most citedLearning Perceptive Bipedal Locomotion over Irregular Terrain

3 citations · 7 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2024

ManiSkill-ViTac 2025: Challenge on Manipulation Skill Learning With Vision and Tactile Sensing

Chuanyu Li, Renjun Dang, Xiang Li +8

This article introduces the ManiSkill-ViTac Challenge 2025, which focuses on learning contact-rich manipulation skills using both tactile and visual sensing. Expanding upon the 202…

cs.RO20241 cited

VLN-Game: Vision-Language Equilibrium Search for Zero-Shot Semantic Navigation

Bangguo Yu, Yuzhen Liu, Lei Han +3

Following human instructions to explore and search for a specified target in an unfamiliar environment is a crucial skill for mobile service robots. Most of the previous works on o…

cs.RO20241 cited

Lifelong Robot Library Learning: Bootstrapping Composable and Generalizable Skills for Embodied Control with Language Models

Georgios Tziafas, Hamidreza Kasaei

Large Language Models (LLMs) have emerged as a new paradigm for embodied reasoning and control, most recently by generating robot policy code that utilizes a custom library of visi…

cs.RO2024

Harnessing the Synergy between Pushing, Grasping, and Throwing to Enhance Object Manipulation in Cluttered Scenarios

Hamidreza Kasaei, Mohammadreza Kasaei

In this work, we delve into the intricate synergy among non-prehensile actions like pushing, and prehensile actions such as grasping and throwing, within the domain of robotic mani…

cs.RO20231 cited

Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Clutter

Georgios Tziafas, Yucheng Xu, Arushi Goel +3

Robots operating in human-centric environments require the integration of visual grounding and grasping capabilities to effectively manipulate objects based on user instructions. T…

cs.RO20233 cited

Learning Perceptive Bipedal Locomotion over Irregular Terrain

Bart van Marum, Matthia Sabatelli, Hamidreza Kasaei

In this paper we propose a novel bipedal locomotion controller that uses noisy exteroception to traverse a wide variety of terrains. Building on the cutting-edge advancements in at…