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Path planning using state lattice for autonomous vehicle

Publication Type : Conference Paper

Publisher : 2017 International Conference on Technological Advancements in Power and Energy ( TAP Energy)

Source : 2017 International Conference on Technological Advancements in Power and Energy ( TAP Energy), IEEE, Kollam, India (2017)

Url : https://ieeexplore.ieee.org/document/8397363

Keywords : Aerospace electronics, autonomous vehicle, Constraints, grid, Kinematics, Lattices, Matrix algebra, Mobile robots, motion control, Motion planning, motion primitive, motion primitives, Path Planning, planning, robot kinematics, rotation matrix, space vehicles, state lattice, trajectory planning, Vehicles, Wheels

Campus : Amritapuri

School : School of Engineering

Department : Electrical and Electronics

Year : 2017

Abstract : Path, trajectory and motion planning are three fundamental classification which come under planning of autonomous vehicle. Path planning deals with searching a plausible path, mulling over of geometry, kinematics and constraints of the vehicle without considering its association with time. Here a path planning technique using state lattice strategy is adopted. A path set which incorporates all the geometry, kinematics and constraints of the vehicle, known as motion primitives is pre-figured and rotation matrix is used in this approach which describes the novelty. The primitives are pre-calculated so that while online searching of the path it won't take much investment in time and furthermore the constraints of the vehicle are included in the primitive design. The set of arranged motion primitives is alluded as state lattice. The motion primitive which is stored in structural array is later used to compute a feasible path in a map. Distinctive situations are considered for which the way has been found.

Cite this Research Publication : S. Pothan, Nandagopal J. L., and Selvaraj, G., “Path planning using state lattice for autonomous vehicle”, in 2017 International Conference on Technological Advancements in Power and Energy ( TAP Energy), Kollam, India, 2017.

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