Fault-Tolernat Vision-Guided Robotic Systems for Aerospace Applications

用于航空航天应用的容错视觉引导机器人系统

• 批准号: RGPIN-2017-06764
• 负责人: Aghili, Farhad
• 金额: $ 1.82万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 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=759616
• 关键词: Fault; Tolernat; Vision; Guided; Robotic

Space robotics manifested by the iconic Canadarm technology is important to Canadian national interest for scientific, commercial, and strategic reasons. In particular, reliable vision-guided systems are critical for autonomous operation in many current and near future robotics space missions to support rendezvous, proximity robotic operations, and automated planetary landing. Adoption of aerial robotic vehicles equipped with vision-guided system for a variety of civilian uses is also important for Canada due to the vastness of its domestic airspace. Despite of significant progress made in the past two decades, vision guided robotic systems still face many challenging problems mainly due to undependability of vision systems, environmental uncertainties, and practical GN&C given multiple physical and operational constraints. Testing vision-guided robotics systems in aerospace applications is particularly challenging because the tests often should perform in a laboratory environment whereas the eventual vision-guided robotic systems operate in an aerospace environment.This research program is aimed at enhancing the robustness of vision-guided robotic system through a series of advancements in fault detection and recovery, adaptive supervisory control, as well as scalable hardware-in-the-loop simulation test methods. The methodology is general enough for applying to space and aerial robotic systems alike. The ultimate goal is to develop an aerospace robotic system cable of adaptively tuning itself against not only inaccurate and potentially erroneous visual information but against the dynamics and calibration uncertainties which affect the flight dynamics and system performance. The adaptive supervisory control chooses the most appropriate control action if partial or complete failure of the vision system happen. Development of a scalable hardware-in-the-loop simulation for realistic testing of vision-guided robotic systems is also aimed at in this research. Real-time 3D vision data to feed the vision algorithm and GN&C are generated by an actual laser range finder or a stereo camera, while the relative motion in a proximity operation or planetary landing is generated by a simulating robot according to flight dynamics. A dimensionless mathematical technique, analogous to fluid mechanics/dimensional analysis, will be adopted for proper scaling of the mockup geometry and the simulated states such as range and velocities in order to achieve dynamic similarities in the face of physical limitations of the laboratory testing.The graduate students involved in this proposed research will have a unique opportunity to acquire practical skills in aerospace engineering, while working on problems at the cutting edge of the theoretical development of advanced GN&C, adaptive estimation, 3D vision systems, fault recovery strategies, and HIL simulation technology.

标志性的Canadarm技术所体现的空间机器人技术对于加拿大的科学，商业和战略利益非常重要。特别是，可靠的视觉导航系统对于当前和不久的将来的许多机器人太空任务中的自主操作至关重要，以支持会合，接近机器人操作和自动行星着陆。由于加拿大国内空域广阔，采用配备视觉导航系统的空中机器人车辆用于各种民用也很重要。尽管在过去的二十年中取得了重大进展，视觉引导机器人系统仍然面临着许多具有挑战性的问题，主要是由于视觉系统的不可靠性，环境的不确定性，以及实际的GN&C给定的多个物理和操作约束。 视觉引导机器人系统在航空航天领域的应用是一个极具挑战性的课题，因为视觉引导机器人系统的测试通常需要在实验室环境中进行，而最终的视觉引导机器人系统则需要在航空航天环境中运行。本研究计划旨在通过一系列的改进，如故障检测与恢复、自适应监控、以及可扩展的硬件在环仿真测试方法。该方法是普遍适用于空间和航空机器人系统。最终的目标是开发一个航空航天机器人系统电缆的自适应调整本身不仅对不准确的和潜在的错误的视觉信息，但对影响飞行动力学和系统性能的动态和校准的不确定性。自适应监督控制在视觉系统发生部分或全部故障时，选择最合适的控制动作。开发一个可扩展的硬件在环仿真的视觉引导机器人系统的现实测试也是针对在这项研究中。实时3D视觉数据提供给视觉算法和GN&C由实际的激光测距仪或立体摄像机生成，而接近操作或行星着陆中的相对运动由模拟机器人根据飞行动力学生成。一个无量纲的数学技术，类似于流体力学/量纲分析，将采用适当的比例模型的几何形状和模拟的状态，如范围和速度，以实现动态相似性，在面对物理限制的实验室测试。研究生参与这项拟议的研究将有一个独特的机会，获得航空航天工程的实践技能，同时研究先进GN&C、自适应估计、3D视觉系统、故障恢复策略和HIL仿真技术的理论发展前沿问题。