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Formal Performance Guarantees For Behavior-Based Localization Missions, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang
Formal Performance Guarantees For Behavior-Based Localization Missions, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang
Faculty Publications
Abstract— Localization and mapping algorithms can allow a robot to navigate well in an unknown environment. However, whether such algorithms enhance any specific robot mission is currently a matter for empirical validation. In this paper we apply our MissionLab/VIPARS mission design and verification approach to an autonomous robot mission that uses probabilistic localization software.
Two approaches to modeling probabilistic localization for verification are presented: a high-level approach, and a sample-based approach which allows run-time code to be embedded in verification. Verification and experimental validation results are presented for two different missions, each using each method, demonstrating the accuracy …
Establishing Performance Guarantees For Behavior-Based Robot Missions Using An Smt Solver, Feng Tang, Damian M. Lyons, Ronald Arkin
Establishing Performance Guarantees For Behavior-Based Robot Missions Using An Smt Solver, Feng Tang, Damian M. Lyons, Ronald Arkin
Faculty Publications
In prior work we developed an approach to formally representing behavior-based multi-robot programs, and the uncertain environments in which they operate, as process networks. We automatically extract a set of probabilistic equations governing program execution in that environment using a static analysis module called VIPARS, and solve these using a Dynamic Bayesian Network (DBN) to establish whether stated performance guarantees hold for the program in that environment. In this paper we address the challenge of expanding the range of performance guarantees that are possible by using an SMT-solver instead of a DBN. We translate flow functions, which are recursive probabilistic …