Path planning problems and solutions

Goldman, Jeffrey A.

doi:10.1109/naecon.1994.333013

Cited by 28 publications

(16 citation statements)

References 2 publications

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“…(lmin-0)/lmin < 0, (i = 1, ,n) (1) Maximum turning angle: it is the maximum angle a vehicle can take while swerving. This value is dependent on overload ability and the assignment.…”

Section: ) Route Constraintsmentioning

confidence: 99%

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An On-line Multiple Route(s) Planner for Air Vehicles Using Genetic Algorithms

JinRongt

Sun

Chen³

et al. 2006

The Proceedings of the Multiconference on "Computational Engineering in Systems Applications"

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An on-line multiple route(s) planner using genetic algorithms (GAs) for vehicles is proposed in this paper.The proposed algorithm solves the problem of various and conflict mission constraints efficiently through on-line map reading, real-value vector representation of chromosomes and classification-evaluation system. All routes evolve in their own sub-population simultaneously. Each sub-population provides an optimal route finally. If the environment changes during the computing, the algorithm will update the environment in time and then compute new route in the new environment with last result routes as the initial chromosomes. Simulation results demonstrate the feasibility of this approach.

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“…(lmin-0)/lmin < 0, (i = 1, ,n) (1) Maximum turning angle: it is the maximum angle a vehicle can take while swerving. This value is dependent on overload ability and the assignment.…”

Section: ) Route Constraintsmentioning

confidence: 99%

“…crossing (1) (2) disturbing (3)inserting G Om (4)deleting (5)smoothing (6)direction disturbing Fig.2 …”

Section: ) Classification-evaluation Systemmentioning

confidence: 99%

An On-line Multiple Route(s) Planner for Air Vehicles Using Genetic Algorithms

JinRongt

Sun

Chen³

et al. 2006

The Proceedings of the Multiconference on "Computational Engineering in Systems Applications"

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“…One of the enabling technologies of unmanned mobile systems is the ability to autonomously plan paths to navigate in an environment while avoiding obstacles (Goldman, 1994). While global path planning approaches are used to guide a UGV to a destination, a local path planning is necessary for a UGV to reactively avoid unexpected obstacles while following an overall trajectory generated by a global path planner.…”

Section: Introductionmentioning

confidence: 99%

A Reactive Bearing Angle Only Obstacle Avoidance Technique for Unmanned Ground Vehicles

Lwowski¹,

Sun²,

Mexquitic-Saavedra³

et al. 2014

JACR

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“…One of the fundamental tasks of mobile robotics is navigation [1], which consists of having to move from one place to another, this task isn't as trivial as it seems, since it is necessary to know the location of the robot in a given environment, and thus plan its next movement.…”

Section: Introductionmentioning

confidence: 99%

Path planning algorithm for a mobile robot with a synchronous propulsion architecture

Cardozo

Bedoya

Lopez

2013

2013 IEEE 56th International Midwest Symposium on Circuits and Systems (MWSCAS)

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In this paper an algorithm is proposed to plan the path taken by a robot in order to reach a specific coordinate. This algorithm is proposed to be used in a robot with a synchronous propulsion architecture, because this architecture improves robot odometry and is not common in navigation tasks, mapping and localization. Furthermore, this algorithm determines the shortest path with respect to the resolution of the displacement and rotation of the robot, minimizing the efforts to reach the desired goal.

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Path planning problems and solutions

Cited by 28 publications

References 2 publications

An On-line Multiple Route(s) Planner for Air Vehicles Using Genetic Algorithms

An On-line Multiple Route(s) Planner for Air Vehicles Using Genetic Algorithms

A Reactive Bearing Angle Only Obstacle Avoidance Technique for Unmanned Ground Vehicles

Path planning algorithm for a mobile robot with a synchronous propulsion architecture

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