Category
1,589 papers
Adversarial Calibration Attack (ACA), the first physical attack against camera-LiDAR online calibration, is presented and demonstrated that online calibration is a practical and safety-critical attack surface for AVs.
This work proposes a unified autoregressive diffusion-based graph generative model that jointly learns structure and features, constructing complete 3DSGs bottom-up from observed vertical planes across arbitrary hierarchy depths, and proposes an adaptation of the Fused Gromov--Wasserstein distance for principled graph-...
Control performance guarantee is first established by deriving tracking error bound for the in-network control architecture, while accounting for computational delays, and an explicit expression of the proposed event-trigger condition for exponentially stabilizable systems is derived.
This work proposes an asynchronous cooperative learning strategy that explicitly accounts for prediction accuracy, query point variations and delay effects, and a distributed control law based on an adjoint MAS is developed to ensure the desired control performance.
Reach audiences
Advertise in front of researchers, engineers, and readers.
This work proposes a fully distributed continuous-time algorithm for shared linear equality constraints that converges without multiplier exchange and reaches any GNE, reducing communication overhead and improving privacy.
The proposed PathBridger is a hierarchical offline GCRL method that explicitly connects subgoal selection to short-horizon execution, and constructs a state-space bridge toward the selected intermediate endpoint and decodes it into a short executable action chunk using an inverse dynamics model.
While standard end-to-end baselines struggle to complete these logically demanding tasks, ACE achieves a 50% success rate in equation formation and a 70% success rate in constraint retrieval, demonstrating that explicit workflow reasoning and mask-mediated control offer a robust, practical route toward adaptable roboti...
Experiments on real deformable-object manipulation sequences show that PhysCoRe outperforms state-of-the-art baselines in prediction accuracy, and that its predicted confidence forms a reliable distribution across the object's geometry, providing a natural signal for future confidence-guided exploration.
Agentic Real2Sim is introduced, a framework for generalized physical world modeling with vision-language agents, converting a real-world recording of object-robot interaction into a simulatable episodic twin which preserves observations, geometries, robot interactions, and object states.
XS-VLA is introduced, a lightweight framework that teaches tiny VLA policies "where to look" and "how to move" without increasing deployment-time model cost and shows that explicit spatial grounding and latent action-structure learning can make tiny VLA models effective for robotic manipulation.
CLAP (Causal Language-Action Prediction), which prepends each numeric action sequence with a natural-language action description, causally conditioning precise action-token prediction on a language-action plan without modifying the backbone architecture, enabling controlled analysis of VLM-to-VLA capability transfer.
This paper introduces hint, a method for guiding short-horizon policies toward satisfying complex LTL specifications at inference time using hierarchical world models, and shows that hint$^2$ can handle complex instructions on a real UR5e manipulator.
A Blog post by Ai2 on Hugging Face
A new system identifies and corrects unreliable object descriptions stored in a robot’s memory, improving the robot’s ability to interact with its environment.
Discover Gemini 4 Argon for robotics: leading the ERQA benchmark with physical reasoning, zero-shot control, Real2Sim, and agentic workflows.
Robots are getting smarter, but how can their hardware match that growth? New Microsoft Research findings show that moving AI inference beyond the robot can improve task success, boost efficiency, and support more advanced physical AI workloads. The post Offloaded inference for real-world physical AI robotics appeared first on Microsoft Research.
A Blog post by Amazon on Hugging Face
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
