Bringing Robotics AI to Embedded Platforms: Dataset Recording, VLA Fine‑Tuning, and On‑Device Optimizations

Embedded Arena: Iterative Optimization via Hardware Feedback

arXiv:2606. 16190v1 Announce Type: cross Abstract: Embedded devices from wildlife monitoring stations to clinical wearables require local AI inference due to latency, communication, or privacy constraints.

Hardware-Accelerated Instance Segmentation for Resource-Constrained Space Robotics with Criticality Analysis

The paper presents a hardware‑accelerated instance segmentation framework tailored for resource‑constrained lunar robotics, addressing low‑light perception, limited compute, and radiation‑induced hardware faults. It introduces Activation Variance Informative Sampling (AVIS), a label‑free calibration method that selects samples based on activation variance, and deploys a YOLO‑based model on a Deep Learning Processor Unit with architectural tweaks to reduce CPU fallback and ensure bounded latency. A software‑level criticality analysis estimates fault exposure, guiding mitigation that reduces global criticality by 31.7%, while AVIS with bias correction recovers 69.8% of quantization‑induced accuracy loss at 309 ms latency and 5.7 W power consumption.

A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI

arXiv:2505. 01458v2 Announce Type: replace-cross Abstract: Navigation and manipulation are core capabilities in Embodied AI, but training agents to perform them directly in the real world is costly, time-consuming, and unsafe.

Gemini Robotics On-Device brings AI to local robotic devices

We’re introducing an efficient, on-device robotics model with general-purpose dexterity and fast task adaptation.

LeRobot Community Datasets: The “ImageNet” of Robotics — When and How?

Creating Impactful Autonomous Driving Datasets: A Strategic Guide from Research Gap to Benchmark

arXiv:2607. 00710v1 Announce Type: cross Abstract: Well-designed autonomous driving datasets have fundamentally shaped research progress, yet existing literature primarily describes what datasets contain rather than how to strategically design impactful ones.