The theoretical ability of modular robots to reconfigure in response to complex tasks in a priori unknown environments has frequently been cited as an advantage, but has never been experimentally demonstrated. For the first time, we present a system that integrates perception, high-level mission planning, and modular robot hardware, allowing a modular robot to autonomously reconfigure in response to an a priori unknown environment in order to complete high-level tasks. Three hardware experiments validate the system, and demonstrate a modular robot autonomously exploring, reconfiguring, and manipulating objects to complete high-level tasks in unknown environments. We present system architecture, software and hardware in a general framework that enables modular robots to solve tasks in unknown environments using autonomous, reactive reconfiguration. The physical robot is composed of modules that support multiple robot configurations. An onboard 3D sensor provides information about the environment and informs exploration, reconfiguration decision making and feedback control. A centralized high-level mission planner uses information from the environment and the user-specified task description to autonomously compose low-level controllers to perform locomotion, reconfiguration, and other behaviors. A novel, centralized self-reconfiguration method is used to change robot configurations as needed.
Self-reconfiguration has been demonstrated with several other modular robot systems. CKbot, Conro, and MTRAN have all demonstrated the ability to join disconnected clusters of modules together @cite_17 @cite_16 @cite_25 . In order to align, Conro uses infra-red sensors on the docking faces of the modules, while CKBot and MTRAN use a separate sensor module on each cluster. In all cases, individual clusters locate and servo towards each other until they are close enough to dock. These experiments do not include any planning or sequencing of multiple reconfiguration actions in order to create a goal structure appropriate for a task. Additionally, modules are not individually mobile, and mobile clusters of modules are limited to slow crawling gaits. Consequently, reconfiguration is very time consuming, with a single connection requiring 5-15 minutes.
@cite_16 @cite_25 @cite_17
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The theoretical ability of modular robots to reconfigure in response to complex tasks in a priori unknown environments has frequently been cited as an advantage, but has never been experimentally demonstrated. For the first time, we present a system that integrates perception, high-level mission planning, and modular robot hardware, allowing a modular robot to autonomously reconfigure in response to an a priori unknown environment in order to complete high-level tasks. Three hardware experiments validate the system, and demonstrate a modular robot autonomously exploring, reconfiguring, and manipulating objects to complete high-level tasks in unknown environments. We present system architecture, software and hardware in a general framework that enables modular robots to solve tasks in unknown environments using autonomous, reactive reconfiguration. The physical robot is composed of modules that support multiple robot configurations. An onboard 3D sensor provides information about the environment and informs exploration, reconfiguration decision making and feedback control. A centralized high-level mission planner uses information from the environment and the user-specified task description to autonomously compose low-level controllers to perform locomotion, reconfiguration, and other behaviors. A novel, centralized self-reconfiguration method is used to change robot configurations as needed. Current research in self-reconfiguring robots focuses predominantly on systems of identical modules. However, allowing modules of varying types, with different sensors, for example, is of practical interest. In this paper, we propose the development of an algorithmic basis for heterogeneous self-reconfiguring systems. We demonstrate algorithmic feasibility by presenting O(n sup 2 ) time centralized and O(n sup 3 ) time decentralized solutions to the reconfiguration problem for n non-identical modules. As our centralized time bound is equal to the best published homogeneous solution, we argue that space, as opposed to time, is the critical resource in the reconfiguration problem. Our results encourage the development both of applications that use heterogeneous self-reconfiguration, and also heterogeneous hardware systems. A self-reconfigurable (SR) robot is one composed of many small modules that autonomously act to change the shape and structure of the robot. In this paper we consider a general class of SR robot modules that have rectilinear shape that can be adjusted between fixed dimensions, can transmit forces to their neighbors, and can apply additional forces of unit maximum magnitude to their neighbors. We present a kinodynamically optimal algorithm for general reconfiguration between any two distinct, 2D connected configurations of n SR robot modules. The algorithm uses a third dimension as workspace during reconfiguration. This entire movement is achieved within O( √ n) movement time in the worst case, which is the asymptotically optimal time bound. The only prior reconfiguration algorithm achieving this time bound was restricted to linearly arrayed start and finish configurations (known as the “x-axis to y-axis problem”). All other prior work on SR robots assumed a constant velocity bound on module movement and so required at least time linear in n to do the reconfiguration. In this paper we propose a novel algorithm that, given a source robot S and a target robot T, reconfigures S into T. Both S and T are robots composed of n atoms arranged in 2x2x2 meta-modules. The reconfiguration involves a total of O(n) atomic operations (expand, contract, attach, detach) and is performed in O(n) parallel steps. This improves on previous reconfiguration algorithms [D. Rus, M. Vona, Crystalline robots: Self-reconfiguration with compressible unit modules, Autonomous Robots 10 (1) (2001) 107-124; S. Vassilvitskii, M. Yim, J. Suh, A complete, local and parallel reconfiguration algorithm for cube style modular robots, in: Proc. of the IEEE Intl. Conf. on Robotics and Automation, 2002, pp. 117-122; Z. Butler, D. Rus, Distributed planning and control for modular robots with unit-compressible modules, Intl. J. Robotics Res. 22 (9) (2003) 699-715, doi:10.1177 02783649030229002], which require O(n^2) parallel steps. Our algorithm is in-place; that is, the reconfiguration takes place within the union of the bounding boxes of the source and target robots. We show that the algorithm can also be implemented in a synchronous, distributed fashion.