1 research outputs found
Optimal control for a robotic exploration, pick-up and delivery problem
This paper addresses an optimal control problem for a robot that has to find
and collect a finite number of objects and move them to a depot in minimum
time. The robot has fourth-order dynamics that change instantaneously at any
pick-up or drop-off of an object. The objects are modeled by point masses with
a-priori unknown locations in a bounded two-dimensional space that may contain
unknown obstacles. For this hybrid system, an Optimal Control Problem (OCP) is
approximately solved by a receding horizon scheme, where the derived lower
bound for the cost-to-go is evaluated for the worst and for a probabilistic
case, assuming a uniform distribution of the objects. First, a time-driven
approximate solution based on time and position space discretization and mixed
integer programming is presented. Due to the high computational cost of this
solution, an alternative event-driven approximate approach based on a suitable
motion parameterization and gradient-based optimization is proposed. The
solutions are compared in a numerical example, suggesting that the latter
approach offers a significant computational advantage while yielding similar
qualitative results compared to the former. The methods are particularly
relevant for various robotic applications like automated cleaning, search and
rescue, harvesting or manufacturing.Comment: 14 pages, 23 figure