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Probabilistic Analysis of Correctness of High-Level Robot Behavior with Sensor Error

https://doi.org/10.15607/rss.2011.vii.020

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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A Fully Automated Framework for Control of Linear Systems from LTL Specifications

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Hierarchical Synthesis of Hybrid Controllers from Temporal Logic Specifications

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Probabilistic Reachability for Parametric Markov Models

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Probabilistic reachability for parametric Markov models

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Temporal and Modal Logic

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Automatic synthesis of multi-agent motion tasks based on LTL specifications

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Hybrid Controllers for Path Planning: A Temporal Logic Approach

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Sampling-based motion planning with deterministic μ-calculus specifications

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A probabilistic approach for control of a stochastic system from LTL specifications

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LTLMoP: Experimenting with language, Temporal Logic and robot control

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Sampling-based motion planning with temporal goals

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Motion planning and control from temporal logic specifications with probabilistic satisfaction guarantees

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Linear Time Logic Control of Discrete-Time Linear Systems

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Receding Horizon Temporal Logic Planning

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Temporal-Logic-Based Reactive Mission and Motion Planning

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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Incremental Verification of Parametric and Reconfigurable Markov Chains

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Probabilistic guarantees for high-level robot behavior in the presence of sensor error

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A Petri net based approach for multi-robot path planning

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Assume-guarantee reasoning framework for MDP-POMDP

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Getting it right the first time: Robot mission guarantees in the presence of uncertainty

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Synthesizing manipulation sequences for under-specified tasks using unrolled Markov Random Fields

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Performance Verification for Behavior-Based Robot Missions

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Mission Accomplished: An Introduction to Formal Methods in Mobile Robot Motion Planning and Control

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Guaranteeing High-Level Behaviors while Exploring Partially Known Maps

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Probabilistic Temporal Logic for Motion Planning with Resource Threshold Constraints

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