Convex Approximation for LTL-based Planning
Shumpei Tokuda, Masaki Yamakita, Hiroyuki Oyama, Rin Takano
Abstract
We present a formulation for linear temporal logic (LTL)-based task planning of nonlinear dynamical systems. We consider pick-and-place task planning as a typical example of the planning task that can be modeled as a hybrid system that includes the states of robots and objects. LTL-based planning for hybrid systems is solved as a mixed-integer problem (MIP), especially a mixed-integer linear programming problem (MILP). Due to the formulation by the MILP, we could only deal with linear systems and linear constraints. In our proposed method, we apply a convex approximation to systems that have bilinear terms and quadratic terms in their dynamics. And we incorporate nonlinear systems into existing LTL-based planning as an MILP. We demonstrate the effectiveness through numerical simulations of a simple robot arm system and drone system.
BibTeX
@inproceedings{iros2021_convexapproximat,
title = {Convex Approximation for LTL-based Planning},
author = {Shumpei Tokuda and Masaki Yamakita and Hiroyuki Oyama and Rin Takano},
booktitle = {IROS 2021},
year = {2021}
}