Weiwei Wan

TL;DR: In this paper, the authors compared the performance of single-arm and dual-arm regrasp by running the two algorithms thousands of times and found that when the two hands can grasp the object with good clearance, the dual-armed regrasps are better and have higher successful rate than the single-armed grrasps.

TL;DR: In this paper, the authors present an integrated software and hardware system for autonomous mobile robot navigation in uneven and unstructured indoor environments, which incorporates capabilities of perception and navigation, and employs a variable step size Rapidly Exploring Random Trees that could adjust the step size automatically, eliminating tuning step sizes according to environments.

TL;DR: A brief review of affordance research in robotics, with special concentrations on its applications in grasping and manipulation of objects, and shows the current work, which is a cloud database for advanced manipulation intelligence.

TL;DR: An assembly planner which can find an optimal assembly sequence automatically without teaching of the assembly orders and directions by skilled human technicians is proposed, highly expected to improve teachingless robotic manufacturing.

TL;DR: This letter focuses on pick-and-place regrasp, which reorients an object from one placement to another by using a sequence of pick-ups and place-downs, and finds dual-arm regRasp is not necessarily better than single-arm Regrasp: dual- arm regrASP is flexible.