Three Dimensional Stochastic Reconfiguration of Modular Robots

White, Paul; Zykov, Victor; Bongard, Josh; Lipson, Hod

doi:10.15607/rss.2005.i.022

Cited by 128 publications

(117 citation statements)

References 20 publications

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“…One class of robots that allows for morphological change during behavior is modular robotics (37), particularly at the meso-and microscale (38) where greater topological and material change is possible than if only a few macroscopic modules are employed.…”

Section: Discussionmentioning

confidence: 99%

Morphological change in machines accelerates the evolution of robust behavior

Bongard

2011

Proc. Natl. Acad. Sci. U.S.A.

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152

115

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Most animals exhibit significant neurological and morphological change throughout their lifetime. No robots to date, however, grow new morphological structure while behaving. This is due to technological limitations but also because it is unclear that morphological change provides a benefit to the acquisition of robust behavior in machines. Here I show that in evolving populations of simulated robots, if robots grow from anguilliform into legged robots during their lifetime in the early stages of evolution, and the anguilliform body plan is gradually lost during later stages of evolution, gaits are evolved for the final, legged form of the robot more rapidly-and the evolved gaits are more robust-compared to evolving populations of legged robots that do not transition through the anguilliform body plan. This suggests that morphological change, as well as the evolution of development, are two important processes that improve the automatic generation of robust behaviors for machines. It also provides an experimental platform for investigating the relationship between the evolution of development and robust behavior in biological organisms.evolutionary computation | robotics | evolutionary robotics | biomechanics | locomotion U sing robots to study adaptive behavior is of interest as a basic intellectual pursuit, but it may also lead to machines that assist or replace humans in unstructured or outdoor environments. To date, however, limited success has been achieved in realizing machines that continually perform simple yet robust behaviors in unstructured environments. It is contended here that this is due to overemphasis on the proximate mechanisms (1) of adaptive behavior-copying specific morphological and neuromorphological detail from organisms of interest into robots (2) in the hopes of replicating their behavior-and too little emphasis on the ultimate mechanisms of behavior-replicating the ontogenetic processes and selection pressures that gave rise to the behavior initially.To demonstrate the value of incorporating the evolution of development (3) into robotics, here I show that the automated discovery of robot behaviors can be accelerated if their body plans progress from an infant to an adult form over their lifetime (Fig. 1B)-and this ontogenetic change itself changes over successive generations of robots ( Fig. 1 D and F) such that later robots exhibit only the adult form during their lifetime (Fig. 1H)-than if robots maintain the adult form throughout behavior optimization. Moreover, robots evolved with this evolution-of-development method were found to be more robust to environmental perturbation than robots evolved without it because the former robots' ancestors assumed a range of body plans and thus had to maintain the behavior over a wider range of sensor-motor relationships.

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Section: Discussionmentioning

confidence: 99%

Morphological change in machines accelerates the evolution of robust behavior

Bongard

2011

Proc. Natl. Acad. Sci. U.S.A.

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152

115

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“…The Claytronics project envisions cylindrical [11,10], and eventually spherical modules, covered in magnetic or electrostatic actuators, that are capable of rolling relative to one another. Lipson et al have developed a stochastic fluidic assembly system consisting of cubic modules whose assembly is controlled by pressure and suction [19,17]. Klavins et al have developed a set of triangular tiles that circulate on an air table and magnetically bond with their neighbors [1].…”

Section: Related Workmentioning

confidence: 99%

What's in the Bag: A Distributed Approach to 3D Shape Duplication with Modular Robots

Gilpin¹,

Rus²

2012

Robotics: Science and Systems VIII

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Abstract-Our goal is to develop an automated digital fabrication process that can make any object out of smart materials. In this paper, we present an algorithm for creating shapes by the process of duplication, using modules we have termed smart sand. The object to be duplicated is dipped into a bag of smart sand; the particles exchange messages to sense the object's shape; and then the particles selectively form mechanical bonds with their neighbors to form a duplicate of the original.Our algorithm is capable of duplicating convex and concave 3D objects in a completely distributed manner. It uses O(1) storage space and O(n) inter-module messages per module. We perform close to 500 experiments using a realistic simulator with over 1400 modules. These experiments confirm the functionality and messaging demands of our distributed duplication algorithm while demonstrating that the algorithm can be used to form interesting and useful shapes.

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“…Often the categorization of a robot is ambiguous and there are other systems, like the Digital Clay project [8], that lack any innate actuation capability and rely on a user to rearrange the modules. There are many interesting systems which rely on stochastic selfassembly with rigid modules to create shapes [9]- [12]. More recent research [13] has investigated scaling the size of a selfassembled object based on the number of modules available.…”

Section: B Related Workmentioning

confidence: 99%

Making self-disassembling objects with multiple components in the Robot Pebbles system

Gilpin¹,

Koyanagi

Rus³

2011

2011 IEEE International Conference on Robotics and Automation

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Abstract-This paper describes several novel algorithms for shape formation by subtraction in programmable matter systems. These algorithms allow the simultaneous formation of multiple different shapes from a single block of host material. The resulting shapes are allowed to intertwine in arbitrarily complex ways. We also present a proof that the algorithms operate correctly to form the desired shapes. Finally, we show experimental results from close to 100 trials using both the Robot Pebbles hardware and a unique software simulator. Multiple trials of several different experiments demonstrate the algorithms operating correctly.

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Three Dimensional Stochastic Reconfiguration of Modular Robots

Cited by 128 publications

References 20 publications

Morphological change in machines accelerates the evolution of robust behavior

Morphological change in machines accelerates the evolution of robust behavior

What's in the Bag: A Distributed Approach to 3D Shape Duplication with Modular Robots

Making self-disassembling objects with multiple components in the Robot Pebbles system

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