Simulated annealing with adaptive neighborhood: A case study in off-line robot path planning

► Study of simulated annealing parameters. ► Simulated annealing increases the number of accepted candidates without using derivatives. ► Trajectory representation. ► Study of trajectory parameters. Simulated annealing (SA) is an optimization technique that can process cost functions with degrees of nonlinearities, discontinuities and stochasticity. It can process arbitrary boundary conditions and constraints imposed on these cost functions. The SA technique is applied to the problem of robot path planning. Three situations are considered here: the path is represented as a polyline; as a Bézier curve; and as a spline interpolated curve. In the proposed SA algorithm, the sensitivity of each continuous parameter is evaluated at each iteration increasing the number of accepted solutions. The sensitivity of each parameter is associated to its probability distribution in the definition of the next candidate.