CAREER: Hierarchical Abstractions for Planning and Control of Robotic Swarms

机器人群规划和控制的分层抽象Calin Belta由于最近在计算、通信、传感器和执行器技术方面的进步，现在有可能建立由数百个小型且廉价的地面、空中和水下机器人组成的团队。它们重量轻，易于运输和部署，可以放在小地方。这样的自治代理群提供了对单个故障的更强的健壮性，覆盖广泛区域的可能性，并通过并行性提高了计算能力。然而，在通信和计算能力有限的情况下，规划和控制如此庞大的智能体团队是一个在过去十年中备受关注的难题。为了适应大量具有非平凡运动学或动力学在复杂环境中运动的机器人，该项目提出了分层抽象。在较低的层次上，连续抽象通过提取群体的一组基本特征来降低问题的维度，同时正确地捕捉到机器人的约束。在更高的层次上，离散抽象关注环境的复杂性，并将规划和控制问题从连续系统的无限维世界映射到有限状态自动机的可判定世界。所提出的算法导致了Hills和LARAD的发展，Hills是一种面向群的高级规范语言，而LARAD是一种用于机器人自动部署的语言。在这些框架中，机器人运动计划是用高级语言以离散系统的语言中的字符串或时间逻辑公式来制定的，以捕捉环境的复杂性。Hills和LARAD是以模拟包的形式实现的，也用于机器人蜂拥而至的实验平台。虽然这个项目的目的是为蜂拥而至的问题提供解决方案，但这个项目解决了形状理论中的基本问题和众所周知的“n体问题”，这些问题传统上是在理论物理中研究的，并在原子物理和天体力学等领域找到了应用。另一方面，使用一种独特的离散抽象方法，这项工作试图扩大已知的可判定连续和混合系统的类别。最后，该项目的分层抽象体系结构为移动机器人的规划和控制开辟了一个新的方向，它创建了一个框架，在该框架中，处理环境复杂性的强大的离散算法可以无缝地结合用于非平凡机器人动力学的连续控制律。这项研究是高度跨学科的，涵盖了从传统的“连续”领域，如几何非线性控制，到“离散”领域，如形式分析，以及在机器人学和生物学之间的应用领域。教育计划的重点是通过引入混合系统、系统生物学、几何规划和控制以及生物信息学的研究生和本科生课程，在上述领域之间建立桥梁。它还包括一系列丰富的外联活动，包括指导高中教师，为参加机器人比赛的高中生提供评判和建议，以及指导代表不足的少数族裔本科生。

Hierarchical Abstractions for Planning and Control of Robotic SwarmsCalin BeltaAs a result of recent advances in computation, communication, sensor, and actuator technology, it is now possible to build teams of hundreds of small and inexpensive ground, air, and underwater robots. They are light, easy to transport and deploy, and can fit into small places. Such swarms of autonomous agents provide increased robustness to individual failures, the possibility to cover wide regions, and improve computational power through parallelism. However, planning and controlling such large teams of agents with limited communication and computation capabilities is a difficult problem that received a lot of attention in the past decade.To accommodate large numbers of robots with nontrivial kinematics or dynamics moving in complicated environments, this project proposes hierarchical abstractions. At a lower level, continuous abstractions reduce the dimension of the problem by extracting a set of essential features of the swarm, while correctly capturing the robot constraints. At a higher level, discrete abstractions focus on the complexity of the environment and map the planning and control problem from the infinite dimensional world of continuous systems to the decidable world of finite state automata. The proposed algorithms lead to the development of HILLS, a High Level Specification Language for Swarms, and LARAD, a LAnguage for Robot Automated Deployment. In these frameworks, robotic motion plans are formulated in a high level language in terms of strings or temporal logic formulas in the language of a discrete system capturing the complexity of the environment. HILLS and LARAD are implemented as simulation packages and also used in experimental platforms for swarming robotics.While aimed to providing a solution to the swarming problem, this project addresses fundamental issues in shape theory and the well-known "n-body problem," which are traditionally studied in theoretical physics and find applications in areas such as atomic physics and celestial mechanics. On the other hand, using a unique approach to discrete abstractions, this work attempts to enlarge the class of known decidable continuous and hybrid systems. Finally, the hierarchical abstraction architectures of this project open a new direction in planning and control of mobile robots by creating a framework in which powerful discrete algorithms dealing with the complexity of the environment can be seamlessly combined with continuous control laws for nontrivial robot dynamics.This research is highly interdisciplinary, covering topics ranging from traditionally "continuous" areas, such as geometric nonlinear control, to "discrete" areas such as formal analysis, as well as application areas at the boundary between robotics and biology. The educational plan is focused on building bridges among the above areas by introducing graduate and undergraduate courses on Hybrid Systems, Systems Biology, Geometric Planning and Control, and Bioinformatics. It also involves a rich spectrum of outreach activities, including mentoring of high school teachers, judging and advising high school students participating in robotics competitions, and mentoring under-represented minority undergraduate students.