The advantage of modular self-reconfigurable robot systems is their flexibility, but this advantage can only be realized if appropriate configurations (shapes) and behaviors (controlling programs) can be selected for a given task. In this paper, we present an integrated system for addressing high-level tasks with modular robots, and demonstrate that it is capable of accomplishing challenging, multi-part tasks in hardware experiments. The system consists of four tightly integrated components: (1) a high-level mission planner, (2) a large design library spanning a wide set of functionality, (3) a design and simulation tool for populating the library with new configurations and behaviors, and (4) modular robot hardware. This paper builds on earlier work by (in: Robotics: science and systems, 2016), extending the original system to include environmentally adaptive parametric behaviors, which integrate motion planners and feedback controllers with the system.
In @cite_13 , Castro introduce a high-level control framework for the CKBot modular robot. This framework lays the theoretical foundations for our high-level mission planner, one of the four major components of our system. We expand the framework into a larger system capable of addressing significantly more sophisticated tasks. In addition to the mission planner, we provide design and simulation tools for creating and testing modular robot configurations and behaviors, and a large library (52 designs, 97 behaviors, 19 properties) with designs capable of addressing a wide range of tasks. We expand the theoretical formalism introduced by Castro to include both behavior and environment properties, increasing the expressiveness of task specification, and introduce a performance improvement by grounding abstract action specifications in concrete configurations and behaviors prior to automata synthesis.
@cite_13
2155878025
This paper discusses the creation of provably correct control for modular robots from high-level tasks expressed using sentences in structured English. Due to the nature of modular robots, we address problems that include requirements on the geometry and motion characteristics of the robot; these requirements are captured using traits in the specification that are then used in the control generation process. Outlined in this paper is our approach for generating all the lower levels of control for a modular robot given the high-level problem statement. The approach includes the use of a configuration-gait-trait library for characterizing modular robots and tools for populating this library such as a physics-based simulator and gait creator. The approach is demonstrated in simulation and with the CKBot hardware platform.