气号”火星探测车被困在松软的土壤中，“好奇号”火星科学实验室探测车车轮上的撕裂和穿孔，都表明了目前在火星上漫游所面临的一些挑战，而这些挑战正是这项研究将要解决的。这项研究的目标是在人工智能和最优控制方面取得进展，为漫游者提供更明智的风险分析和能源效率。除了解决当前的挑战，这项研究还为太空探索开辟了新的机会。例如，先进的探测车能够在更陡峭的沙质斜坡上行驶，对大量新的陨石坑和山脉进行探索。有效的机器人路线规划可以从电力匮乏的太空任务中获得更多。这些领域的研究将有助于保持加拿大在太空机器人领域的全球领导地位，这将为经济提供高科技工作岗位，并激励下一代加拿大人追求科学和工程。空间机器人人工智能技术的发展将通过培养高素质人才，吸引和留住加拿大优秀人才，进一步加强加拿大的人工智能生态系统，创造新的就业或创业机会，并为空间探索航天业的数据使用创造新的收入来源，从而对加拿大产生重大的社会经济影响。