Conference Paper

From structured english to robot motion.

Univ. of Pennsylvania, Philadelphia
DOI: 10.1109/IROS.2007.4398998 Conference: 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 29 - November 2, 2007, Sheraton Hotel and Marina, San Diego, California, USA
Source: DBLP

ABSTRACT Recently, Linear Temporal Logic (LTL) has been successfully applied to high-level task and motion planning problems for mobile robots. One of the main attributes of LTL is its close relationship with fragments of natural language. In this paper, we take the first steps toward building a natural language interface for LTL planning methods with mobile robots as the application domain. For this purpose, we built a structured English language which maps directly to a fragment of LTL.

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    ABSTRACT: In this paper, we consider the robust interpretation of metric temporal logic (MTL) formulas over timed sequences of states. For systems whose states are equipped with nontrivial metrics, such as continuous, hybrid, or general metric transition systems, robustness is not only natural, but also a critical measure of system performance. In this paper, we define robust, multi-valued semantics for MTL formulas, which capture not only the usual Boolean satisfiability of the formula, but also topological information regarding the distance, ε, from unsatisfiability. We prove that any other timed trace which remains ε-close to the initial one also satisfies the same MTL specification with the usual Boolean semantics. We derive a computational procedure for determining an under-approximation to the robustness degree ε of the specification with respect to a given finite timed state sequence. Our approach can be used for robust system simulation and testing, as well as form the basis for simulation-based verification. KeywordsRobustness-Metric spaces-Monitoring-Timed State Sequences-Metric and Linear Temporal Logic
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    ABSTRACT: A temporal logic paradigm to specify the mission objectives and then to automatically derive the high level control definition required for an abstract robotic system is presented. Such paradigms for defining mission con-troller have been advocated by several researchers for mobile robots since the obtained controller can be proved to be correct by construction, provided that a correct specification formula is given. In this paper the problem of translating a Linear Temporal Logic (LTL) formula into a mission controller implementation is analyzed. One finding is that all the published solutions for that problem follow a static approach when the formula is used off-line to define a complete controller and then implemented as a fixed controller. Dynamic approaches for this problem are unknown, even though potentially they have several advantages, like the progressive construction of the solution, the ability to deal with changeable specifications and unknown environments, and the advantage of not having to visit the entire state space for finding a working solution. The paper also deals with the actual application of mission control specification through LTL formulae including the use of temporal commands, how to convert different robotic modes -like reactive or behavior control -into logic formulation, and how to deal with dynamic definitions. Finally typical mission specification patterns are studied. The main conclusion is that the LTL formulation is a very powerful tool for defining high level control for robotic abstractions, since the formula can be translated automatically into the desired mission controller, and most of the situations with mission control can be solved. However the necessity to improve or change currently available static conversion approaches is observed, and a dynamic approach solution for that problem suggested here is the main original contribution of this article.
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    ABSTRACT: Recently, formal methods have been used to transform high-level robot tasks into correct-by-construction controllers. While correctness is guaranteed, these inherently discrete methods often lead to behaviors that are not optimal in the continuous sense, i.e. they induce robot paths that are significantly suboptimal. This paper proposes an algorithm for dynamically reordering the robot goals and connecting them via the shortest path with respect to a given continuous metric. The generated robot trajectories are close-to-optimal while satisfying the task specification in a dynamic environment. This method is implemented and simulation results are shown.
    Robotics and Automation (ICRA), 2013 IEEE International Conference on; 01/2013

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