Raheem et al., 2018 - Google Patents
Path planning algorithm using D* heuristic method based on PSO in dynamic environmentRaheem et al., 2018
View PDF- Document ID
- 13541483074288841598
- Author
- Raheem F
- Hameed U
- et al.
- Publication year
- Publication venue
- American Scientific Research Journal for Engineering, Technology, and Sciences
External Links
Snippet
This paper is devoted to find a short and safe path for robot in environment with moving obstacles such as different objects, humans, animals or other robots. A mixing approach of robot path planning using the heuristic method D star (D*) algorithm based on optimization …
- 238000004422 calculation algorithm 0 title abstract description 26
Classifications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/50—Machine tool, machine tool null till machine tool work handling
- G05B2219/50109—Soft approach, engage, retract, escape, withdraw path for tool to workpiece
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
- G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
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