Temporal logic robot mission planning for slow and fast actions

Raman, Vasumathi; Finucane, Cameron; Kress-Gazit, Hadas

doi:10.1109/iros.2012.6385935

Cited by 14 publications

(22 citation statements)

References 14 publications

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“…Action verification during the motion of the robot, having correctby-constructions controllers for temporal logic based synthesis, was proposed by Raman et al [13]. Here the physical robot was controlled and invoked by low-level behaviors.…”

Section: Related Workmentioning

confidence: 99%

Linear Temporal Logic-based Mission Planning

Kumar¹,

Kala²

2016

IJIMAI

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-In this paper, we describe the Linear Temporal Logic-based reactive motion planning. We address the problem of motion planning for mobile robots, wherein the goal specification of planning is given in complex environments. The desired task specification may consist of complex behaviors of the robot, including specifications for environment constraints, need of task optimality, obstacle avoidance, rescue specifications, surveillance specifications, safety specifications, etc. We use Linear Temporal Logic to give a representation for such complex task specification and constraints. The specifications are used by a verification engine to judge the feasibility and suitability of plans. The planner gives a motion strategy as output. Finally a controller is used to generate the desired trajectory to achieve such a goal. The approach is tested using simulations on the LTLMoP mission planning tool, operating over the Robot Operating System. Simulation results generated using high level planners and low level controllers work simultaneously for mission planning and controlling the physical behavior of the robot.

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Section: Related Workmentioning

confidence: 99%

Linear Temporal Logic-based Mission Planning

Kumar¹,

Kala²

2016

IJIMAI

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“…Don't go to D and E in certain time intervals." There has been rich literature on how to design controllers to meet temporal logic specifications (see Kress-Gazit et al (2009);Raman et al (2012); Lin et al (2002); Smith et al (2010); Ulusoy et al (2011)). The temporal logic formulae are typically predefined as a guideline for the behaviors of the system.…”

Section: Introductionmentioning

confidence: 99%

Temporal Logic Inference with Prior Information: An Application to Robot Arm Movements**Corresponding Author: Zhe Xu. We acknowledge the support of the National Science Foundation through grants number CNS0953976, CNS-1218109, and NRI-1426907, and the O_ce of Naval Research through grant number N00014-14-1-0554 for the research reported in this paper.

Belta

Julius

2015

IFAC-PapersOnLine

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Temporal logics are widely used to express (desired) system properties in controller synthesis and verification. In linear temporal logics, the semantics of the formulae are defined on the execution trajectories of the system. Recently, there have been a lot of interest in using dense-time linear temporal logic, such as Signal Temporal Logic (STL) in characterizing system trajectories. In this paper, we present a new method to derive an STL formula that characterizes the motion of a robot arm. Our work generalizes earlier work in this area by (i) allowing the use of polyhedral predicates, and (ii) incorporating a priori knowledge about the predicates. The formula is defined by a set of parameters, whose values are determined by minimizing a cost function that balances the trade-off between the formula's match with the trajectories and the the similarity between its predicate and an a priori known predicate. We apply our algorithm on experimental trajectories generated using a PHANToM Omni robot.

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“…Given a discrete transition between two states with different locations, the motion controller for driving the robot between regions is activated first, and the remaining controllers are only activated (or deactivated) once the robot has crossed into the new region. However, as described in [11], there are artifacts of this continuous execution paradigm that are not modeled at the discrete level. These include a delayed response to events in the environment, and unsafe continuous executions even though the discrete automaton is provably correct.…”

Section: Introductionmentioning

confidence: 99%

“…If the execution paradigm is changed to activate the fast actions as soon as possible (before the slow actions complete), the synthesis algorithm must be changed to ensure safe continuous execution [11]. However, with this approach, the execution paradigm ignores changes in the environment once a transition has been started, until the destination state is reached.…”

Section: Introductionmentioning

confidence: 99%

Provably correct continuous control for high-level robot behaviors with actions of arbitrary execution durations

Raman

Piterman

Kress-Gazit

2013

2013 IEEE International Conference on Robotics and Automation

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Formal methods have recently been successfully applied to construct verifiable high-level robot control. Most approaches use a discrete abstraction of the underlying continuous domain, and make simplifying assumptions about the physical execution of actions given a discrete implementation. Relaxing these assumptions unearths a number of challenges in the continuous implementation of automatically-synthesized hybrid controllers. This paper describes a controller-synthesis framework that ensures correct continuous behaviors by explicitly modeling the activation and completion of continuous low-level controllers. The synthesized controllers exhibit desired properties like immediate reactiveness to sensor events and guaranteed safety of physical executions. The approach extends to any number of robot actions with arbitrary relative timings.

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Temporal logic robot mission planning for slow and fast actions

Cited by 14 publications

References 14 publications

Linear Temporal Logic-based Mission Planning

Linear Temporal Logic-based Mission Planning

Provably correct continuous control for high-level robot behaviors with actions of arbitrary execution durations

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