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Only First party#Planning and decision-making
  1. Shanghai AI Laboratory - Embodied Intelligence70

    Shanghai AI Lab launches Sage·LabOS laboratory operating system

    Shanghai AI Lab has launched its laboratory operating system Sage·LabOS, which uses Sage SCP-Lab as a unified interface and the Sage physical world model W0 to drive robots in completing experimental operations, connecting heterogeneous devices for autonomous execution and data return. The system has four core capabilities: capability discovery, task orchestration, execution scheduling, and data feedback. In a lipid nanoparticle (LNP) formulation optimization task at Lingang Laboratory, it completed five rounds of dry-wet closed-loop iterations, automatically synthesizing and validating 335 formulations, with encapsulation efficiency rising from 67% to 98%.

    Why it matters: The source provides the four core capabilities of the autonomous laboratory operating system and measured dry-wet closed-loop data from LNP formulation optimization, showing how robots can be integrated into scientific research workflows.

  1. Rainbow Robotics61

    Samsung unveils robot commercialization roadmap and Metro-WM world model at Samsung AI Forum 2026

    At Samsung AI Forum 2026, held at its Seoul headquarters, Samsung Electronics unveiled a robot commercialization roadmap led by its newly established RX (Robot eXperience) Business Promotion Office, combining robot foundation model (RFM) and world model technology to first advance automation at its own more than 100 factories and more than 100 production lines, before entering the home assistant robot market.

    Why it matters: The article presents the per-unit cost breakdown of humanoid robots and the success-rate threshold for factory scenarios, which can be used to compare and understand differences in manufacturers' commercialization paths.

  2. Rainbow Robotics63

    Samsung unveils robot commercialization roadmap: factory automation first, then the home

    At the Samsung AI Forum 2026, Samsung announced its robot commercialization roadmap. Centered on its newly established RX (Robot eXperience) business promotion office, the plan is to first advance automation at its more than 100 factories and more than 100 production lines, then enter the home assistant robot market.

    Why it matters: The article lays out the cost math for a humanoid robot at about $100,000 per unit and a three-layer behavior stack, helping readers understand why Samsung puts factory automation ahead of home robots.

  1. Robot.com Holdings Inc.68

    Robot.com releases R-KNav 10,000-hour sidewalk navigation dataset and launches FoMo Challenge

    Robot.com has released the R-KNav dataset and launched the FoMo Challenge, inviting the community to train visual navigation models on real data from its R-kiwi sidewalk delivery robot fleet and to evaluate them in controlled tests on physical robots.

    Why it matters: The data comes from a long-running commercial delivery fleet rather than simulation, and the KPI criteria for physical-robot evaluation have been published, making it possible to assess the reusability of real-street navigation data.

  2. Harbin Institute of Technology Robotics62

    HIT's Zhu Yanhe Team Publishes Paper on Cooperative Reconfiguration for Self-Repair in Modular Robots

    Professor Zhu Yanhe's team at Harbin Institute of Technology (HIT) published a paper in the International Journal of Extreme Manufacturing (IJEM), proposing an autonomous fault-tolerant repair strategy for modular robots based on cooperative reconfiguration, which restores joint fault damage by changing morphology without backup module replacement. The method combines topological description and kinematic self-modeling, particle swarm optimization to search for target configurations, and an improved RRT cooperative reconfiguration algorithm. In experiments, the fault-tolerance upper limit was 7 times higher than that of fixed-configuration redundancy methods. HIT is the sole completing institution, and doctoral student Qi Jian is the first author.

    Why it matters: The paper presents a cooperative reconfiguration fault-tolerance strategy that requires no backup modules and data showing a 7-fold increase in the fault-tolerance upper limit, allowing readers to understand a concrete implementation path for self-repair in robot swarms under extreme environments.

  1. Dexterity60

    Dexterity details evaluation methods and production metrics for the Foresight packing agent

    Dexterity published an article introducing system evaluation and production measurement for the Foresight packing agent. On the planning side, it was tested on four real warehouse box-type distributions, with density of 0.65–0.77 and stability of 99.7–100%, and distribution-free order statistics were used to give 95% confidence intervals; the article also found that randomly shuffling the box sequence causes local variance to collapse by about 1.4 times, making evaluation overly optimistic.

    Why it matters: The original article fully discloses the evaluation method for the packing agent, including distribution-free confidence intervals and the evaluation bias caused by random shuffling; the method can be transferred to similar systems.

  1. 线性资本72

    Bot Auto completes first fully driverless truck real-world road test

    Linear Capital portfolio company Bot Auto announced it has completed its first real-world road test in which the truck truly performed all operations on its own, with no one in the driver's seat, the back seat, or at a remote-control terminal, and no escort vehicle. During the test, the truck on a Texas highway handled scenarios including avoidance, detouring, merging, and responding to the appearance of a fire truck. The vehicle is equipped with 15 cameras, 8 lidars, and 3 millimeter-wave radars, with redundancy in perception, computing, actuation, and power supply; after the primary server is shut down it can switch to a backup server, and if the backup is also shut down, the vehicle control unit takes over to pull over and stop.

    Why it matters: The article sorts out the differences between Bot Auto's truly driverless road test and earlier modes with safety drivers, escort vehicles, and remote control, helping readers understand the differences in its technical approach.

  2. Figure AI72

    Figure launches Project Go-Big: Helix learns navigation zero-shot from human first-person video alone

    Figure announced two advances in Project Go-Big: a partnership with Brookfield to build a large-scale humanoid pretraining dataset, with Brookfield holding over 100,000 homes, 500 million square feet of commercial office space, and 160 million square feet of logistics space; and Helix, after training on 100% first-person human video, responding to natural-language commands such as "go to the fridge" without any robot demonstrations, navigating cluttered real home environments.

    Why it matters: The original gives the training method by which Helix learned navigation using only human video and the scale details of the Brookfield data partnership, offering a view of actual progress on the humanoid pretraining data approach.

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