Heuristically initialized motion planning in a low cost consumer robot

In this paper we address the problem of designing a consumer robot capable of manipulating objects typically present in a home. One reason for lack of consumer adoption of manipulator robots is that planning for grasps while negotiating obstacles is costly in terms of time, power, and computational resources. Also, robot arms are generally expensive, thus confining their usage to research labs and the industry. The contribution of this paper is twofold. First we present the hardware design of robot arms resulting in an order of magnitude reduction in cost over the state of the art. Second, we propose an efficient motion planning algorithm which is able to generate motion plans for grasping consistently within 1s everytime using heuristic initialization. We evaluate the algorithm on a challenging task of grasping objects in a cluttered home environment, using a proprietary physical system using two low-cost 7 DoF arms, 3 fingered underactuated hands, and a 1 DoF torso and neck on a holonomic drive base.