Physical AI, robots, and autonomous systems
The company turns footage from robots into structured, searchable datasets with a deep learning model.
Everyone talks about AI models, but the real bottleneck might be hardware. According to a recent study by Roots Analysis: AI chip market ...
I've been sitting with a question for a while: what happens when AI agents aren't just tools to be used, but participants in an economy? ...
![[2602.15245] MyoInteract: A Framework for Fast Prototyping of Biomechanical HCI Tasks using Reinforcement Learning](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
MyoInteract is a novel framework that simplifies the prototyping of biomechanical HCI tasks using reinforcement learning, significantly r...
The paper introduces ETGL-DDPG, a novel deep deterministic policy gradient algorithm designed to enhance exploration in reinforcement lea...
This paper explores behavior-targeted attacks on reinforcement learning systems and proposes a novel defense strategy using time-discount...
The Dex4D framework enables task-agnostic dexterous manipulation by using simulation to learn generalist policies that can be applied to ...
The paper presents a framework for humanoid robots to perform dynamic parkour using motion matching and reinforcement learning, enabling ...
The paper presents LoRWeB, a novel approach to visual analogy learning that enhances image manipulation by dynamically selecting and weig...
This article presents a novel real-time conversational assistant that utilizes audio and IMU data to guide users through procedural tasks...
The paper presents Safe-SDL, a framework for ensuring safety in AI-driven Self-Driving Laboratories, addressing the critical 'Syntax-to-S...
The paper presents CLOT, a closed-loop system for humanoid teleoperation that addresses global pose drift, enabling stable and precise lo...
The paper introduces the Agent Communication Protocol (ACP), a framework for secure and efficient agent-to-agent orchestration, addressin...
The paper presents GRACE, an AI agent designed for autonomous experimental design in particle physics, utilizing simulations to optimize ...
The paper presents GlobeDiff, a novel algorithm addressing partial observability in multi-agent systems by utilizing a state diffusion pr...
The paper introduces PERSONA, a novel framework for dynamic personality control in Large Language Models (LLMs) using activation vector a...
This article presents a novel approach using symbolic regression to reconstruct key analytic structures in scattering amplitudes from num...
The paper introduces Experiment Automation Agents (EAA), a system leveraging vision-language models to automate complex microscopy workfl...
This article presents a novel approach using Feasibility-Guided Exploration (FGE) to address parameter-robust avoid problems in reinforce...
This paper presents a novel approach to modeling controlled oscillations using port-Hamiltonian neural networks, emphasizing a second-ord...
This paper presents a model-based primal-dual algorithm for online constrained Markov Decision Processes (CMDPs), achieving near-optimal ...
The International Federation of Robotics (IFR) highlights the rapid integration of AI in robotics, emphasizing its transformative impact ...
Elon Musk's SpaceX and xAI are participating in a Pentagon challenge to develop voice command technology for coordinating drone swarms, w...
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