Berkeley AUTOLAB proposes the STITCH 2.0 suturing robot system, with seven improvements including improved EKF needle pose estimation, new thread untangling methods, and an automated 3D suture alignment algorithm.
Figure AI has released its third-generation humanoid robot, Figure 03, redesigned from the ground up for the Helix VLA model, the home, and large-scale mass production, covering both software and hardware.
Why it matters: The official announcement fully explains the new-generation humanoid robot's perception, touch sensing, home-safety design, and mass-production plans, so readers can understand its hardware changes and production capacity targets.
KEENON Robotics has officially released KOM 2.0 (KEENON Operator Model 2.0), which it calls the world's first VLA (vision-language-action) model for the service industry. The model uses a dual-system architecture with the K-Mind thinking system and the K-Act action system, is trained on hundreds of millions of real service interaction data points, and supports millisecond-level real-time decision-making.
The paper "Generative Visual Foresight Meets Task-Agnostic Pose Estimation in Robotic Table-top Manipulation," a collaboration between SUSTech CLEAR Lab, LimX Dynamics, and the University of Hong Kong, has been accepted to CoRL 2025.
Why it matters: This research presents a concrete technical approach and experimental figures for learning manipulation from human video, helping readers understand the feasibility of training robot manipulation with video data.
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.
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.
As of February 2025, Livox has delivered a cumulative 100,000 Mid-360 LiDAR units to Dreame. Under a three-year strategic partnership, the plan is to deliver more than one million units over the next three years. The sensors will be installed in Dreame's full lineup of robotic lawn mowers, covering more than 100 countries and regions, including high-end markets in Europe and North America.
Field AI Research Institute (FAIRI) is collaborating with NVIDIA to study robotic embodied question answering (EQ&A) in dynamic environments. The team uses the NVIDIA Omniverse platform, Isaac Sim, Omniverse Replicator, and the USD Search API to build physically accurate 3D office scenes, simulate changes in the environment over time, and plans to open-source this long-term embodied question answering dataset.
XGRIDS and DEEP Robotics recently reached a strategic partnership, combining XGRIDS' high-precision 3D scanning and modeling equipment with the environmental interaction capabilities of DEEP Robotics' intelligent robot dogs to create an intelligent modeling solution. The system targets scenarios such as tunnel and underground space exploration, emergency rescue, and building and campus surveying, supports 4G, 5G, and ad hoc network modes, and can transmit data in real time in areas without signal coverage.