A decentralized control framework for modular robots

Distributed control paradigm offers robustness, scalability, and simplicity to the control and organization of module based systems. MSR (Modular Self-Reconfigurable) robot is a class of robot that best demonstrate the effectiveness of distributed systems as all modules in the robot are individuals that perform their own actuation and computation; the behavior of the complete robot is a collective behavior of all independent modules. In this paper, a general control framework, named General Suppression Framework, is proposed and a distributed control system based on the framework is presented. The control system is designed to control a set of MSR robots configured into a planar manipulator arm. All modules in the manipulator arm contain their own processing and actuation units, which allow them to evaluate and react to the environment independently. The modules can perform passive communication with their immediate neighbors and can exhibit aggressive or tolerant behavior based on the environment change to generate emergent group behaviors. A simulation program is developed to demonstrate the effectiveness of the distributed system in controlling the module based planar manipulator arm.published_or_final_versio

SUPERBOT: A Deployable, Multi-Functional, and Modular Self-Reconfigurable Robotic System

Abstract – Self-reconfigurable robots are modular robots that can autonomously change their shape and size to meet specific operational demands. Recently, there has been a great interest in using self-reconfigurable robots in applications such as reconnaissance, rescue missions, and space applications. Designing and controlling self-reconfigurable robots is a difficult task. Hence, the research has primarily been focused on developing systems that can function in a controlled environment. This paper presents a novel self-reconfigurable robotic system called SuperBot, which addresses the challenges of building and controlling deployable self-reconfigurable robots. Six prototype modules have been built and preliminary experimental results demonstrate that SuperBot is a flexible and powerful system that can be used in challenging realworld applications

Mission-Phasing Techniques for Constrained Agents in Stochastic Environments.

Resource constraints restrict the set of actions that an agent can take, such that the agent might not be able to perform all its desired tasks. Computational time limitations restrict the number of states that an agent can model and reason over, such that the agent might not be able to formulate a policy that can respond to all possible eventualities. This work argues that, in either situation, one effective way of improving the agent's performance is to adopt a phasing strategy. Resource-constrained agents can choose to reconfigure resources and switch action sets for handling upcoming events better when moving from phase to phase; time-limited agents can choose to focus computation on high-value phases and to exploit additional computation time during the execution of earlier phases to improve solutions for future phases. This dissertation consists of two parts, corresponding to the aforementioned resource constraints and computational time limitations. The first part of the dissertation focuses on the development of automated resource-driven mission-phasing techniques for agents operating in resource-constrained environments. We designed a suite of algorithms which not only can find solutions to optimize the use of predefined phase-switching points, but can also automatically determine where to establish such points, accounting for the cost of creating them, in complex stochastic environments. By formulating the coupled problems of mission decomposition, resource configuration, and policy formulation into a single compact mathematical formulation, the presented algorithms can effectively exploit problem structure and often considerably reduce computational cost for finding exact solutions. The second part of this dissertation is the design of computation-driven mission-phasing techniques for time-critical systems. We developed a new deliberation scheduling approach, which can simultaneously solve the coupled problems of deciding both when to deliberate given its cost, and which phase decision procedures to execute during deliberation intervals. Meanwhile, we designed a heuristic search method to effectively utilize the allocated time within each phase. As illustrated in experimental results, the computation-driven mission-phasing techniques, which extend problem decomposition techniques with the across-phase deliberation scheduling and inner-phase heuristic search methods mentioned above, can help an agent generate a better policy within time limit.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/60650/1/jianhuiw_1.pd

Movement of Modular Hydraulic Propulsion robots: Decentralised and reactive pose control strategies

Modular robotic systems consist of a set of reconfigurable units, called modules, which can be combined in a multitude of ways to produce robots of different shaps . One of the challenges in the design of these system is to enable them to perform precise movements in their environment. Control strategies that are centralised or rely on external sensing can limit the robustness and scalability of the system. This thesis focuses on the development of control strategies that allow the position and orientation (pose) of a modular robot to be controlled in a fully decentralised and reactive manner. The strategies are designed for the Modular Hydraulic Propulsion (MHP) system, wich operates in a liquid environment. An MHP robot is made of cubic modules, which create a fluid network when connected together. To move, the robot routes through this network fluid from the environment. A physical implementation of the MHP concept is designed, built and validated. An MHP robot’s ability to translate efficiently towards a goal is tested using occlusion based controllers, both with and without communication between modules. The robot is shown to reach the goal using either of the controllers. When using communication, an average of 70% of energy is saved, at the cost of a longer completion time. This thesis proposes multiple minimalistic controllers to control the pose of MHP robots. The robot is required to reach a goal in a preferred orientation. All of the controllers use binary sensing and actuation, with each module using only two bits of sensory information per face. The controllers are proposed for robots moving in 2D and 3D space, and use up to five bits of communication between modules. We prove that robots of convex shape are guaranteed to complete the task. Using computer simulations, the controllers are tested in different environments, using multiple module sizes and under the effect of noise. Additionally, their performance is compared against a centralised controller from the literature. Given the simplicity of the solutions, modules could potentially be realised at scales below a millimetre-cube, where robots of high spatial resolution could perform accurate movements in liquid environments