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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 - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, 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.
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https://hal.inria.fr/inria-00259321
Contributor : Thierry Fraichard <>
Submitted on : Wednesday, February 27, 2008 - 3:19:33 PM
Last modification on : Monday, December 28, 2020 - 3:44:01 PM
Long-term archiving on: : Thursday, May 20, 2010 - 8:00:07 PM

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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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