4 papers · 1 filter
HDCNet: A Hybrid Depth Completion Network for Grasping Transparent and Reflective Objects
Guanghu Xie, Mingxu Li, Songwei Wu +4
Depth perception of transparent and reflective objects has long been a critical challenge in robotic manipulation.Conventional depth sensors often fail to provide reliable measurem…
DCIRNet: Depth Completion with Iterative Refinement for Dexterous Grasping of Transparent and Reflective Objects
Guanghu Xie, Zhiduo Jiang, Yonglong Zhang +4
Transparent and reflective objects in everyday environments pose significant challenges for depth sensors due to their unique visual properties, such as specular reflections and li…
Learning Perceptive Humanoid Locomotion over Challenging Terrain
Wandong Sun, Baoshi Cao, Long Chen +4
Humanoid robots are engineered to navigate terrains akin to those encountered by humans, which necessitates human-like locomotion and perceptual abilities. Currently, the most reli…
Neural-Network-Driven Reward Prediction as a Heuristic: Advancing Q-Learning for Mobile Robot Path Planning
Yiming Ji, Kaijie Yun, Yang Liu +2
Q-learning is a widely used reinforcement learning technique for solving path planning problems. It primarily involves the interaction between an agent and its environment, enablin…