7 citations · 16 across the 6 of their papers we have counts for
6 papers
MARVL: Multi-Stage Guidance for Robotic Manipulation via Vision-Language Models
Xunlan Zhou, Xuanlin Chen, Shaowei Zhang +4
Designing dense reward functions is pivotal for efficient robotic Reinforcement Learning (RL). However, most dense rewards rely on manual engineering, which fundamentally limits th…
Iterative Youla-Kucera Loop Shaping For Precision Motion Control
Xiaohai Hu, Jason Laks, Guoxiao Guo +1
This paper presents a numerically robust approach to multi-band disturbance rejection using an iterative Youla-Kucera parameterization technique. The proposed method offers precise…
Learned Slip-Detection-Severity Framework using Tactile Deformation Field Feedback for Robotic Manipulation
Neel Jawale, Navneet Kaur, Amy Santoso +2
Safely handling objects and avoiding slippage are fundamental challenges in robotic manipulation, yet traditional techniques often oversimplify the issue by treating slippage as a…
Context and Geometry Aware Voxel Transformer for Semantic Scene Completion
Zhu Yu, Runmin Zhang, Jiacheng Ying +5
Vision-based Semantic Scene Completion (SSC) has gained much attention due to its widespread applications in various 3D perception tasks. Existing sparse-to-dense approaches typica…
GraphLLM: Boosting Graph Reasoning Ability of Large Language Model
Ziwei Chai, Tianjie Zhang, Liang Wu +4
The advancement of Large Language Models (LLMs) has remarkably pushed the boundaries towards artificial general intelligence (AGI), with their exceptional ability on understanding…
Learning to Detect Slip through Tactile Estimation of the Contact Force Field and its Entropy
Xiaohai Hu, Aparajit Venkatesh, Yusen Wan +5
Detection of slip during object grasping and manipulation plays a vital role in object handling. Existing solutions primarily rely on visual information to devise a strategy for gr…