Iterative temporal motion planning for hybrid systems in partially unknown environments

Abstract

This paper considers the problem of motion planning for a hybrid robotic system with complex and nonlinear dynamics in a partially unknown environment given a temporal logic specification. We employ a multi-layered synergistic framework that can deal with general robot dynamics and combine it with an iterative planning strategy. Our work allows us to deal with the unknown environmental restrictions only when they are discovered and without the need to repeat the computation that is related to the temporal logic specification. In addition, we define a metric for satisfaction of a specification. We use this metric to plan a trajectory that satisfies the specification as closely as possible in cases in which the discovered constraint in the environment renders the specification unsatisfiable. We demonstrate the efficacy of our framework on a simulation of a hybrid second-order car-like robot moving in an office environment with unknown obstacles. The results show that our framework is successful in generating a trajectory whose satisfaction measure of the specification is optimal. They also show that, when new obstacles are discovered, the reinitialization of our framework is computationally inexpensive.

Reactive mission and motion planning with deadlock resolution avoiding dynamic obstacles

“…This abstraction is composed with a specification of a multi-agent task to synthesize a strategy automaton encoding the mission plan. In contrast to approaches that would require on-the-fly re-planning upon encountering a physical deadlock (Bhatia et al 2010;Maly et al 2013;Karaman and Frazzoli 2009), the approach we propose automatically generates alternative plans within the synthesized automaton. As with any reactive task, there may exist no mission plan that guarantees the task, due to the conservative requirement that a mission plan must execute under all possible environment behaviors.…”

CASP solutions for planning in hybrid domains

“…Some examples include (Cimatti et al 2015;Cavada et al 2014;Tabuada et al 2002;Maly et al 2013;Bae et al 2016;Liu and Ozay 2014;Henzinger and Otop 2014), sampling-based planners (Karaman et al 2011;Lahijanian et al 2014). Similarly, falsification of hybrid systems tries to guide the search towards the error states, that can be easily cast as a planning problem, (Plaku et al 2013;Cimatti et al 1997).…”

Asymptotically Optimal Stochastic Motion Planning with Temporal Goals

“…Sampling-based motion planners have been augmented to satisfy a task specification given in ltl [7,8,10,18,19]. These works are able to quickly emit a satisfying trajectory for systems with hybrid and/or complex dynamics.…”