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? ...
![[2602.16187] SIT-LMPC: Safe Information-Theoretic Learning Model Predictive Control for Iterative Tasks](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The paper presents SIT-LMPC, a novel algorithm for safe information-theoretic learning model predictive control tailored for robots perfo...
The paper introduces DreamZero, a World Action Model (WAM) that enhances zero-shot policy learning for robotic tasks by predicting future...
The paper presents ScenicRules, a benchmark for evaluating autonomous driving systems that balances multiple objectives like safety and e...
This article presents a novel approach to UAV search operations in post-disaster scenarios, addressing the challenges posed by Non-Line-o...
This paper presents NOMAD, a novel approach for training autonomous vehicles to navigate new cities without relying on human driving demo...
The paper introduces ODYN, a novel non-interior-point method for quadratic programming, designed for efficiency in robotics and AI applic...
The paper presents MARVL, a novel approach for robotic manipulation that utilizes Vision-Language Models (VLMs) to enhance task performan...
This paper presents a hybrid model predictive control approach using physics-informed neural networks for improved satellite attitude con...
The paper presents EarthSpatialBench, a benchmark designed to evaluate spatial reasoning capabilities of multimodal large language models...
The paper presents Resp-Agent, an innovative agent-based system for generating multimodal respiratory sounds and diagnosing diseases, add...
FUTURE-VLA introduces a unified architecture for real-time trajectory forecasting in robotics, enhancing spatiotemporal reasoning and pre...
The paper presents Fly0, a novel framework that separates semantic grounding from geometric planning to enhance zero-shot aerial navigati...
This paper presents a novel approach to test-time adaptation (TTA) for tactile-vision-language (TVL) models, addressing challenges posed ...
The paper presents EdgeNav-QE, a framework that combines QLoRA quantization and dynamic early exit mechanisms to enhance LAM-based naviga...
The paper presents CAFE, a novel framework for automated feature engineering that combines causal discovery with multi-agent reinforcemen...
The paper presents the Factored Latent Action Model (FLAM), a new framework for modeling complex dynamics in action-free video generation...
The paper introduces GPSBench, a dataset designed to evaluate the geospatial reasoning capabilities of large language models (LLMs) using...
This paper explores optimization instability in autonomous workflows for clinical symptom detection, revealing critical failure modes and...
This paper presents a Koopman-Bayesian framework to enhance haptic surgical simulations, improving realism through nonlinear dynamics and...
This Reddit thread discusses the challenges of developing evaluation metrics for a generative model in scientific research, particularly ...
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