The article presents a study on improving slip detection in robotic manipulation. It focuses on the macroscopic deformation of the fingertip’s soft structure and its role as a vibration medium…
Continue readingThe paper introduces a new assistance algorithm and interface for robot teleoperation, allowing operators to explicitly communicate a manipulation goal. This is done by pointing the end-effector, with optimization and…
Continue readingThe article introduces SLIM, a multi-critic learning approach for skill discovery, particularly focusing on robotic manipulation. It addresses the limitations of mutual information maximization in producing useful manipulation behaviors. The…
Continue readingThe article discusses a system that uses tactile information to estimate the rotation angle of a grasped object when slippage occurs during robotic manipulation tasks. The system uses a neural…
Continue readingThe research presents ManipLLM, a system that improves robotic manipulation by leveraging Multimodal Large Language Models (MLLMs). Traditional learning-based robot manipulation often struggles with generalizability, especially with extensive categories. ManipLLM…
Continue readingThis paper presents a new approach to robotic manipulation, focusing on bin-picking. It leverages category-agnostic instance segmentation and simulation-based training for real-world application. The method can handle objects regardless of…
Continue readingDiffusion Reward is a novel framework that learns rewards from expert videos for reinforcement learning tasks. The system leverages conditional video diffusion models to solve complex visual reinforcement learning problems….
Continue readingThe article discusses the development of a versatile, cost-effective robotic system named Dobb E which can learn and perform tasks in a home environment. The system learns new tasks in…
Continue readingThe paper presents a constraint-aware policy for compliant robotic manipulation, particularly in physically-constrained environments such as household operations. The policy, developed using reinforcement learning, is designed to adjust to the…
Continue readingThe article discusses the challenges of applying robotic manipulation in varied scenarios due to the limitations of control-based approaches and inefficiency of existing learning methods. To address these, the authors…
Continue readingLooks like you're using an ad blocker. Please support us by disabling these ad blocker.
