Robot3D &amp;#x2014; A simulator for mobile modular self-reconfigurable robots

Winkler, Lutz; Vonásek, Vojtĕch; Wörn, Heinz; Přeučil, Libor

doi:10.1109/mfi.2012.6343016

Cited by 13 publications

(6 citation statements)

References 9 publications

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“…Furthermore, we tested the life span of the docking unit and measured the number of additional modules CoSMO is able to lift. According to the capabilities of the hinge, different organism topologies and possible motion behaviors have been evaluated using the Robot3D simulator [24].…”

Section: Preliminary Resultsmentioning

confidence: 99%

A theoretical approach to pneumatic muscle mechanics

Sorge

Cammalleri

2013

2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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In this paper we will present the CoSMO platform, a new mobile modular self-reconfigurable robot (MSR) platform which we developed within the two European projects REPLICATOR and SYMBRION. Compared to other MSR platforms, this platform possesses huge computational capabilities and it exhibits a large communication bandwidth between connected modules. Furthermore, its modules have the ability to share energy among each other and locomote in every main direction by their own. Due to the mechanical design, different organism topologies and motion behaviors enable CoSMO to be flexible to different tasks and to adapt to unforeseen changes in the environment. Nevertheless, the size and the mass of the robot modules are still comparable to other platforms. In this paper, we will give an overview of the architecture of the CoSMO platform, which is in its final stage of development. In particular, we will describe the mechanical, the electronic and the software design. We will present first tests with the prototype of the robot and will show the potential functionality of the platform in simulation.

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Section: Preliminary Resultsmentioning

confidence: 99%

A theoretical approach to pneumatic muscle mechanics

Sorge

Cammalleri

2013

2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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“…4.3) in a simulation framework that can simulate the power flow and the physical movements of a modular robotic organism in 3D space. One possible option can be to use the open source Robot3D simulator (Winkler and Wörn 2009;Winkler et al 2012). It is proposed because the Robot3D simulator used the design and form factor of the REPLICATOR robotic modules to dynamically simulate a swarm of mobile robots and modular robotic organisms.…”

Section: Improved Simulation Systemmentioning

confidence: 99%

Self-Sufficiency of an Autonomous Reconfigurable Modular Robotic Organism

Qadir¹

2015

Adaptation, Learning, and Optimization

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The role of adaptation, learning and optimization are becoming increasingly essential and intertwined. The capability of a system to adapt either through modification of its physiological structure or via some revalidation process of internal mechanisms that directly dictate the response or behavior is crucial in many real world applications. Optimization lies at the heart of most machine learning approaches while learning and optimization are two primary means to effect adaptation in various forms. They usually involve computational processes incorporated within the system that trigger parametric updating and knowledge or model enhancement, giving rise to progressive improvement. This book series serves as a channel to consolidate work related to topics linked to adaptation, learning and optimization in systems and structures. Topics covered under this series include:• complex adaptive systems including evolutionary computation, memetic computing, swarm intelligence, neural networks, fuzzy systems, tabu search, simulated annealing, etc.

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“…Motion model necessary for offline optimization and motion planning was realized using physical simulator based on ODE physical engine [17]. Videos from the experiments are available at: http://mrs.felk.cvut.cz/icra2015…”

Section: Experimental Verificationmentioning

confidence: 99%

Online motion planning for failure recovery of modular robotic systems

Vonásek

Neumann²,

Oertel³

et al. 2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

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Modular robots are built of many basic robotic modules that can be connected into robots of various shapes. These robots are able to recover from a failure by ejecting and replacing damaged modules. Although this type of failure recovery is usually suggested in literature, it may be precluded due inability of the broken modules to cooperate or if no spare modules are available. In such a case, locomotion of a damaged robot should be adapted to allow the robot to reach a repair station or even to finish its task without the need to exchange the broken modules. In this paper, we investigate how to adapt motions of modular robots with respect to failures using the concept of motion planning with motion primitives. The ability of the proposed system to recover from failures is verified in a simulation and also in a HW experiment.

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Robot3D — A simulator for mobile modular self-reconfigurable robots

Cited by 13 publications

References 9 publications

A theoretical approach to pneumatic muscle mechanics

A theoretical approach to pneumatic muscle mechanics

Self-Sufficiency of an Autonomous Reconfigurable Modular Robotic Organism

Online motion planning for failure recovery of modular robotic systems

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