Qualitative analysis of POMDPs with temporal logic specifications for robotics applications IST Austria Technical Report Chatterjee, Krishnendu ; https://orcid.org/0000-0002-4561-241X Chmelik, Martin Gupta, Raghav Kanodia, Ayush ddc:005 We consider partially observable Markov decision processes (POMDPs), that are a standard framework for robotics applications to model uncertainties present in the real world, with temporal logic specifications. All temporal logic specifications in linear-time temporal logic (LTL) can be expressed as parity objectives. We study the qualitative analysis problem for POMDPs with parity objectives that asks whether there is a controller (policy) to ensure that the objective holds with probability 1 (almost-surely). While the qualitative analysis of POMDPs with parity objectives is undecidable, recent results show that when restricted to finite-memory policies the problem is EXPTIME-complete. While the problem is intractable in theory, we present a practical approach to solve the qualitative analysis problem. We designed several heuristics to deal with the exponential complexity, and have used our implementation on a number of well-known POMDP examples for robotics applications. Our results provide the first practical approach to solve the qualitative analysis of robot motion planning with LTL properties in the presence of uncertainty. IST Austria 2014 info:eu-repo/semantics/other doc-type:other text http://purl.org/coar/resource_type/c_18gh https://research-explorer.ista.ac.at/record/5426 https://research-explorer.ista.ac.at/download/5426/5537 Chatterjee K, Chmelik M, Gupta R, Kanodia A. <i>Qualitative Analysis of POMDPs with Temporal Logic Specifications for Robotics Applications</i>. IST Austria; 2014. doi:<a href="https://doi.org/10.15479/AT:IST-2014-305-v2-1">10.15479/AT:IST-2014-305-v2-1</a> eng info:eu-repo/semantics/altIdentifier/doi/10.15479/AT:IST-2014-305-v2-1 info:eu-repo/semantics/altIdentifier/issn/2664-1690 info:eu-repo/semantics/openAccess