Rolling and Climbing by the Multifunctional SuperBot Reconfigurable Robotic System

Shen, Wei; Chiu, Harris Chi Ho; Rubenstein, Michael; Salemi, Behnam

doi:10.1063/1.2845049

Cited by 17 publications

(11 citation statements)

References 4 publications

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“…Then, a scenario of the "complete" behaviors has been carried out without turning off the power or reloading the program. At the beginning, the rolling tracks rolls forward at the same speed (about 0.35m/s) as reported in our previous work [6]. The robot is then placed flatten down and recovered successfully by carrying out the recovery steps every 3 seconds as shown in Figure 3.…”

Section: Remotely Controllable Rolling Trackmentioning

confidence: 66%

“Deformable Wheel”-A Self-recovering Modular Rolling Track

Chiu

Rubenstein

Shen

2009

Distributed Autonomous Robotic Systems 8

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Section: Remotely Controllable Rolling Trackmentioning

confidence: 66%

“Deformable Wheel”-A Self-recovering Modular Rolling Track

Chiu

Rubenstein

Shen

2009

Distributed Autonomous Robotic Systems 8

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“…Many platforms of modular robot hardware was proposed such as Claytronics [1], SuperBot [2], Molecubes [3] or the metamorphic robots system of [4]. In these platforms, a collection of robots changes its global shape in order to reach H. Mabed Copyright (c) 2012 IEEE.…”

Section: Introductionmentioning

confidence: 99%

Scalable Distributed Protocol for Modular Micro-Robots Network Reorganization

Mabed

Bourgeois

2016

IEEE Internet Things J.

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The programmable material is one of the most challenging problems in micro-robot networking. In addition to the problems that raise by the miniaturization of millimeter-scale mobile devices; the conception of the distributed asynchronous algorithms allowing the coordination of large number of robots remains a very complex task. Micro-robot network represents one of the implementations of the Internet of Things, where a set of micro-robots react to an order submitted on a wireless downlink channel specifying a global goal. This goal corresponds to a target shape in the case of shape-shifting problem.Programmable materials have many applications in field of paintable displays, prototyping, locomotion, etc. We propose in this paper an original flexible distributed algorithm allowing to reorganize a modular micro-robot network into a desired target shape (phisical topology). The efficiency of such algorithm is assessed on the basis of the memory requirements, the communication load and the number of performed movements to reach the final shape.The proposed algorithm shows a great flexibility concerning the range of target shapes that can be achieved, in part because the no need for an explicit description of the final shape. To assess the computational performances of the presented algorithm, we proposed a linear programming model of the shape-shifting problem that provides a lower bounds of optimized criteria. The comparison of our results with those given by the relaxed linear programming proves the efficiency of our approach.

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“…While the rollingtrack is traveling, each module checks a value of its accelerometer to find its orientation and change its configuration following a given rule (sets of stateaction). Previously, in [3] and [9], Superbot did not recognize its environment and thus was unable to adapt accordingly. It simply obeyed the specified gait rule.…”

Section: A Different Rollingtrack Gaits Of Superbotmentioning

confidence: 99%

“…In [3] and [9], the accelerometer sensor was used to recognize each module's orientation. This is useful in developing various movement patterns(gaits) by programming different pairs of conditions and actions.…”

Section: B Two Purposes Of 3d Accelerometor Sensor In Superbotmentioning

confidence: 99%

An online gait adaptation with SuperBot in sloped terrains

Han

Ranasinghe

Barrios

et al. 2012

2012 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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Abstract-Among the different types of robots, modular and self-reconfigurable robots such as SuperBot have less limitations than their counterparts due to their versatility of gaits and increased dynamic adaptability. This results in a highly dexterous and adjustable robot suitable for many environments. This however, usually comes at the expense of a necessary human observer required to monitor and control the robot manually resulting in a waste of power and time. Thus, an intelligent system would be indispensable in optimzing the behavior and control of modular and self-reconfigurable robots. This paper presents an Intelligent Online Reconfiguration System (IORS) which through a combination of learning and reasoning, increases the efficiency in control and movement of the modular and self-reconfigurable robot called Superbot. Using this system, Superbot is able to learn and choose the best gait automatically by sensing its current environment (e.g., friction or slope). As a result, the IORS implementation in SuperBot achieves: 1) correct slope gradient sensing, 2) best gait learning to traverse different slopes, and 3) rational decision making for choosing the best gait.

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Rolling and Climbing by the Multifunctional SuperBot Reconfigurable Robotic System

Cited by 17 publications

References 4 publications

“Deformable Wheel”-A Self-recovering Modular Rolling Track

“Deformable Wheel”-A Self-recovering Modular Rolling Track

Scalable Distributed Protocol for Modular Micro-Robots Network Reorganization

An online gait adaptation with SuperBot in sloped terrains

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