Configuration discovery of modular self-reconfigurable robots: Real-time, distributed, IR+XBee communication method

Baca, José; Woosley, Bradley; Dasgupta, Prithviraj; Nelson, Carl A.

doi:10.1016/j.robot.2017.01.012

Cited by 20 publications

(10 citation statements)

References 7 publications

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“…Remark 1 (Discovery of Platform Configuration): To define the transformation (7), we need the information on how the vessels are connected in the platform from which we can infer the orientations of the force vectors f i and the values of the parameters r i . This problem is known to be configuration discovery [14], [15] in modular robotics. Due to space limit, our work in this paper focuses on designing learning-based control scheme, and we leave integration of algorithms and hardware for configuration discovery as a future plan.…”

Section: A Modeling Of Connected-vesselsmentioning

confidence: 99%

Learning-based Nonlinear Model Predictive Control of Reconfigurable Autonomous Robotic Boats: Roboats

Kayacan

Park

Ratti

et al. 2019

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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This paper presents a Learning-based Nonlinear Model Predictive Control (LB-NMPC) algorithm for reconfigurable autonomous vessels to facilitate high-accurate path tracking. Each vessel is designed to latch to a pre-defined point of another vessel that allows the vessels to form a rigid body. The number of possible configurations of such vessels exponentially grows as the total number of vessels increases, which imposes a technical challenge in modeling and identification. In this work, we propose a framework consisting of a real-time parameter estimator and a feedback control strategy, which is capable of ensuring high-accurate path tracking for any feasible configuration of vessels. Novelty of our method is in that the parameter is estimated on-line and adjusts control parameters (e.g., cost function and dynamic model) simultaneously to improve path-tracking performance. Through experiments on different configurations of connectedvessels, we demonstrate stability of our proposed approach and its effectiveness in high-accuracy in path tracking.

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Section: A Modeling Of Connected-vesselsmentioning

confidence: 99%

Learning-based Nonlinear Model Predictive Control of Reconfigurable Autonomous Robotic Boats: Roboats

Kayacan

Park

Ratti

et al. 2019

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…There are several categories of hardware architecture for MSR robotic modules, such as lattice architecture (see, e.g., [22,28]), mobile architecture (e.g., [17,27,33]), chain architecture (e.g., [2,29]) and hybrid architecture (e.g., [6,31,35]). For the regular geometric organization, lattice architecture is the most convenient for computer modeling among all those architectures.…”

Section: Msr Robotsmentioning

confidence: 99%

An Approach to the Bio-Inspired Control of Self-reconfigurable Robots

Bie

Gutiérrez–Naranjo

Zhao

et al. 2017

Communications in Computer and Information Science

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Self-reconfigurable robots are robots built by modules which can move in relationship to each other. This ability of changing its physical form provides the robots a high level of adaptability and robustness. Given an initial configuration and a goal configuration of the robot, the problem of self-regulation consists on finding a sequence of module moves that will reconfigure the robot from the initial configuration to the goal configuration. In this paper, we use a bio-inspired method for studying this problem which combines a cluster-flow locomotion based on cellular automata together with a decentralized local representation of the spatial geometry based on membrane computing ideas. A promising 3D software simulation and a 2D hardware experiment are also presented.

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“…The work [8] is dedicated to the problem of communication between modular robots which a priori do not have information about their situation and previous communication sessions. In the proposed approach of building a communication network using an infrared channel, neighbouring nearby modules are first identified, and then other robots are identified based on the XBee channel.…”

Section: Related Workmentioning

confidence: 99%

Justification of the technical requirements of a fully functional modular robot

et al. 2017

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Abstract. Modular robots are characterized by limited built-in resources necessary for communication, connection and movement of modules, when performing reconfiguration tasks at rigidly interconnected elements. In developing the technological fundamentals of designing modular robots with pairwise connection mechanisms, we analysed modern hardware and model algorithms typical of a fully functional robot, which provide independent locomotion, communication, navigation, decentralized power and control. A survey of actuators, batteries, sensors, communication means, suitable for modular robotics is presented.

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Configuration discovery of modular self-reconfigurable robots: Real-time, distributed, IR+XBee communication method

Cited by 20 publications

References 7 publications

Learning-based Nonlinear Model Predictive Control of Reconfigurable Autonomous Robotic Boats: Roboats

Learning-based Nonlinear Model Predictive Control of Reconfigurable Autonomous Robotic Boats: Roboats

An Approach to the Bio-Inspired Control of Self-reconfigurable Robots

Justification of the technical requirements of a fully functional modular robot

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