In this paper, we present an algorithm for manipulability based trajectory generation for any serial manipulator that has an inverse kinematic model that can obtain all solutions. Our strategy is a search based approach that analyzes candidate configurations at discrete points along the work-space trajectory. Given such a model we prove the configuration-space trajectories generated are optimal within the limit of the discretization of the work-space trajectory

In this paper, we explore preprocessing techniques aimed at efficiently mapping the workspace to the configuration space for redundant manipulators. Exploiting the increasing availability of memory we precompute a database for online use that allows fast querying of joint configurations with high manipulability. Such a system is useful for performing reaching and manipulation tasks, online force control, and quickly computing goal configurations for path planning algorithms. We have implemented a prototype system on the digital human version humanoid robot platform 2 (DH-HRP2) which we use to efficiently compute arm inverse kinematic solutions. We demonstrate the benefits of such a system applied to converting workspace trajectories to configuration space trajectories. Although we have applied the technique to finding joint configurations with high manipulability, our approach can be generalized to a variety of different priority measures that may be used for evaluating inverse kinematic solutions for redundant manipulators.

In this paper we present an online algorithm for pursuit-evasion in a unknown simply connected environment, for one pursuer that has minimal sensing and carries a set of stationary sentries that it can drop off and pick up during the pursuit. In our sensing model, the pursuer is only able to detect discontinuities in depth information (gaps), and it is able to find all of the evaders without any explicit localization or geometric information, by using a gap navigation tree. The strategy is based on growing an evader-free region, by reading "exploration" schedules from the gap navigation tree, that is constructed online. We prove that a pursuer with k + 1 sentries can clear any environment that could be cleared by k pursuers using the algorithm in L.J. Guibas et al. (1999), which required a complete map and perfect sensing.