Beth Tsai Jennifer E. Walter Nancy M. Amato Department of Computer Science Texas A&M University, College Station Distributed Reconfiguration of Metamorphic.

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Beth Tsai Jennifer E. Walter Nancy M. Amato Department of Computer Science Texas A&M University, College Station Distributed Reconfiguration of Metamorphic Robot Chains

Metamorphic Robotic Systems Proposed by Chirikjian (ICRA94) and Murata et al. (ICRA94) Properties of metamorphic modules: 1)Uniformity in structure and capability – usually homogenous with regular symmetry (e.g., hexagons, cubes) – desirable for modules to fit together with minimal gaps 2)Mobility of individual modules allows system to change shape –modules can connect, disconnect, and move over adjacent modules –System composed of masses or clusters of modules

1 2 3 Motion planning problem determine sequence of moves to go from initial configuration I to final configuration G Problem Statement time I G | I | = |G| = n (number of modules in system) any module can fill any cell in G Step 1: move 3 CCW Step 2: move 3 CCW Step 3: move 2 CCW Step 4: move 2 CCW Step 5: move 2 CCW

General shape changing: construction, e.g., bridges, buttresses Potential Applications Object envelopment: surrounding objects for recovery or removal, e.g., satellite recovery, tumor excision

Our Summer Work Determining the best substrate path We can achieve a higher degree of parallelism if I is aligned with the substrate path Fastest reconfiguration occurs when the substrate path… 1)Is a straight chain 2)Equally bisects G 3)Is aligned parallel to longest axis of G 4)Intersects I at an obtuse angle We will represent G as an acyclic, directed graph. We will weight the edges of G and use Djikstra’s Shortest Path Algorithm to find the lowest cost (straightest) substrate path. A straight substrate path that equally bisects G and is parallel to the longest axis