Grasping is the process of picking up an object by applying forces and torques at a set of
contacts. Recent advances in deep learning methods have allowed rapid progress in robotic …

Promising results have been achieved recently in category-level manipulation that
generalizes across object instances. Nevertheless, it often requires expensive real-world …

We propose a system for rearranging objects in a scene to achieve a desired object-scene
placing relationship, such as a book inserted in an open slot of a bookshelf. The pipeline …

We present a framework for specifying tasks involving spatial relations between objects
using only 5-10 demonstrations and then executing such tasks given point cloud …

Transporter Net is a recently proposed framework for pick and place that is able to learn
good manipulation policies from a very few expert demonstrations. A key reason why …

Existing robotic systems have a tension between generality and precision. Deployed
solutions for robotic manipulation tend to fall into the paradigm of one robot solving a single …

We present a strategy for designing and building very general robot manipulation systems
using a general-purpose task-and-motion planner with both engineered and learned …

Robotic pick and place tasks are symmetric under translations and rotations of both the
object to be picked and the desired place pose. For example, if the pick object is rotated or …

We introduce a new task, called Class Incremental Robotic Pick-and-Place (CIRPAP), which
calls for the capacity to learn to pick and place new categories of objects while retaining the …

为解决基于全球导航卫星系统(global navigation satellite system, GNSS) 的农业机器人和自动
驾驶农机在机库, 大棚等卫星信号弱或无环境下定位精度低甚至无法定位的问题 …