3 accepted papers
Grasping a wide range of novel objects in densely cluttered scenes is difficult due to irregular shapes of objects and the uncertainty in sensing. In this paper, a novel vacuum cup grasping method, based on uncertainty modeling of perception data and grasp geometric heuristics, is proposed to grasp…
In this paper, we propose a novel grasp pipeline based on contact point detection on the truncated signed distance function (TSDF) volume to achieve closed-loop 7-degree-of-freedom (7-DoF) grasping on cluttered environments. The key aspects of our method are that 1) the proposed pipeline exploits th…
Data-driven approach for grasping shows significant advance recently. But these approaches usually require much training data. To increase the efficiency of grasping data collection, this paper presents a novel grasp training system including the whole pipeline from data collection to model inferenc…