CAREER: Advancing Mobile Robots to 3D

现在大多数移动机器人基本上都是在地面上移动，没有爬墙的能力。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，并且可以携带相对较大的有效载荷。与传统的地面移动机器人在2D空间中运行，无人机在3D空间中运行不同，city -攀登者机器人在受限的3D空间中运行，即其行动空间被限制在平面内，而感知空间是3D的，这得益于在地面、墙壁和天花板上的自由运动。这种归因既带来了机遇，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有利位置，以获得更好的视野。现有的多机器人系统规划/控制方法已不再适用，需要新的框架来处理这一涉及爬壁机器人的困难且尚未开发的研究领域。PI提出了一个总体框架，为处理在城市环境约束的三维空间中运行的一组异构爬壁机器人和地面机器人的规划、控制和协调问题提供理论基础。在这一重点中要研究的问题包括：复杂城市环境的世界模型的抽象；世界抽象与表示的计算效率与数据结构约束三维空间中多机器人团队的动态视图规划和运动规划；一个集成了离散世界表示、高层规划和低层控制原语的框架；使用几个范例任务（即，自我部署，监视覆盖，多机器人编队控制和目标跟踪）对框架进行案例研究，并对所提出的方法和算法进行实验验证。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，为学生提供指导研究经验，通过连贯的教育和推广活动改善教育管道，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 The challenges lie in the fact that most of the existing planning/control methods for multi-robot systems are no longer valid and it demands new framework to deal with this hard yet previously unexplored research domain involving wall-climbing robots.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.