ModMan: An Advanced Reconfigurable Manipulator System With Genderless Connector and Automatic Kinematic Modeling Algorithm

Yun, Alchan; Moon, Deaho; Ha, Junhyoung; Kang, Sungchul; Lee, Woosub

doi:10.1109/lra.2020.2994486

Cited by 32 publications

(16 citation statements)

References 16 publications

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“…The 1-5-1 NN structure is selected with 1 input neuron, 5 hidden neurons, and 1 output neuron for each joint. The NN weights are defined Control parameters α ei 125 β pi 0.5 κ f i 0.9 κ f i (1,2) 0.01 κ f i (3,4) 0.01 κ ai 0.5…”

Section: Establishment Of Experimental Platformmentioning

confidence: 99%

“…The modular robot manipulators (MRMs) [1,2] equipped with standard modules adapt to severe working conditions through changing their configurations and increasing/reducing modules. Since the modularization and light weight of MRMs, they are potential in numerous unmanned and complex environments, such as aerospace explorations, search-rescue operations, and medical assistance.…”

Section: Introductionmentioning

confidence: 99%

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Compensator-critic structure-based event-triggered decentralized tracking control of modular robot manipulators: theory and experimental verification

2021

Complex Intell. Syst.

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This paper presents a novel compensator-critic structure-based event-triggered decentralized tracking control of modular robot manipulators (MRMs). On the basis of subsystem dynamics under joint torque feedback (JTF) technique, the proposed tracking error fusion function, which includes position error and velocity error, is utilized to construct performance index function. By analyzing the dynamic uncertainties, a local dynamic information-based robust controller is designed to engage the model uncertainty compensation. Based on adaptive dynamic programming (ADP) algorithm and the event-triggered mechanism, the decentralized tracking control is obtained by solving the event-triggered Hamilton–Jacobi–Bellman equation (HJBE) with the critic neural network (NN). The tracking error of the closed-loop manipulators system is proved to be ultimately uniformly bounded (UUB) using the Lyapunov stability theorem. Finally, experimental results illustrate the effectiveness of the developed control method.

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Section: Establishment Of Experimental Platformmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Compensator-critic structure-based event-triggered decentralized tracking control of modular robot manipulators: theory and experimental verification

2021

Complex Intell. Syst.

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“…Modular robot manipulators (MRMs) [2,3] are composed of modules with standard interfaces, which have high flexibility and wide adaptability, and have attracted great attention from researchers in the field of robotics. Compared with the traditional robot which has a single configuration and cannot be combined arbitrarily, the MRM can be added or reduced modules to accomplish different tasks, such as deep-sea exploration [4], disaster rescue [5] and extreme environment operations [6].…”

Section: Introductionmentioning

confidence: 99%

Event-triggered-based cooperative game optimal tracking control for modular robot manipulator with constrained input

Wei

et al. 2022

Nonlinear Dyn

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In this paper, a cooperative game optimal tracking control method based on event-triggered mechanism for constrained input modular robot manipulators (MRMs) system is introduced. According to the joint torque feedback (JTF) technique, the dynamics model of the constrained input subsystem is established and the global state space equation is derived. The control inputs of n joints in the MRM system with constrained input are taken as n participants of cooperative game, the tracking control problem of the manipulator system is transformed into the optimal control problem based on the cooperative game. Next, a fusion function containing position and velocity errors is defined to construct the performance index function. In order to improve the control performance and robustness of the manipulator system, part of the known model information is used to devise controller, the model uncertainty is dealt by the neural network (NN) observer, and the

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“…[17] presented a motion planner which also synthesizes the manipulator for required tasks which includes elimination of the joints to reduce the DoF if required. Along with that, various modular designs has been presented in literature to provide the customized solutions and can be seen in [4,11,18,16,13,7] These solutions are majorly explored on the basis of generating modular compositions from a given set of modules and then checking the configurations if able to work or not on the prescribed tasks. Alongside, the configurations are explored mostly for a fixed DoF system and standard parameters.…”

Section: Introductionmentioning

confidence: 99%

Integrated Modular Solution for Task Oriented Manipulator Configuration Design

Dogra¹,

Sakshay²,

Padhee³

et al. 2021

Preprint

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Modular and reconfigurable robotic systems have been designed to provide a customized solution for the non-repetitive tasks to be performed in a constrained environment. Customized solutions are normally extracted from task-based optimization of the possible manipulator configurations but the solution are not integrated, for providing the modular compositions directly. In this work, in the first phase, a strategy of finding unconventional optimal configurations with minimal number of degrees-of-freedom are discussed based upon the prescribed working locations and the cluttered environment. Then, in the second phase, design of the modular and reconfigurable architecture is presented which can adapt these unconventional robotic parameters. Rather than generating and evolving the modular compositions, a strategy is presented through which the unconventional optimal configurations can be mapped directly to the modular compositions. The generated modular composition is validated using Robot Operating System for the motion planning between the prescribed working locations in a given cluttered environment.

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ModMan: An Advanced Reconfigurable Manipulator System With Genderless Connector and Automatic Kinematic Modeling Algorithm

Cited by 32 publications

References 16 publications

Compensator-critic structure-based event-triggered decentralized tracking control of modular robot manipulators: theory and experimental verification

Compensator-critic structure-based event-triggered decentralized tracking control of modular robot manipulators: theory and experimental verification

Event-triggered-based cooperative game optimal tracking control for modular robot manipulator with constrained input

Integrated Modular Solution for Task Oriented Manipulator Configuration Design

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