The paper discusses the use of imitation learning for controlling quadrotors with multiple waypoint constraints. The authors propose a neural network called WN&CNets (waypoint-constrained navigation and control network) to generate…
Continue readingThis paper presents a method to improve imitation learning in robots by focusing on data with a relatively low correlation to the desired output. The proposed approach inputs such data…
Continue readingThe research introduces a low-cost mobile manipulation system, Mobile ALOHA, that is bimanual and supports whole-body teleoperation. This system enhances the ALOHA system with a mobile base and a whole-body…
Continue readingThe paper presents a study on object grasping in robotics using bilateral control-based imitation learning and a cross-structure hand. This technique allows robots to mimic human force skills and adapt…
Continue readingThe article explores the use of optical tactile sensors, specifically a see-through-your-skin (STS) variant, in robotic manipulation. This type of sensor combines visual and tactile modes, which can be leveraged…
Continue readingThe paper presents RoboFlamingo, a novel framework for robot manipulation using vision-language models (VLMs). The researchers used pre-trained VLMs and fine-tuned them on robotics data, resulting in a system that…
Continue readingThe paper presents a method called Reinforcing Traffic Rules (RTR) for simulating realistic traffic scenarios, which is essential for the development of self-driving software. Traditional imitation learning methods often result…
Continue readingThe article discusses the challenges of Offline Imitation Learning (IL) in learning visuomotor skills, particularly high-precision manipulation tasks. The authors introduce the Constrained-Context Conditional Diffusion Model (C3DM), designed to balance…
Continue readingThis article presents a new AI learning framework, Communication-Efficient Interactive Learning (CEIL), which promotes progressively efficient communication. Traditional frameworks like imitation learning and reinforcement learning only support low-level, inefficient communication….
Continue readingThe paper presents a novel approach to imitation learning (IL) in robotics called CasIL (Cognition-Action-based Skill Imitation Learning). CasIL introduces human cognitive priors into a dual cognition-action architecture, enabling robots…
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