Huaner Technology offers four 18-DOF hexapod robots—miniHexa, SpiderPi, JetHexa, and ROSpider—for different learning needs, all supporting 360° omnidirectional movement and inverse kinematics algorithm learning.
Huaner Technology compares three entry-level robot cars: miniAuto Pro, TurboPi, and ClawPi. The miniAuto Pro is based on ESP32 and supports Scratch and Arduino.
Warehousing and logistics is seen as the scenario closest to real production for embodied intelligence, because it combines high-frequency real demand, a semi-structured environment, and quantifiable business metrics. The article divides the players into three groups: embodied intelligence startups, traditional logistics equipment companies, and end logistics enterprises such as JD Logistics, SF Express, and China Post, which respectively hold technology, systems, and scenario resources.
On November 2, six AgiBot Genie G2 humanoid robots worked 24 consecutive hours at a normally operating convenience store in Xuhui, Shanghai, covering roles including greeting customers, making coffee, stocking shelves, cashiering and cleaning, with the entire shift livestreamed. The six robots shared task scheduling through AgiBot's embodied Agent framework Genie Master and reported execution results back via the embodied execution protocol EEP, collecting failure cases into an error log and converting them into training data.
At CeMAT Asia, which opened on November 3, Ingsmart exhibited the Messol embodied-intelligence loading and unloading robot solution, designed for native mixed-box conditions inside truck trailers; it supports grasping of mixed boxes in multiple box types and orientations, and the operation process requires no manual entry into the trailer for sorting.
Liu Junhui, founder of Zhihui Robotics, said the company's technology route is AI plus spraying robots plus spraying processes. It develops its own explosion-proof spraying robot bodies, sources 3D vision cameras externally, and focuses investment on path and trajectory planning. The company launched 5 explosion-proof spraying robot models in 2023 and put them into mass production; shipments exceeded 100 units in 2025 and are expected to reach 300 units in 2026. It completed an A round of funding in the tens of millions of yuan in April this year and plans to release a seven-degree-of-freedom explosion-proof spraying robot in November.
At CeMAT 2026, Geek+ demonstrated a robotic arm equipped with the Gravity embodied model and its general-purpose humanoid robot Gino 1, completing grasping of unfamiliar objects, picking, and bin handling. Gravity uses a hybrid Transformer (MoT) dual-brain collaborative architecture and a hierarchical memory mechanism, and through natural-language correction it raised the overall success rate of complex manipulation tasks from 17.5% to 87.5%, with a single picking action stable at about 2 seconds.
Starting at 10:00 on November 2, six AgiBot Genie G2 humanoid robots worked 24 consecutive hours at a normally operating convenience store in Xuhui, Shanghai. They were assessed against store standards including on-duty time, task success rate, and response time. In the end, 4 passed probation, while Lengjie and Juanwang did not yet pass probation due to shortcomings in on-duty initiative and job stability.
Starting November 2, six Genie G2 robots equipped with AgiBot's Genie Master embodied Agent framework worked continuous 24-hour shifts in a real convenience store. In the end, four passed the probation assessment, completing a cumulative 1,730 tasks, including greeting customers 683 times, fetching and delivering 369 items, and making coffee 147 times.
This article reproduces three official pretrained policies for the Revo3 dexterous hand in Isaac Lab for in-hand object reorientation control. The cube random-target reorientation runs 8 times per episode, while the cylinder uses a 22.5° incremental chain, advancing once every 3.4 steps.
The 11th installment of the Dexterous Hand in Practice series explains how to build single-finger forward kinematics using D-H parameters. The content covers link-parameter modeling and forward-kinematics derivation for a single finger, and is part of this tutorial series.
PHYMI released its first Physical Agent action partner, Sagi, on October 28. It uses a four-wheeled legged configuration with a humanoid upper body and a companion cargo box, and is positioned to complete long-range mobility and object manipulation in open, dynamic real-world scenarios.
After merging with ATOMIX, Force Machine made its debut at CeMAT ASIA 2026 with a robot multi-agent tiered operation system that divides case-piece picking into three tiers by difficulty: economical robotic arms handle about 60% of standard goods, embodied robots handle about 20% of irregular, hard-to-grasp goods, and the remaining 20% of long-tail tasks are covered by human workers.
Ruoyu Technology exhibited independently for the first time at ROBOTECH2026, held October 27–29 at the Shenzhen World Exhibition & Convention Center. Together with Geely Auto and Zhengxing Technology, it recreated a smart refueling worksite at 1:1 scale, where the Ruoyu Lanyue robot autonomously completed the entire process—taking up the nozzle, opening the fuel tank cap, inserting the nozzle to refuel, and returning the nozzle to its place—without any manual intervention.
Huan'er Technology compares two open-source 6-axis robotic arms that natively support the Hugging Face LeRobot ecosystem: the SO-ARM101 has a 200 g payload, a 400 mm reach, and a maximum servo torque of 30 kg·cm, making it suitable for beginners learning teleoperation and imitation learning; the NexArm has a 500 g payload, a 500 mm reach, and 65 kg·cm torque, features an aviation-grade metal body, and can be expanded with peripherals such as the K230 vision module and a Mecanum-wheel chassis.
Lingchu Intelligence and Hengyan Technology are jointly delivering the Li-Ning East China Smart Logistics Center project. The embodied robot, equipped with Lingchu's self-developed model, has been deployed on site and entered trial operation, taking on routine work and fulfilling commercial orders. The solution targets the bin-picking scenario in footwear and apparel warehousing, where shoeboxes are mixed in storage and item poses are random. The model can autonomously break down multi-step goals and complete recognition, pose estimation, dexterous grasping, product sorting, and pushing full boxes, without requiring large-scale modification of existing infrastructure. During the trial operation, Lingchu will work with Li-Ning's warehouse operations team on stress testing and validation of abnormal conditions, optimizing bin-picking success rates and stability during long periods of continuous operation.
Lingchu Intelligence, together with Beihang University, Peking University, and The Chinese University of Hong Kong, proposed a frequency-aware flow matching method called FAFM; the paper was accepted to the NeurIPS 2026 main conference. The method uses the discrete cosine transform (DCT-II) to represent actions as frequency-domain coefficients corresponding to real time, performs flow matching in coefficient space and constrains the first-order time derivative, requires no additional learnable parameters, and can be used independently or integrated into VLA models such as π₀ and π₀.₅.
Why it matters: The paper presents a frequency-domain action representation that adds no learnable parameters and can be integrated into existing VLA models, offering a transferable approach for joint training on heterogeneous-frequency data.
RoboFFT, proposed by the PKU-Spirit AI Joint Lab, has been accepted to CoRL2026. It is a reinforcement learning post-training method for generative robotic policies that reuses the forward noising process from diffusion model and flow model pretraining to construct an approximate probability ratio for PPO-style clipped updates.
Why it matters: The method reuses the forward noising loss of diffusion and flow models to construct policy update signals, offering a reusable approach for post-training generative policies.
Xiaomi Group received the 2026 World Internet Conference Outstanding Contribution Award, and its "key technologies for a general-purpose robot manipulation foundation model for scaled deployment" received the Leading Technology Award. Xiaomi's humanoid robot took on an 8-hour shift for the first time at the center console side cover sequencing station in an automotive plant, achieving autonomous anomaly correction and system-level coordination with the production line; an Agent system built on the Xiaomi-Robotics-1 pretrained model is in trial operation at Xiaomi Youth Apartments, completing long-horizon task validation of over 30 consecutive minutes, covering 3 rooms and 50+ tasks.
Based on MuJoCo cloth dynamics, twelve controlled experiments were completed using realistic shell-element simulation to study differences in cloth unfolding under the same gripping trajectory. Flicking unfolds the cloth through inertia; the slow setting spreads it most fully, while too fast a motion flings it off the table edge. Unfolding performance is insensitive to stiffness, and overdamping instead produces creep.
Dexterous Hand in Practice 09 focuses on finger jitter, troubleshooting PID control from three directions: sampling, friction, and clamping. The content is a practical troubleshooting approach and does not provide a specific robot model, experimental data, or validation results.
The 10th installment of the Dexterous Hand in Practice series focuses on coordinate transforms and collision detection, with the goal of unifying each finger onto the same map. The content covers a unified representation of multi-finger coordinate frames and collision handling, and is one part of this hands-on tutorial series.
Dexterous Hand in Practice 08 focuses on single-joint control, explaining how to implement position PID closed-loop control so that a single joint moves stably according to commands. It is part of a hands-on tutorial series aimed at the implementation process of joint-level control for dexterous hands.
HAMPER reproduces Unitree G1 basket carrying in Isaac Lab, using a PPO whole-body policy and a five-stage state machine to chain together approach, squatting, threading the handle, and lifting and carrying, with pretrained weights provided for real replay on a local machine.
dex-retargeting analyzes motion retargeting from human hands to robotic dexterous hands, using a Huber loss on wrist-to-fingertip bone vectors as the objective for per-frame numerical optimization. DexPilot builds on this method by adding grasp detection, projected targets, and temporal low-pass filtering, with the Allegro and Shadow hands converging per frame at millisecond-level speed.
REEMAN published three verified AMR forklift pallet-handling deployments: in Huzhou, Ironhide 3.0 moves 1.5-ton pallets along a route of about 47 meters, with daily throughput of 160–200 trips; in Jingmen, Ironhide passes through two electric doors and interfaces with a stretch-wrapping machine, at about 75 cycles per day; in Shanxi, a Rhinoceros 1.5-ton stacker handles high-level handoffs in the packaging area.
36Kr has learned that Shenzhen Yicheng Autonomous Driving Technology Co., Ltd. (Yicheng Innovation) recently closed a RMB 200 million Series C round. Investors include Yueke Group, Shanda Investment, Anhui Guotou, and Foshan Venture Capital. The funds will be used for factory capacity upgrades, core technology iteration, and commercialization deployment.
A research team at Seoul National University has proposed RISE (Responsibility-Induced Specialized Experts), a VLA framework that can collect demonstration data for locomotion and object manipulation separately and then learn jointly from them, enabling a robot to execute multi-stage tasks consecutively without full multi-stage demonstrations.
Tutor Intelligence announced the completion of a $75 million Series B round led by Andreessen Horowitz, bringing its total funding to $117 million. The funds will be used for frontier robotics foundation model training and the manufacturing and deployment of Sonny and Cassie.
A developer combined a $250 SO-101 robot arm with Meta's Muse Spark and SAM 3.1 to find, grasp, and hand over a screwdriver on voice command, with no training required. The project was built for a Meta AI hackathon, and the demo video was posted on X.
Jiben Intelligence announced that it has completed two consecutive funding rounds totaling nearly $10 million (approximately RMB 67 million). The rounds were led by Alphaist Partners and Yaotu Capital respectively, with Jieli Angel and the actual controller of a components industry player participating as follow-on investors.
The team led by Chunhua Shen at Zhejiang University, together with the China Telecom Artificial Intelligence Research Institute (TeleAI) and Chenjia Bai's team at Gamma Intelligence, proposed GR-BC, which builds multiple attempts at the same task into a graph, uses reverse Dijkstra search to estimate the remaining steps from each state to success, and then weights action chunks accordingly to train a vision-language-action model.
Wang Rui, a 2022 undergraduate student in the School of Future Science and Engineering at Soochow University, published research on the TACHIP tactile chip in Nature Communications as a co-first author under the guidance of Professor Chen Tao's team. The plug-and-play soft tactile chip uses a five-pixel pneumatic array to reconstruct tactile patterns such as shape, hardness, roughness, and temperature, achieving a 95% first-round recognition rate and raising the success rate of six types of teleoperation tasks from 65% to 85% through reverse tactile feedback. The team completed validation demonstrations on the EFORT industrial robot platform.
Lanjian Intelligent announced that it signed a contract with Wuhan Chuyang for the Wuhan Phase II warehouse logistics equipment project, valued at RMB 258 million, which is expected to have a positive impact on its 2027 performance. As of June 30, 2026, Lanjian Intelligent's order backlog stood at RMB 2.53 billion; in the first three quarters of this year, revenue was RMB 1.215 billion, up 7.40% year on year, while net profit attributable to shareholders was RMB 67.813 million, down 27.67% year on year.
On November 2, six AgiBot Genie G2 humanoid robots entered an operating convenience store in Xuhui, Shanghai, working 24 consecutive hours in roles including greeter, barista, stocker, and cleaner, under online supervision from viewers across the internet. The robots relied on real-time visual inventory checks to return items to their places on disorganized shelves, stopping before people and then going around them, and routing around boxes. Through Genie Master and the embodied execution protocol EEP, they stored successful and failed task trajectories in long-term memory to feed back into motion strategy optimization.
In October, the Xbotics Embodied Intelligence Community held three offline events: at the Shenzhen session, 48 developers used the OmniHand O10 dexterous hand to complete calibration and a crawling competition; at the Shanghai session, 38 developers completed the transition from MotrixLab simulation training to real-machine deployment of the Qinglong Nano within two days; and at the Hangzhou session, 22 people learned to replicate the MiniDuck little yellow duck.
In Lecture 7 of the "Twenty-One Lectures" series, the Xbotics Embodied Intelligence Lab converts the target object pose obtained in Lecture 6 into gripper actions, linking the grasp-and-place loop with five poses—pre-grasp, grasp, lift, place, and retreat—and a state machine.
STIER's AI flexible grinding robot has won the bid for an intelligent flexible grinding project for aviation material repair, entering the complex grinding scenarios of aviation maintenance (MRO). Addressing the issues of diverse aviation material categories, large differences in wear deformation, and difficulty in forming standardized machining benchmarks, STIER builds a full-stack solution with multimodal environmental perception, multi-source heterogeneous data analysis, intelligent decision-making, and precise execution, enabling self-analysis of workpiece features, self-generation of grinding paths, and intelligent matching of process parameters. Its PolishX flexible force-controlled actuator achieves force control accuracy of ±0.8N, adjustment response <10ms, and contact force accuracy of ±0.5% FS.
Using the Push-T tabletop pushing task as a vehicle, this piece fully reconstructs the mathematical formulation of action diffusion policies, covering cosine-schedule noise addition, the noise-prediction training objective, FiLM conditioning injection, and sliding-window execution. The author also uses public pretrained weights to complete a real inference evaluation across ten seeds.
Official weights of InsertAnything's force-conditioned insertion policy were evaluated in Isaac Lab: at 0.1 mm clearance, baseline success rates for two hole types were 96–100%. With a 5 mm initial hand offset, success rates were unaffected, but with a 3 mm hole-position observation deviation, the hexagonal hole success rate dropped to 60%.