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Robótica & RL

Papers, modelos e datasets em alta no Hugging Face, além do blog oficial — com leitura editorial em português.

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Prime Intellect Releases prime-rl 0.6.0 to Train Trillion-Parameter MoE Models on Agentic RL Workloads
Blog Robótica & RL

Prime Intellect Releases prime-rl 0.6.0 to Train Trillion-Parameter MoE Models on Agentic RL Workloads

Prime Intellect has released prime-rl 0.6.0, an open framework for asynchronous reinforcement learning on trillion-parameter Mixture-of-Experts models. It trained GLM-5 on SWE tasks at up to 131k sequence length, with sub-5-minute step times and 256 rollouts, on 28 H200 nodes. This breakdown covers the inference and training optimizations behind those numbers — FP8 inference, Wide Expert Parallelism, prefill/decode disaggregation, router replay, and 3-D parallelism (FSDP, EP, CP). The post Pri...

23.06.2026
Blog Robótica & RL

Learning Control as Enabling Layer for Embodied Intelligence Research explored with Soft Robotic Swimming in diverse Flow Speeds

arXiv:2606.20660v1 Announce Type: new Abstract: Soft robots are valuable robophysical platforms for studying body-caudal undulatory locomotion, but their compliant bodies are difficult to control precisely under changing hydrodynamic loading. Conventional proportional-integral-derivative (PID) feedback stabilizes periodic undulation in static water, but can accumulate flow-dependent tracking delay and increasing inter-trial variability when environmental flow becomes non-trivial. Here, we evalua...

23.06.2026
Blog Robótica & RL

An Efficient and Effective Architecture for Large-Scale Traffic Prediction via Geometry-Adaptive Square Partitioning

arXiv:2606.21072v1 Announce Type: new Abstract: Traffic prediction is a core task in intelligent transportation systems and urban-scale decision making. Despite the effectiveness of mainstream neural-network based methods, their deployment in real-world settings with thousands of traffic sensors is jeopardized severely by their poor computational scalability. To address this, the community has attempted to incorporate spatial database partitioning techniques (e.g., Grid, Quadtree, and K-D Tree) ...

23.06.2026
Blog Robótica & RL

Coupled Routing and Configuration Optimization for Multi-Viewpoint Robotic Inspection

arXiv:2606.20739v1 Announce Type: new Abstract: We present a unified framework that turns a set of 6-DoF inspection viewpoints into a time-optimal, collision-free route for a 9-DoF robotic system. Unlike modular pipelines that fix a single inverse-kinematics (IK) configuration per viewpoint, build an all-pairs travel-time map, and then route, our method jointly optimizes the visiting order and the per-viewpoint configuration in a single global search. The three-dimensional self-motion manifold o...

23.06.2026
Blog Robótica & RL

A Digital Twin Framework for Traffic-Aware UAV Pavement Monitoring without Lane Closure

arXiv:2606.20742v1 Announce Type: new Abstract: UAV-based pavement inspection can reduce the cost and risk of road-surface monitoring, but real-world deployment remains difficult when traffic, pedestrians, and temporary occlusions affect the visibility of defects. This paper presents a Unity-based digital twin framework for traffic-aware UAV pavement monitoring without lane closure. The proposed environment integrates procedurally generated road defects, dynamic vehicles and pedestrians, autonom...

23.06.2026
Blog Robótica & RL

Structure-Aware Graph Multi-Task Learning for Dynamic Sparse OD Demand Prediction

arXiv:2606.21022v1 Announce Type: new Abstract: Origin-Destination (OD) demand prediction is fundamental to intelligent transportation systems, yet real-world OD flows are often dynamically sparse, long-tailed, and characterized by heterogeneous zero-flow patterns. These properties make it difficult to distinguish whether an OD connection is active from how much demand it generates once activated. Many existing methods primarily treat OD prediction as a single flow regression task, which limits ...

23.06.2026
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