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Dual objective motion planning subject to state constraints

Published online by Cambridge University Press:  14 December 2015

Nader Sadegh
Nader Sadegh*
Affiliation:
The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332–0405, USA
*
*Corresponding author. E-mail: sadegh@gatech.edu
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Summary

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This paper presents a novel motion planning approach inspired by the Dynamic Programming (DP) applicable to multi degree of freedom robots (mobile or stationary) and autonomous vehicles. The proposed discrete–time algorithm enables a robot to reach its destination through an arbitrary obstacle field in the fewest number of time steps possible while minimizing a secondary objective function. Furthermore, the resulting optimal trajectory is guaranteed to be globally optimal while incorporating state constraints such as velocity, acceleration, and jerk limits. The optimal trajectories furnished by the algorithm may be further updated in real time to accommodate changes in the obstacle field and/or cost function. The algorithm is proven to terminate in a finite number of steps without its computational complexity increasing with the type or number of obstacles. The effectiveness of the global and replanning algorithms are demonstrated on a planar mobile robot with three degrees of freedom subject to velocity and acceleration limits. The computational complexity of the two algorithms are also compared to that of an A*–type search.

Keywords

Time-OptimalMotion Planning Obstacle AvoidanceDynamic ProgrammingGlobal OptimizationSplineState ConstraintsMulti-objective

Information

Type
Articles
Information
Robotica , Volume 35 , Issue 5 , May 2017, pp. 1157 - 1175
Copyright
Copyright © Cambridge University Press 2015 

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