TY - GEN
T1 - An intelligent docking station manager for multiple mobile service robots
AU - Ravankar, Abhijeet
AU - Ravankar, Ankit A.
AU - Kobayashi, Yukinori
AU - Jixin, Lv
AU - Emaru, Takanori
AU - Hoshino, Yohei
N1 - Publisher Copyright:
© 2015 Institute of Control, Robotics and Systems - ICROS.
PY - 2015/12/23
Y1 - 2015/12/23
N2 - Robot docking stations are of utmost important for service robots like security robots and automated guided vehicles in warehouses which are in continuous operation, and hence require frequent recharging. While a lot of research has been done on designing the actual hardware of the docking station itself, a practical situation of intelligently managing a limited number of docking stations in case of multiple robots has largely been ignored. We propose a docking station manager for multiple mobile service robots, which intelligently allots a mobile robot to the most appropriate docking station, based on the robot's task priority, location awareness of the robot and the docking station, power left in robot, and request order. We demonstrate, through experiments in real environment, that the proposed manager can function intelligently and resolve conflicts when the docking stations are fully occupied. We experimentally tested the proposed station manager in different conditions of varying task priorities, power levels, and emergency conditions of the robots, and found it to be robust to intelligently allocate the most appropriate robot with the appropriate charging dock.
AB - Robot docking stations are of utmost important for service robots like security robots and automated guided vehicles in warehouses which are in continuous operation, and hence require frequent recharging. While a lot of research has been done on designing the actual hardware of the docking station itself, a practical situation of intelligently managing a limited number of docking stations in case of multiple robots has largely been ignored. We propose a docking station manager for multiple mobile service robots, which intelligently allots a mobile robot to the most appropriate docking station, based on the robot's task priority, location awareness of the robot and the docking station, power left in robot, and request order. We demonstrate, through experiments in real environment, that the proposed manager can function intelligently and resolve conflicts when the docking stations are fully occupied. We experimentally tested the proposed station manager in different conditions of varying task priorities, power levels, and emergency conditions of the robots, and found it to be robust to intelligently allocate the most appropriate robot with the appropriate charging dock.
KW - intelligent systems
KW - robot docking station manager
KW - Service robots
UR - http://www.scopus.com/inward/record.url?scp=84966441020&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84966441020&partnerID=8YFLogxK
U2 - 10.1109/ICCAS.2015.7364881
DO - 10.1109/ICCAS.2015.7364881
M3 - Conference contribution
AN - SCOPUS:84966441020
T3 - ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings
SP - 72
EP - 78
BT - ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Conference on Control, Automation and Systems, ICCAS 2015
Y2 - 13 October 2015 through 16 October 2015
ER -