Sampling-based stochastic optimal control with metric interval temporal logic specifications

Abstract

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Sampling-Based Path Planning for Multi-robot Systems with Co-Safe Linear Temporal Logic Specifications

“…Case 1: Only one atomic proposition is required in the transition, i.e., |Π req | = 1 (Alg. 2, lines [12][13][14][15]. In this case, if robot j can satisfy the required atomic proposition through the connection, a new state…”

“…Motion planning based on high-level temporal specifications has become an important area of research. Several methods have been developed for single robots, e.g., [5,15,18,22]; and for multiple robots, e.g., [2,6,19]. The multi-robot path planning problem with linear temporal logic (LTL) specifications can be categorised into two areas depending on the final goal: (i) each robot has its own task, or (ii) all the robots act as a team trying to accomplish a global specification.…”

Probabilistic Plan Synthesis for Coupled Multi-Agent Systems

“…Some recent works model the system in a probabilistic way and imposes high-level specifications, given in Linear Temporal Logic (see e.g., [Ding et al, 2011, Wolff et al, 2012, Ding et al, 2014, Fu et al, 2015, Wang et al, 2015). In [Montana et al, 2016], the authors modeled the system with an MDP and computed policies such that the satisfaction of a formula given in MITL, is maximized. Other works model the system in a probabilistic way with Markov Decision Processes (MDPs) and introduce high-level tasks in PCTL (see e.g., [Ayala et al, 2011, Lahijanian et al, 2012, Wu and Lin, 2015).…”

Sampling-Based Reactive Motion Planning with Temporal Logic Constraints and Imperfect State Information

“…Using model checking techniques, several methods have been developed to solve the problem of control synthesis for stochastic systems with perfect state information, e.g., [9,15]. However, only few solutions have been presented for stochastic systems with partially observable states.…”