Paper Info
Title
Sampling-Based Motion Planning with μ-Calculus Specifications Without Steering.
Abstract
While using temporal logic specifications with motion planning has been heavily researched, the reliance on having an available steering function is impractical and often suited only to basic problems with linear dynamics. This is because a steering function is a solution to an optimal two-point boundary value problem (OBVP); to our knowledge, it is nearly impossible to find an analytic solution to such problems in many cases. Addressing this issue, we have developed a means of combining the asymptotically optimal and probabilistically complete kinodynamic planning algorithm SST* with a local deterministic $mu$ -calculus model checking procedure to create a motion planning algorithm with deterministic $mu$ -calculus specifications that does not rely on a steering function. The procedure involves combining only the most pertinent information from multiple Kripke structures in order to create one abstracted Kripke structure storing the best paths to all possible proposition regions of the state-space. A linear-quadratic regulator (LQR) feedback control policy is then used to track these best paths, effectively connecting the trajectories found from multiple Kripke structures. Simulations demonstrate that it is possible to satisfy a complex liveness specification for infinitely often reaching specified regions of state-space using only forward propagation.
Year
DOI
Venue
2018
10.1109/icra.2018.8460769
ICRA
Field
DocType
Volume
Kripke structure,Motion planning,Kinodynamic planning,Model checking,Temporal logic,Engineering,Asymptotically optimal algorithm,Trajectory,Calculus,Liveness
Conference
2018
Issue
Citations 
PageRank 
1
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Luc Larocque100.34
Jun Liu221520.63