CAREER: Advancing Mobile Robots to 3D

目前大多数移动的机器人基本上都是在地面上移动，没有爬壁能力。纽约城市学院（CCNY）开发的“城市攀登者”机器人能够在几乎任何光滑或粗糙的表面上移动，并能携带相对较大的有效载荷。与在2D空间中操作的常规地面移动的机器人和在3D空间中操作的UAV不同，城市攀登者机器人在受限的3D空间中操作，即，它的动作空间被限制在平面内，而感测空间是3D的，通过在地面、墙壁和天花板上的自由运动来促进。这一属性既带来了机遇，也带来了挑战。 其中一个好处是，城市攀登者可以在天花板或墙壁上占据Vantage位置，以获得更好的视野。挑战在于，大多数现有的多机器人系统的规划/控制方法不再有效，它需要新的框架来处理这个困难的，但以前未开发的研究领域，涉及爬壁机器人。PI建议开发一个通用的框架，并提供一个理论基础，以处理规划，控制和协调问题的一组异构爬壁机器人和地面机器人在城市环境的约束三维空间中运行。研究内容包括：复杂城市环境中世界模型的抽象、世界抽象与表示的计算效率和数据结构、受限三维空间中多机器人团队的动态视图规划和运动规划、离散世界表示、高层规划和底层控制原语的集成框架、多机器人团队的动态视图规划和运动规划、多机器人团队的动态视图规划和运动规划以及多机器人团队的动态视图规划和运动规划。使用几个范例任务的框架的案例研究（即，自部署，监视覆盖，多机器人的编队控制和目标跟踪），以及所提出的方法和算法的实验验证。作为职业发展计划的一个组成部分，拟议的教育活动包括：将研究融入课程，为学生提供指导性的研究经验，通过连贯的教育和推广活动改善教育渠道，加强针对K-12教育的机器人扩展计划。

Most of the mobile robots nowadays essentially move on the ground without wall-climbing capability. The "City-Climber" robots developed at the City College of New York (CCNY) are able to move on virtually any kind of smooth or rough surfaces and can carry a relative large payload. Unlike the conventional ground mobile robots operating in 2D space, and UAVs in 3D space, the City-Climber robots operate in constrained 3D space, i.e., its action space is confined within planar surfaces while the sensing space is 3D, facilitated by the freedom of motion on ground, walls, and ceilings. This attribution provides both opportunities and challenges. One of the benefits is that the City-Climber can take vantage positions on a ceiling or wall to gain better view of the scene. The challenges lie in the fact that most of the existing planning/control methods for multi-robot systems are no longer valid and it demands new framework to deal with this hard yet previously unexplored research domain involving wall-climbing robots. The PI proposed to develop a general framework and provide a theoretical foundation to deal with planning, control and coordination problems for a group of heterogeneous wall-climbing robots and ground robots operating in the constrained 3D space of urban environments. The issues to be studied in this thrust include: abstraction of world models for complex urban environments; computational efficiency and data structure for the world abstraction and representation; dynamic view planning and motion planning for a multi-robot team in constrained 3D space; a framework integrating the discrete world representation, high level planning and lower level control primitives; case studies of the framework using several exemplar tasks (i.e., self-deployment, surveillance coverage, formation control of multi-robots, and target tracking), and the experimental validation of the proposed methods and algorithms. Being an integral part of the career development plan, the proposed education activities include: integration of research into curriculum, mentored research experience for students, improving the educational pipeline with coherent education and outreach activities, enhancing the robotics extension programs targeted for K-12 education.