Motion planning using first-order synergies

This paper proposes a novel motion planning approach that exploits the concept of synergies (correlations) between degrees of freedom, extending it to the velocity space and calling them first-order synergies. An automatic partition method is defined to optimally divide the configuration space into cells where first-order synergies are significantly different. Using this partition, an algorithm that tends to grow a tree by extending the branches in the directions determined by the the first-order synergies of the cell where the leaf to be grown lies is introduced and called FOS-RRT. This allows the natural expansion of the tree along the directions determined by the data used to define the synergies. 2D examples illustrate the performance of the proposed approach, which is particularly attractive for potential applications in human-like robots using human synergies.