Objects are often movable in the environment and do not have to be grasped from the presented placement. •Pre-grasp interaction can adjust object configuration in the environment to improve the task conditions for the final grasp. •Our video observation surveys the variety of pre-grasp interactions used by people in natural task settings. •The observed pre-grasp interactions can be described by...

Continuous GRASP (C-GRASP) is a stochastic local search metaheuristic for finding cost-efficient solutions to continuous global optimization problems subject to box constraints (Hirsch et al., 2006). Like a greedy randomized adaptive search procedure (GRASP), a C-GRASP is a multi-start procedure where a starting solution for local improvement is constructed in a greedy randomized fashion. In th...

We focus on grasp planning for a humanoid multi-fingered hand attached at the tip of a humanoid robot’s arm. The hand has potential possibility to grasp various objects under several situations. Since the multi-fingered hand can use several grasp types such as fingertip grasp, and envelope grasp with taking the advantage of degrees of freedom. We develop grasp planner which selects a feasible g...

Machine vision-based planar grasping detection is challenging due to uncertainty about object shape, pose, size, etc. Previous methods mostly focus on predicting discrete gripper configurations, and may miss some ground-truth grasp postures. In this article, a pixel-level method proposed, which uses deep neural network predict configurations RGB images. First, novel oriented arrow representatio...