TY - GEN
T1 - Decentralized Task Allocation in Lossy Networks
T2 - 16th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2019
AU - Rantanen, Matthew
AU - Mastronarde, Nicholas
AU - Hudack, Jeffrey
AU - Dantu, Karthik
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - Advances in hardware, software and sensing are bringing swarms of robots to daily life. A major challenge in enabling such applications is multi-robot coordination. Most multi-robot coordination algorithms are developed under the assumption of perfect communication, which does not hold in practical wireless networks. To understand the consequences of this, we investigate the performance of a representative task allocation algorithm for multi-robot systems, namely, the Asynchronous Consensus Based Bundle Algorithm (ACBBA), in realistic network conditions. We show that the ACBBA deviates from its desired theoretical behavior when deployed in a realistic network. This manifests in the form of redundant task assignments across agents, which violates the algorithm's "conflict-free" assignment constraint and degrades the task allocation efficiency. We explore several network-based mitigations to this problem.
AB - Advances in hardware, software and sensing are bringing swarms of robots to daily life. A major challenge in enabling such applications is multi-robot coordination. Most multi-robot coordination algorithms are developed under the assumption of perfect communication, which does not hold in practical wireless networks. To understand the consequences of this, we investigate the performance of a representative task allocation algorithm for multi-robot systems, namely, the Asynchronous Consensus Based Bundle Algorithm (ACBBA), in realistic network conditions. We show that the ACBBA deviates from its desired theoretical behavior when deployed in a realistic network. This manifests in the form of redundant task assignments across agents, which violates the algorithm's "conflict-free" assignment constraint and degrades the task allocation efficiency. We explore several network-based mitigations to this problem.
UR - https://www.scopus.com/pages/publications/85072996592
U2 - 10.1109/SAHCN.2019.8824898
DO - 10.1109/SAHCN.2019.8824898
M3 - Conference contribution
AN - SCOPUS:85072996592
T3 - Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks workshops
BT - 2019 16th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2019
PB - IEEE Computer Society
Y2 - 10 June 2019 through 13 June 2019
ER -