Analyzing Unsynthesizable Specifications for High-Level Robot Behavior Using LTLMoP

Raman, Vasumathi; Kress-Gazit, Hadas

doi:10.1007/978-3-642-22110-1_54

Cited by 37 publications

(42 citation statements)

References 15 publications

(25 reference statements)

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“…In [28], an algorithm was defined to report a reason as to why a GR(1) LTL specification is unrealizable. The work in [15] presents a method of changing an unsatisfiable nondeterministic Büchi automaton into the "closest" satisfiable one, where all actions of the robot are represented using a finite state machine.…”

Section: Related Workmentioning

confidence: 99%

Iterative temporal motion planning for hybrid systems in partially unknown environments

Maly

Lahijanian

Kavraki

et al. 2013

Proceedings of the 16th International Conference on Hybrid Systems: Computation and Control

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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.

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Section: Related Workmentioning

confidence: 99%

Iterative temporal motion planning for hybrid systems in partially unknown environments

Maly

Lahijanian

Kavraki

et al. 2013

Proceedings of the 16th International Conference on Hybrid Systems: Computation and Control

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“…Given a robot task as an LTL formula belonging to the fragment described above, if the task is synthesizable [18] an automaton whose behaviors satisfy the formula will be automatically generated (see [17,14] for details).…”

Section: B Discrete Abstraction Of the Workpacementioning

confidence: 99%

“…Furthermore, if a specification contains behaviors that cannot be guaranteed (they may be inconsistent or there may be an environment in which the robot fails), no automaton will be synthesized and LTLMoP facilitates the process of understanding the problem in the given specification [18]. The experiments described in this paper were executed using LTLMoP as further discussed in Section VI.…”

Section: Ltl Mission Planner (Ltlmop)mentioning

confidence: 99%

Guaranteeing High-Level Behaviors while Exploring Partially Known Maps

Sarid¹,

Kress-Gazit

2012

Robotics: Science and Systems VIII

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Abstract-This paper presents an approach for automatically synthesizing and re-synthesizing a hybrid controller that guarantees a robot will exhibit a user-defined high-level behavior while exploring a partially known workspace (map).The approach includes dynamically adjusting the discrete abstraction of the workspace as new regions are detected by the robot's sensors, automatically rewriting the specification (formally defined using Linear Temporal Logic) and re-synthesizing the control while preserving the robot state and its history of task completion. The approach is implemented within the LTLMoP toolkit and is demonstrated using a Pioneer 3-DX in the lab.

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“…Our work is related to [21], [22], where the authors study the following problem: given an LTL specification and a model of a robot that does not satisfy this specification, decide whether or not the invalidity is limited to the provided model. Related literature includes also [6], where the authors aim to pinpoint the (un)realizable fragments of the specification to reveal causes of the specification violation.…”

Section: Introductionmentioning

confidence: 99%

Minimum-violation LTL planning with conflicting specifications

Tůmová

Castro

Karaman

et al. 2013

2013 American Control Conference

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Abstract-We consider the problem of automatic generation of control strategies for robotic vehicles given a set of highlevel mission specifications, such as "Vehicle x must eventually visit a target region and then return to a base," "Regions A and B must be periodically surveyed," or "None of the vehicles can enter an unsafe region." We focus on instances when all of the given specifications cannot be reached simultaneously due to their incompatibility and/or environmental constraints. We aim to find the least-violating control strategy while considering different priorities of satisfying different parts of the mission. Formally, we consider the missions given in the form of linear temporal logic formulas, each of which is assigned a reward that is earned when the formula is satisfied. Leveraging ideas from the automata-based model checking, we propose an algorithm for finding an optimal control strategy that maximizes the sum of rewards earned if this control strategy is applied. We demonstrate the proposed algorithm on an illustrative case study.

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Analyzing Unsynthesizable Specifications for High-Level Robot Behavior Using LTLMoP

Cited by 37 publications

References 15 publications

Iterative temporal motion planning for hybrid systems in partially unknown environments

Iterative temporal motion planning for hybrid systems in partially unknown environments

Guaranteeing High-Level Behaviors while Exploring Partially Known Maps

Minimum-violation LTL planning with conflicting specifications

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