activity
20192026
most citedL3MVN: Leveraging Large Language Models for Visual Target Navigation

100 citations · 210 across the 38 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.RO2025

Parse-Augment-Distill: Learning Generalizable Bimanual Visuomotor Policies from Single Human Video

Georgios Tziafas, Jiayun Zhang, Hamidreza Kasaei

Learning visuomotor policies from expert demonstrations is an important frontier in modern robotics research, however, most popular methods require copious efforts for collecting t…

cs.RO2025

Fast Trajectory Planner with a Reinforcement Learning-based Controller for Robotic Manipulators

Yongliang Wang, Hamidreza Kasaei

Generating obstacle-free trajectories for robotic manipulators in unstructured and cluttered environments remains a significant challenge. Existing motion planning methods often re…

cs.CV2025

Asymmetric Dual Self-Distillation for 3D Self-Supervised Representation Learning

Remco F. Leijenaar, Hamidreza Kasaei

Learning semantically meaningful representations from unstructured 3D point clouds remains a central challenge in computer vision, especially in the absence of large-scale labeled…

cs.RO2025

Learning Dual-Arm Coordination for Grasping Large Flat Objects

Yongliang Wang, Hamidreza Kasaei

Grasping large flat objects, such as books or keyboards lying horizontally, presents significant challenges for single-arm robotic systems, often requiring extra actions like pushi…

cs.CV2025

LM-MCVT: A Lightweight Multi-modal Multi-view Convolutional-Vision Transformer Approach for 3D Object Recognition

Songsong Xiong, Hamidreza Kasaei

In human-centered environments such as restaurants, homes, and warehouses, robots often face challenges in accurately recognizing 3D objects. These challenges stem from the complex…

cs.RO2025

Enhanced View Planning for Robotic Harvesting: Tackling Occlusions with Imitation Learning

Lun Li, Hamidreza Kasaei

In agricultural automation, inherent occlusion presents a major challenge for robotic harvesting. We propose a novel imitation learning-based viewpoint planning approach to activel…