Trajectory planning in a dynamic workspace: a `state-time space' approach

Thierry Fraichard 1
1 SHARP - Automatic Programming and Decisional Systems in Robotics
GRAVIR - IMAG - Graphisme, Vision et Robotique, Inria Grenoble - Rhône-Alpes
Abstract : This paper presents a control architecture endowing a car-like vehicle moving in a dynamic and partially known environment with autonomous motion capabilities. Like most recent control architectures for autonomous robot systems, it combines three functional components: a set of basic real-time skills, a reactive execution mechanism and a decision module. The main novelty of the architecture proposed lies in the introduction of a fourth component akin to a meta-level of skills: the sensor-based manoeuvres, ie general templates that encode high-level expert human knowledge and heuristics about how a specific motion task is to be performed. The concept of sensor-based manoeuvres permit to reduce the planning effort required to address a given motion task, thus improving the overall response-time of the system, while retaining the good properties of a skill-based architecture, ie robustness, flexibility and reactivity. The paper focuses on the trajectory planning function (which is an important part of the decision module) and two types of sensor-based manoeuvres, trajectory following and parallel parking, that have been implemented and successfully tested on a real automatic car-like vehicle placed in different situations.
Type de document :
Article dans une revue
Advanced Robotics, Taylor & Francis, 1998, 13 (1), 〈10.1163/156855399X00928〉
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Soumis le : mercredi 27 février 2008 - 15:19:33
Dernière modification le : lundi 26 novembre 2018 - 11:52:08
Document(s) archivé(s) le : jeudi 20 mai 2010 - 20:00:07


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Thierry Fraichard. Trajectory planning in a dynamic workspace: a `state-time space' approach. Advanced Robotics, Taylor & Francis, 1998, 13 (1), 〈10.1163/156855399X00928〉. 〈inria-00259321〉



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