RI: Small: Vision-Based Mobile Manipulation and Navigation

该项目的重点是解决机器人系统长期自主的一个关键障碍，即缺乏理论上有充分依据的惯性和基于视觉的传感器的自我校准方法，这些方法通常在复杂的机器人上找到。该项目的动力来自于开机即走机器人系统的愿景，该系统能够在不需要繁琐的手动传感器校准的情况下长期自主运行。研究小组在基于视觉的移动操作和导航的背景下解决了这个问题。这项工作的核心是：1.发展一个统一的数学理论，随时自动校准视觉惯性系统，以及2.用具有显著多样性的最先进、复杂的机器人(执行移动操作的人形机器人和进行户外导航的自主地面车辆)对所产生的算法进行实验表征。惯性感知对于人形平衡控制至关重要，而视觉感知将3D世界与机器人的身体坐标联系起来，从而实现操作。在自主地面车辆的情况下，单目和立体摄像机的校准仍然通常使用已知的校准目标来手动执行。该项目消除了对这一要求的需要。该项目的预期成果是：1.为类人机器人在非结构化环境中在很长一段时间内自主工作奠定了理论基础，2.地面车辆的新导航算法使它们能够以更高的敏锐度看到更远的地方。该项目明确地将本科生研究与目前在南加州大学计算机科学系运营的REU网站合作。

This project focuses on tackling a critical barrier to long-term autonomy for robotic systems, namely the lack of theoretically well-founded self-calibration methods for inertial and vision-based sensors, commonly found on sophisticated robots. The project is motivated by the vision of power-up-and-go robotic systems that are able to operate autonomously for long periods without requiring tedious manual sensor calibration. The research team addresses this problem in the context of vision-based mobile manipulation and navigation. The core foci of the work are: 1. the development of a unified mathematical theory of anytime, automatic calibration for visual-inertial systems, and 2. an experimental characterization of the resulting algorithms with state-of-the-art, sophisticated robots of significant diversity (humanoids performing mobile manipulation and autonomous ground vehicles navigating outdoors). Inertial sensing is critically important for humanoid balance control, while visual sensing relates the 3D world to the robot's body coordinates thereby enabling manipulation. In the case of autonomous ground vehicles, monocular and stereo camera calibration is still commonly performed manually using a known calibration target. The project obviates the need for this requirement. The expected outcomes of the project are: 1. a theoretical foundation for humanoid robots to function autonomously in unstructured environments over significant periods of time, and 2. new navigation algorithms for ground vehicles allowing them to see further with greater acuity. The project explicitly incorporates undergraduate research in cooperation with an REU site currently operational at the USC Computer Science Department.