TY - GEN
T1 - Optimal control of stochastic coverage strategies for robotic swarms
AU - Elamvazhuthi, Karthik
AU - Berman, Spring
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/6/29
Y1 - 2015/6/29
N2 - This paper addresses a trajectory planning and task allocation problem for a swarm of resource-constrained robots that cannot localize or communicate with each other and that exhibit stochasticity in their motion and task-switching policies. We model the population dynamics of the robotic swarm as a set of advection-diffusion-reaction partial differential equations (PDEs), a linear parabolic PDE model that is bilinear in the robots' velocity and task-switching rates. These parameters constitute a set of time-dependent control variables that can be optimized and broadcast to the robots prior to their deployment. The planning and allocation problem can then be formulated as a PDE-constrained optimization problem, which we solve using techniques from optimal control. Simulations of a commercial pollination scenario validate the ability of our control approach to drive a robotic swarm to achieve predefined spatial distributions of activity over a closed domain, which may contain obstacles.
AB - This paper addresses a trajectory planning and task allocation problem for a swarm of resource-constrained robots that cannot localize or communicate with each other and that exhibit stochasticity in their motion and task-switching policies. We model the population dynamics of the robotic swarm as a set of advection-diffusion-reaction partial differential equations (PDEs), a linear parabolic PDE model that is bilinear in the robots' velocity and task-switching rates. These parameters constitute a set of time-dependent control variables that can be optimized and broadcast to the robots prior to their deployment. The planning and allocation problem can then be formulated as a PDE-constrained optimization problem, which we solve using techniques from optimal control. Simulations of a commercial pollination scenario validate the ability of our control approach to drive a robotic swarm to achieve predefined spatial distributions of activity over a closed domain, which may contain obstacles.
UR - http://www.scopus.com/inward/record.url?scp=84938229550&partnerID=8YFLogxK
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U2 - 10.1109/ICRA.2015.7139435
DO - 10.1109/ICRA.2015.7139435
M3 - Conference contribution
AN - SCOPUS:84938229550
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 1822
EP - 1829
BT - 2015 IEEE International Conference on Robotics and Automation, ICRA 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 IEEE International Conference on Robotics and Automation, ICRA 2015
Y2 - 26 May 2015 through 30 May 2015
ER -