Minimum time path planning for a robot

Meystel, A.; Guez, A.; Hillel, G.

doi:10.1109/robot.1986.1087461

Cited by 17 publications

(8 citation statements)

References 34 publications

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“…A minimum time planning approach for a robot was given by Meystel et al [MEY86]. In this method, the robot's acceleration, deceleration and turning capabilities were taken into consideration during planning in order to minimize the overall time-to-goal for the calculated trajectory.…”

Section: Search and Heuristic Methodsmentioning

confidence: 99%

Simultaneous Planning and Control for Autonomous Ground Vehicles

Galluzzo¹

2009

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Section: Search and Heuristic Methodsmentioning

confidence: 99%

Simultaneous Planning and Control for Autonomous Ground Vehicles

Galluzzo¹

2009

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“…A technique often referred to as obstacle growing [20] extends the obstacles by the dimensions of the robot. This alleviates the problem of collision detection in the path-planning problem since the robot can now be treated as a mass point.…”

Section: Dynamic Obstacle Extensionmentioning

confidence: 99%

Robust Collision Avoidance in Unknown Domestic Environments

Jacobs

Ferrein

Schiffer

et al. 2010

RoboCup 2009: Robot Soccer World Cup XIII

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Abstract. Service robots operating in domestic indoor environments must be endowed with a safe collision avoidance and navigation method that is reactive enough to avoid contacts with the furniture of the apartment and humans that suddenly appear in front of the robot. Moreover, the method should be local, i.e. should not need a predefined map of the environment. In this paper we describe a navigation and collision avoidance method which is all of that: safe, fast, and local. Based on a geometric grid representation which is derived from the laser range finder of our domestic robot, a path to the next target point is found by employing A * . The obstacles which are used in the local map of the robot are extended depending on the speed the robot travels at. We compute a triangular area in front of the robot which is guaranteed to be free of obstacles. This triangle serves as the space of feasible solutions when searching for the next drive commands. With this triangle, we are able to decouple the path search from the search for drive commands, which tremendously decreases the complexity. We used the proposed method for several years in RoboCup@Home where it was a key factor to our success in the competitions.

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“…When positioning is done in the obstacle-cluttered environment, the method of slalom situations can be applied and all the past alternatives can be found as topological passageways, and the final solution is determined by using dynamic programming or searching in the state-space [460]. For the multilink manipulator this approach is explored in [461] If minimum time is required while tracking the specified trajectory similar methods can be applied.…”

Section: Task Decompositionmentioning

confidence: 99%

Intelligent systems:

Meystel¹

2002

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Minimum time path planning for a robot

Cited by 17 publications

References 34 publications

Simultaneous Planning and Control for Autonomous Ground Vehicles

Simultaneous Planning and Control for Autonomous Ground Vehicles

Robust Collision Avoidance in Unknown Domestic Environments

Intelligent systems:

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