A Graph Isomorphism-based Distributed Algorithm for Modular Robot Configuration Formation
Advisor Information
Prithviraj Dasgupta
Location
UNO Criss Library, Room 112
Presentation Type
Oral Presentation
Start Date
6-3-2015 2:00 PM
End Date
6-3-2015 2:15 PM
Abstract
We consider the problem of configuration formation in modular robot systems where a set of modules that are initially in arbitrary configurations and located at arbitrary locations are required to assume appropriate positions so that they can get into a new user-specified target configuration. We propose a novel algorithm based on graph isomorphism, where the modules select locations or spots in the target configuration using a utility based framework that reduces the time and energy required by the modules to assume the target configuration. We have shown analytically that our proposed algorithm is deterministic, and using it, a set of modules can converge to the desired configuration in finite time. Experimental simulations of our algorithm with different number of modules in different initial configurations and located initially at different locations, show that planning time of our algorithm is nominal (275 ms. for 100 modules) and total distance traveled by the modules to occupy their respective selected spots, increases linearly with number of modules. We have also compared our algorithm against the Bertsekas’ auction algorithm. Results show that our proposed algorithm outperforms the auction algorithm.
A Graph Isomorphism-based Distributed Algorithm for Modular Robot Configuration Formation
UNO Criss Library, Room 112
We consider the problem of configuration formation in modular robot systems where a set of modules that are initially in arbitrary configurations and located at arbitrary locations are required to assume appropriate positions so that they can get into a new user-specified target configuration. We propose a novel algorithm based on graph isomorphism, where the modules select locations or spots in the target configuration using a utility based framework that reduces the time and energy required by the modules to assume the target configuration. We have shown analytically that our proposed algorithm is deterministic, and using it, a set of modules can converge to the desired configuration in finite time. Experimental simulations of our algorithm with different number of modules in different initial configurations and located initially at different locations, show that planning time of our algorithm is nominal (275 ms. for 100 modules) and total distance traveled by the modules to occupy their respective selected spots, increases linearly with number of modules. We have also compared our algorithm against the Bertsekas’ auction algorithm. Results show that our proposed algorithm outperforms the auction algorithm.