TY - GEN
T1 - Coordinating recharging of large scale robotic teams
AU - Drenner, Andrew
AU - Janssen, Michael
AU - Papanikolopoulos, Nikolaos
PY - 2009/12/11
Y1 - 2009/12/11
N2 - Robotic teams are often proposed for solving a number of problems, ranging from exploring unknown environments to monitoring areas for security or environmental contamination. These teams are composed of individual robots which may lack the capabilities to complete a task on their own. One critical capability required by teams regardless of the mission is the ability to have sufficient battery life to remain active for the duration of the mission. We present an approach for maintaining battery life by developing a hierarchical team composed of deployable robots and docking stations. Unlike other approaches, the approach presented here focuses on docking stations supporting multiple deployed robots simultaneously. In order to do so the docking stations must continually optimize their locations with respect to the robots in need of service. Discussion of the optimization is presented, along with simulation in multiple environments to illustrate the scalability of the approach to large robotic teams. The on-going transition of this algorithm to actual hardware is also discussed.
AB - Robotic teams are often proposed for solving a number of problems, ranging from exploring unknown environments to monitoring areas for security or environmental contamination. These teams are composed of individual robots which may lack the capabilities to complete a task on their own. One critical capability required by teams regardless of the mission is the ability to have sufficient battery life to remain active for the duration of the mission. We present an approach for maintaining battery life by developing a hierarchical team composed of deployable robots and docking stations. Unlike other approaches, the approach presented here focuses on docking stations supporting multiple deployed robots simultaneously. In order to do so the docking stations must continually optimize their locations with respect to the robots in need of service. Discussion of the optimization is presented, along with simulation in multiple environments to illustrate the scalability of the approach to large robotic teams. The on-going transition of this algorithm to actual hardware is also discussed.
UR - http://www.scopus.com/inward/record.url?scp=76249093627&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=76249093627&partnerID=8YFLogxK
U2 - 10.1109/IROS.2009.5354767
DO - 10.1109/IROS.2009.5354767
M3 - Conference contribution
AN - SCOPUS:76249093627
SN - 9781424438044
T3 - 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009
SP - 1357
EP - 1362
BT - 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009
T2 - 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009
Y2 - 11 October 2009 through 15 October 2009
ER -