This post demonstrates how to train robot policies for the Unitree H1 humanoid using NVIDIA Isaac Lab on Amazon SageMaker AI. It explores two compute options: Amazon SageMaker HyperPod and Amazon SageMaker Training Jobs.
This paper introduces CARVE and CARVE-Q, architectures for certified interactive driving repair following a vetoed maneuver. It focuses on ensuring repairs adhere to hard rules and responsibilities, addressing the algorithmic bottleneck of multi-owner repair with a quantum-proposed solution.
This content focuses on the advancement and future development of robotics technology within Europe. It explores strategies and initiatives aimed at strengthening Europe's position in the global robotics landscape.
This content explores the limitations of traditional planning and pure neural AI approaches for autonomous rover navigation in planetary geology survey missions with extreme data sparsity. The author found neuro-symbolic reasoning to be a hybrid solution, combining neural network pattern recognition with logical rigor.
This content explores the Gemma Playground, using a 'Robot Duck' as an application example. The focus is on demonstrating the capabilities of the Gemma model in a practical scenario.
Dan from Elodin has released an open-source, real-time capable flight software simulation harness for AI Grand Prix contestants. The tool, built to match competition constraints, runs against real Betaflight and features direct camera sensor generation within the simulation loop, utilizing the Rust Bevy game engine.
Uma pessoa está desenvolvendo um robô companheiro de IA offline para seu marido tetraplégico, buscando reduzir o isolamento. O protótipo atual usa Mistral-7B-Instruct em um ThinkPad com 8GB de RAM para conversação e faster-whisper em um Jetson Nano para reconhecimento de fala, e a autora busca conselhos de otimização.
This article provides a technical breakdown of Visual-Language-Action (VLA) models, explaining how they map vision and language inputs into robot actions. It delves into current action-decoding approaches like tokenized autoregressive actions, diffusion-based action heads, and flow-matching policies.
![How Visual-Language-Action (VLA) Models Work [D]](/cdn-cgi/image/width=3840,quality=75,format=webp/https://external-preview.redd.it/fBpt1C8zS6YDW2Lp0_fnNCU2C0Dw1W3tzt7P4g39SHw.jpeg?width=640&crop=smart&auto=webp&s=d9f046e9b38c478cf671d18df1b23a42fd1613bd)
The content describes a war robots project where the Qwen3 model generates code to control the robots. The author reports a significant improvement in AI execution after transitioning from Ollama to llama.cpp.
Sony AI has developed Ace, the first ping-pong robot capable of beating top-ranked human players under official rules. This achievement highlights AI's progress in physical games, which pose greater challenges than purely digital ones like Chess or Go.
This work explores self-supervised learning for stereo matching, focusing on a system with a self-improving ability. The research aims to enhance the accuracy and robustness of computer vision algorithms in depth estimation.
This research proposes Lie group embedded dynamical neural networks (LieEDNN) and associated learning algorithms for achieving learnable and stable dynamics on underlying manifolds. It leverages Lie groups' powerful representation capabilities to address challenges in neural network interactions and nonlinear representation spaces, with applications in robotics, graphics, and control.
This content explores the rise of open-source embodied AI, which democratizes the development of intelligent robots interacting with the physical world. It provides key takeaways for contributing, including engaging with platforms like ROS and Gazebo, developing programming and AI/ML skills, and actively participating in projects.
DEEPX and Hyundai are partnering to build generative AI robots using DEEPX's new DX-M2 edge AI chip, shifting generative AI workloads from the cloud to on-device. This move promises lower latency, reduced power consumption, and real-time decision-making, confirming a major trend of generative AI moving to the edge.
Nvidia unveiled physical AI agent skills and a 32B-parameter Visual Language Action (VLA) model, Alpamayo 2 Super, at CVPR to streamline autonomous vehicle and robotics research. These innovations address the fragmented tooling bottleneck by automating tasks like scene reconstruction and synthetic data generation.
Jim Fan of Nvidia's robotics group proposes that robotics is entering its "end game" and will follow the same four-stage trajectory as large language models. He asserts that "robotics is entering its end game, and the playbook is already written" by LLMs.
GIST introduces a multimodal knowledge extraction pipeline for spatial grounding in complex environments, transforming mobile point clouds into semantically annotated navigation topologies. It distills scenes into 2D occupancy maps, extracts topological layouts, and overlays a lightweight semantic layer to aid embodied AI and humans.
This article details a personal journey in AI for soft robotics, inspired by a catastrophic "silent failure" in a bio-inspired gripper during a simulated mission. It highlights the challenge of using AI to reason about physical degradation in novel environments, proposing Physics-Augmented Diffusion Modeling for maintenance in critical recovery windows.
The text introduces the Qiushi Discovery Engine, an LLM-based agentic system for autonomous scientific discovery on a real optical platform. It demonstrates end-to-end discovery by combining nonlinear research phases, Meta-Trace memory, and a dual-layer architecture, successfully reproducing a published experiment.
VIOLA presents a novel approach for vision-based manipulation tasks, leveraging imitation learning to teach robots complex actions. It incorporates Object ProposalPriors to enhance the efficiency and robustness of learning, enabling more effective interaction with objects.