Fault-Tolernat Vision-Guided Robotic Systems for Aerospace Applications

以标志性的加拿大武器技术为代表的空间机器人技术对加拿大的科学、商业和战略利益至关重要。特别是，可靠的视觉制导系统对于许多当前和不久的将来的机器人空间任务的自主操作至关重要，以支持交会、近距离机器人操作和自动行星着陆。由于加拿大国内空域广阔，采用配备视觉制导系统的空中机器人飞行器用于各种民用用途也很重要。尽管在过去二十年中取得了重大进展，但由于视觉系统的不可靠性、环境的不确定性以及多种物理和操作约束下的实际GN&C，视觉引导机器人系统仍然面临许多具有挑战性的问题。在航空航天应用中测试视觉引导机器人系统尤其具有挑战性，因为测试通常应该在实验室环境中进行，而最终的视觉引导机器人系统在航空航天环境中运行。******本研究计划旨在通过在故障检测和恢复、自适应监督控制以及可扩展的硬件在环仿真测试方法方面的一系列进步来增强视觉引导机器人系统的鲁棒性。该方法具有足够的通用性，适用于空间和空中机器人系统。最终目标是开发一种航空航天机器人系统电缆，它不仅能适应不准确和潜在错误的视觉信息，而且能适应影响飞行动力学和系统性能的动力学和校准不确定性。自适应监督控制在视觉系统发生部分或完全故障时选择最合适的控制动作。开发一种可扩展的硬件在环仿真，用于视觉引导机器人系统的现实测试，也是本研究的目标。提供给视觉算法和GN&C的实时三维视觉数据由实际激光测距仪或立体摄像机生成，而近距离操作或行星着陆时的相对运动由模拟机器人根据飞行动力学生成。将采用类似于流体力学/量纲分析的无量纲数学技术，对模型几何形状和模拟状态（如距离和速度）进行适当的缩放，以便在面对实验室测试的物理限制时实现动态相似性。******参与这项研究的研究生将有一个独特的机会获得航空航天工程的实践技能，同时在先进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的前沿问题上工作。

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.