Guidance, Navigation and Control in Robotics, Medical and Aerospace Systems

机器人、医疗和航空航天系统中的制导、导航和控制

• 批准号: RGPIN-2016-06255
• 负责人: Sasiadek, Jurek
• 金额: $ 2.4万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=710236
• 关键词: Guidance; Navigation; Control; Robotics; Medical

The intelligent guidance, navigation and control systems for autonomous systems in robotics, aerospace engineering and medicine are the main focus of this proposal. Increasing requirements for autonomy make systems more and more complex, and, therefore more difficult to control. Recent events have highlighted the utility of the autonomous space and aerial robots for various tasks, including surveillance, space exploration, etc. The main problem with those systems is its ability for accurate localization, positioning and navigation. Space robots are used for outer planet exploration but also for space debris removal from higher orbits. In order to navigate autonomously UAVs or space robots must be able to estimate location and attitude. Position and attitude or pose of the robot is not easy to determine. It may involve, depending of the applications, inertial navigation sensors, GPS, and vision systems. All sensors suffer from number of problems and shortcomings and therefore, advanced sensor/data fusion algorithms are used to estimate position and/or location. This proposal builds on earlier investigation done by the applicant on sensor/data fusion methods and intelligent guidance, navigation and control for robotics. The objective of the proposed research is to make mobile, unmanned systems fully autonomous, and to developed advanced guidance, navigation, and control systems for autonomous vehicles and other moving and dynamic systems based on vision systems. The particular objectives are: 1. To investigate and develop new advanced intelligent methods and algorithms for sensor and data fusion that would allow autonomous systems better perception of its environment; 2. To investigate and develop new advanced guidance, navigation and, control systems and algorithms for unmanned autonomous mobile vehicles and aerospace robots, as well as, other autonomous systems; 3. To develop advanced localization and positioning methods for mobile robots and stationary manipulators that could be used for aerospace, medical and energy applications: 4. To investigate and develop advanced control systems for guidance and positioning of robots with flexible links and joints. The suggested methodology will be based on Adaptive and Extended Kalman Filtering (EKF), as well as, Unscented Kalman Filter (UKF). The adaptive procedure applied to the Kalman Filter gain will be based on fuzzy logic methodology. This would ensure the convergence in the case of signals with coloured noise. This procedure will be compared with some chosen statistical and probabilistic method. In particular, an extended Monte Carlo method and Particle Filter methods will be used. The developed methods, algorithms, and procedures will be applied to aerospace robots, mobile robots and medical manipulators. It is expected that significant progress will be made in robots environment perception and control.

机器人、航空航天工程和医学领域自主系统的智能制导、导航和控制系统是本提案的主要重点。对自主性的要求越来越高，使得系统变得越来越复杂，因此也越来越难以控制。最近的事件突出了自主空间和空中机器人在各种任务中的效用，包括监视，空间探索等。这些系统的主要问题是其精确定位、定位和导航的能力。太空机器人不仅用于探测外行星，还用于清除更高轨道上的空间碎片。为了自主导航，无人机或空间机器人必须能够估计位置和姿态。机器人的位置和姿态或姿态不容易确定。根据应用的不同，它可能涉及惯性导航传感器、GPS和视觉系统。所有传感器都存在许多问题和缺点，因此需要使用先进的传感器/数据融合算法来估计位置和/或位置。该提案建立在申请人对传感器/数据融合方法和机器人智能制导、导航和控制的早期研究基础上。