Novel Robust Motion Control Methods for the Formation of Robots with Docking Capabilities

用于形成具有对接能力的机器人的新型鲁棒运动控制方法

• 批准号: RGPIN-2014-06000
• 负责人: Biglarbegian, Mohammad
• 金额: $ 1.82万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=567522
• 关键词: Novel; Robust; Motion; Control; Methods

The theme of the applicant’s research program is on the development of novel motion control methodologies that can effectively handle disturbance/uncertainties for a frontier class of a high-utility modular mobile robots (MMRs) with docking capabilities. The use of mobile robots is dramatically increasing for applications such as in security, exploration, scientific data collection, search and rescue, etc. In the field of mobile robotics, MMRs represent a leading-edge class that offer significantly improved mobility and sensing compared to non-modular ones. Hence, recent research efforts to exploit their capabilities and enhance their functionalities are timely. Furthermore, developing efficient and novel motion control algorithms for MRRs will enable their utility for a wide spectrum of applications. The motion control methods to be developed in this proposal consist of both path planning and control algorithms for MMRs in formation operating in dynamic environments with the presence of noise and uncertainties, commonly encountered in actual robot operation environments. The formations considered in this proposal are either docked (rigid) or flexible. To the best of the applicant’s knowledge, robust motion control methods for the former (docked) that can handle disturbances/uncertainties in dynamics environments have not been introduced in the literature. For flexible formations, limited useful research has been introduced, yet more research needs to be undertaken to overcome many shortcomings that preclude the implementation of efficient motion controls for MMRs especially with the presence of noise, disturbances. The focus of this research program is on developing novel theoretical framework for motion control of MRRs, but to verify those techniques extensive simulations and experiments will be also conducted. The developed algorithms will be implemented using advanced processors such as reconfigurable computing to further increase their real-time operations. The proposed methodologies can be also applied to other systems which can fully or partially utilize the developed techniques such as in automotive, aerospace, and military/defense. This program aims to train several undergraduate and graduate students on design, modeling, advanced sensing and control of mechatronics systems that are of high demands for several industries such as automation, mining, aerospace, and automotive.

申请人的研究计划的主题是开发新的运动控制方法，可以有效地处理干扰/不确定性的前沿类的高效用模块化移动的机器人（MMR）与对接能力。移动的机器人的使用显着增加的应用，如在安全，勘探，科学数据收集，搜索和救援等领域的移动的机器人，MMR代表了领先的一类，提供显着改善的流动性和传感相比，非模块化的。因此，最近的研究努力，以利用其能力和增强其功能是及时的。此外，开发有效的和新颖的运动控制算法的MRR将使他们的效用为广泛的应用。在这个建议中开发的运动控制方法包括路径规划和控制算法的MMR信息在动态环境中运行，存在噪声和不确定性，通常会遇到在实际的机器人操作环境。本提案中考虑的编队是对接的（刚性）或柔性的。据申请人所知，在文献中还没有介绍用于前者（对接）的鲁棒运动控制方法，其可以处理动态环境中的干扰/不确定性。对于柔性编队，已经引入了有限的有用的研究，但是需要进行更多的研究来克服许多缺点，这些缺点妨碍了MMR的有效运动控制的实施，特别是在存在噪声、干扰的情况下。本研究计划的重点是开发新的理论框架，用于MRR的运动控制，但为了验证这些技术，还将进行广泛的模拟和实验。开发的算法将使用先进的处理器，如可重构计算，以进一步提高其实时操作。所提出的方法也可以应用于其他系统，可以完全或部分利用开发的技术，如在汽车，航空航天和军事/国防。该计划旨在培养几名本科生和研究生对机电一体化系统的设计，建模，先进的传感和控制，这些系统对自动化，采矿，航空航天和汽车等行业有很高的要求。