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Sim-to-real Latest coverage

Robotics coverage relating to sim-to-real.

549 selected reportsLast 30 days 427 recordsAll coverage 2,461 records

updated

Signal archive — Page 28

2026-06-30Tue541–549 records
  1. Apptronik — Official announcements68

    Welcome to Robot Park: Where Apptronik’s Apollo Goes to Work Training the Next Generation of Humanoid Robot Intelligence

    Apptronik announced the opening of its expanded Robot Park in Austin, Texas, and the launch of Apollo 2, a modular humanoid robot platform. The facility and robot are part of a global network, enabling real-world data collection and training for embodied AI models. Apollo 2 supports both bipedal and wheeled configurations, with data used to refine Gemini Robotics models for commercial deployment.

2026-06-09Tue
  1. Michigan Robotics — Research news72

    An earthworm-inspired robot to inspect complex pipelines

    University of Michigan researchers have developed SPPIRO, an untethered soft robot inspired by earthworms, capable of navigating complex pipelines with varying diameters and sharp turns. Equipped with Kresling origami actuators, onboard sensors, and a self-mapping system, SPPIRO can inspect pipelines at speeds up to 9.5 mm/s vertically and 6.5 mm/s horizontally, outperforming existing untethered soft in-pipe robots. The robot uses liquid-metal-based sensors and an onboard camera to detect defects in enclosed pipes, though challenges remain in maintaining stability and accuracy in certain conditions.

2026-04-01Wed
  1. Sanctuary AI — Research and announcements72

    Sanctuary AI Demonstrates Zero-Shot In-Hand Manipulation on Hydraulic Hand

    Sanctuary AI has demonstrated zero-shot in-hand manipulation using their proprietary hydraulic hand, autonomously reorienting a lettered cube ten times without dropping it. This showcases successful simulation-to-reality transfer, overcoming challenges in simulating dexterous hands and highlighting the company's advanced robotic hardware and policy training capabilities.

2026-03-03Tue
  1. Dexterity — Blog65

    Introducing Foresight

    Dexterity introduces Foresight, a world model that enables robots to reason about the physical world, predict outcomes, and act confidently in real environments. Trained on over 100 million autonomous actions in production, Foresight is designed for interpretability, safety, and performance, with capabilities like predictive branching and pragmatic decision-making. It addresses complex tasks like spatial packing and includes a game and API challenge for further exploration.

2025-11-13Thu
  1. Dexterity — Blog68

    Transactable World Models

    Dexterity introduces 'Transactable World Models' as a foundational component for Physical AI, emphasizing interpretability, physics integration, and real-time consistency. The approach treats world models as operators rather than data stores, enabling multi-agent coordination and robust manipulation in complex environments. This contrasts with traditional world models that focus on data compression and replay, lacking causal reasoning and physical grounding.

2025-10-29Wed
  1. Hugging Face — Robotics65

    Building a Healthcare Robot from Simulation to Deployment with NVIDIA Isaac

    This hands-on tutorial walks through the process of collecting data, training policies, and deploying autonomous medical robotics workflows on real hardware using NVIDIA Isaac for Healthcare. It introduces the SO-ARM starter workflow, which enables developers to build and validate surgical assistant robots from simulation to deployment.

2025-10-24Fri
2025-06-03Tue
  1. Hugging Face — Robotics85

    SmolVLA: Efficient Vision-Language-Action Model trained on Lerobot Community Data

    Hugging Face introduces SmolVLA, a 450M parameter open-source Vision-Language-Action model for robotics, trained on community-shared datasets. It outperforms larger models in simulation and real-world tasks, supports asynchronous inference for faster response, and is designed for deployment on consumer hardware.

2025-06-01Sun
  1. LeRobot — Model repository updates68

    SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics

    SmolVLA is a compact, efficient Vision-Language-Action (VLA) model designed for affordable robotics, trainable on a single GPU and deployable on consumer hardware. It matches the performance of larger VLAs through community-driven data, with a reference implementation and training instructions provided.

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