Technology areas
Planning and decision making
Task decomposition, behavior trees, joint task and motion planning, path and trajectory planning, autonomous navigation, obstacle avoidance, foothold planning, and multi-robot task allocation. This area asks what to do, in what order, and by which route or action. Pose estimation belongs under Perception and localization; trajectory tracking belongs under Motion control.
24 selected · 14 in the last 30 days
甲子光年 · 微信公众号 ·
Peking University's Dong Hao team proposes One Scan is Enough: embodied navigation post-training with a single scan
Dong Hao's team at Peking University has published the paper "One Scan is Enough," which uses a LiDAR-equipped iPhone to scan a target environment once, automatically generates navigation tasks, and uses the reconstructed scene geometry for reinforcement post-training, without needing manual teleoperation demonstrations.
机器之心 · 微信公众号 ·
Fysics AI and Fudan propose Fysiverse-UniWAM unified world-action model, ranks first in both navigation and mobile manipulation across 24 real-robot tests
Fysics AI, together with Fudan University's CITLab, proposed the unified world-action model Fysiverse-UniWAM, which uses a single model to handle autonomous navigation, mobile manipulation, and fixed-workstation dexterous manipulation.
arXiv cs.RO ·
Rendering-Free Event Frame Simulation Accelerates Reinforcement Learning for Autonomous Robot Navigation
The authors propose an analytic event simulator that synthesizes event streams directly from scene geometry and ego-motion without image rendering, generating 64x64 event observations in just 17 microseconds on a single GPU, over 400 times faster than state-of-the-art rendering pipelines. Reinforcement learning training for an event-camera obstacle-avoidance policy based on this simulator converges in under 30 minutes, three orders of magnitude faster than training on rendered events, and transfers zero-shot to ray-traced event simulation in Isaac Sim.
arXiv cs.RO ·
RepresentNav: A Navigation Foundation Model Built on a Self-Constructed Representation Space
The authors propose RepresentNav, a navigation foundation model that uses Representation Residuals, a three-layer transformer, to aggregate full-depth features from multiple vision foundation models and construct a representation space driven by the policy's own objectives.
机器之心 · 微信公众号 ·
Harvard, Berkeley, NVIDIA and others propose RAX, using online exploration scaling to let robots learn skills with zero demonstrations
A research team from Harvard, NVIDIA, Berkeley, MIT and Stanford proposes RAX (Robot Agent eXploration), which connects a general coding agent to robot perception and control interfaces, uses online exploration to write successful decisions into executable programs and accumulate them as reusable skills, while keeping model parameters frozen.
云深处科技 · 微信公众号 ·
DEEP Robotics unveils five embodied brain results: world model DR-WM-1.0, VLA model DR-VLA-2.0, and more
DEEP Robotics has released five research results centered on its self-developed embodied brain, DEEPRobotics-Brain, including the world model DR-WM-1.0, the embodied foundation model DR-VLA-2.0, the embodied agent DR-Agent, the policy optimization framework DR-APO, and the data closed-loop platform DR-Benchmark. The company is also collaborating with seven universities, including MIT, Tsinghua, and Zhejiang University.
中国机器人网 · 微信公众号 ·
Google-owned Intrinsic open-sources robot foundation software platform Intrinsic Core
At ROSCon 2026 in Toronto, Canada, Intrinsic announced that it is open-sourcing the core components of its industrial robotics platform under the Apache 2.0 license and launching Intrinsic Core, a ROS-compatible foundation software platform.
深圳市机器人协会 · 微信公众号 ·
HKU MMLAB releases PhysicalRSI 1.0, tops RoboDojo and sharply cuts token costs
The University of Hong Kong's MMLAB jointly released PhysicalRSI 1.0, a self-evolving embodied intelligence system baseline, achieving a score of 36.27 and an average task success rate of 31.38% on RoboDojo, ranking first.
Rainbow Robotics ·
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.
Rainbow Robotics ·
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.
RoboParty · 微信公众号 ·
RoboParty Lab, Zhejiang University, and Tsinghua AIR release and open-source world model control method INTACT
RoboParty Lab, Zhejiang University, Tsinghua University Institute for AI Industry Research (AIR), and InSpatio jointly released and open-sourced the world model control method INTACT (INtent-To-ACTion).
Robot.com Holdings Inc. ·
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.
Harbin Institute of Technology Robotics ·
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.
Dexterity ·
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.
SIGRobotics · X ·
Earth Rover Mini+ low-cost open-source autonomous mobile robot released, with 7TB of real teleoperation data
Earth Rover Mini+ has been released. It is an open-source autonomous mobile robot priced under $300, has actually driven in multiple cities, comes with over 7TB of real teleoperation data, and supports LeRobot integration.
线性资本 ·
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.
Figure AI ·
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.