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#Planning and decision-making
Nov 10Tue
  1. New Strategy Robotics38

    Bangqi Technology debuts at 2026 CeMAT in Shanghai with full-scenario embodied intelligence solution and value-based RaaS model

    At 2026 CeMAT ASIA, Bangqi Technology is showcasing a full-stack embodied intelligence logistics solution and a "pay-per-operation-value" RaaS model, combining standardized AMR transport with humanoid robots for end-of-line operations, coordinated by its self-developed ADS scheduling system. The solution has been validated on a production line at a leading vehicle manufacturer, improving material delivery efficiency by 30%; in a warehouse goods-to-person project, equipment achieved 7×24-hour unmanned operation, boosting capacity by 125% with 99.9% accuracy. RaaS is billed by actual workload, and the full model can be deployed in 1-3 months.

Nov 9Mon
  1. Tech Xplore Robotics78

    UC Berkeley and NVIDIA propose agentic robotics to generate and improve robot programs in simulation

    Ken Goldberg's team at UC Berkeley and Spencer Huang, NVIDIA's head of robotics engineering, proposed an "agentic robotics" method that lets AI agents generate, test, and correct robot control programs in simulation without additional data collection.

    Why it matters: The report describes a method for using multi-agent systems to generate, test, and correct robot programs in simulation, and presents real-world data from warehouse sorting.

  3. arXiv cs.RO60

    LeWAM: Robot planning method based on JEPA world action model and diffusion-guided MPC

    The authors propose LeWAM, a bidirectional Transformer trained end-to-end on a decoder-free JEPA latent space that supports four modes: forward, backward, inverse dynamics, and policy prediction. Linear probe experiments show that LeWAM's latent space reads robot and object state better than the forward-only Le World Model, and that its degree of ignoring visual distractors is comparable to LeWM and clearly better than reconstruction-based WAM.

  4. arXiv cs.RO71

    Onboard Dynamic Obstacle Avoidance System for Small Quadrotor UAVs Based on mmWave Radar

    The authors propose the first mmWave radar-based onboard perception-and-control dynamic obstacle avoidance system for small quadrotor UAVs. The system combines a lightweight interacting multiple models (IMM) tracker with a control barrier function (CBF) controller that directly outputs evasive accelerations, and derives sufficient avoidance conditions relating sensing range, relative speed, and control delay.

  7. arXiv cs.RO62

    VLD: Visual Learned Distance as an Interface for Reinforcement Learning Navigation

    The authors propose the Visual Learned Distance (VLD) framework, which decouples perception learning from policy learning for image-goal navigation: first, a distance-to-goal predictor is trained self-supervised on about 3,000 hours of internet and simulated video; then, in simulation, a reinforcement learning policy is trained using privileged geometric distances perturbed by GeoNoise; at deployment, VLD predictions are used zero-shot.

  10. arXiv cs.RO55

    Lightweight Path-Aware Frontier Re-ranking for LiDAR UAV Exploration

    The paper proposes a lightweight path-aware frontier re-ranking method for LiDAR UAV autonomous exploration: a lightweight utility function first retains a small top-N set of frontier candidates, then time-bounded RRT* planning estimates their feasible path costs for re-ranking, and the path for the selected frontier is reused for navigation to reduce redundant global planning.

  11. arXiv cs.RO69

    TPS-A*: Path Planning for Any-Shape Vehicles with Certified Collision Checking in Trajectory Parameter Space

    The authors propose TPS-A*, a lattice planner whose edges are kinematically feasible trajectories produced by parameterized trajectory generators, with certified collision checking performed in trajectory parameter space. A grid precomputed per footprint needs only a single pass over local obstacles to return a certified free distance for every candidate trajectory, making the per-node collision cost independent of footprint complexity and trajectory count.

  12. arXiv cs.RO58

    Range-only HOCBF-QP framework enables safe circumnavigation by heterogeneous-orbit multi-robot systems

    The paper proposes a safety-critical control framework for nonholonomic multi-robot systems that lets each robot circumnavigate a stationary target at a different orbital radius while maintaining spacing from neighbors and avoiding collisions. Each robot measures only its distance to the target and exchanges information only with its two adjacent robots; it drives the radius to the target value via acceleration, balances the formation via turn-rate, and uses a higher-order control barrier function quadratic program (HOCBF-QP) to simultaneously constrain target distance, geofence, and inter-robot safety.

  14. OFweek Robotics77

    Apple unveils HALO humanoid robot control system; Unitree G1 achieves 91% task success rate in unfamiliar environments

    Apple's research team published the paper "Perceptive Humanoid Motion from Simulation" on arXiv, unveiling HALO, an autonomous humanoid robot control system, and validating it on the Unitree G1.

    Why it matters: Apple's HALO splits task orchestration, motion generation, and tracking into three layers, and reports comparative results of 91% in unfamiliar environments and 70% on composite tasks, offering a look at its layered design and data synthesis pipeline.

  15. 锐曼REEMAN36

    What Is an AMR Forklift? Navigation, Flexibility, and Factory Fit

    AMR forklifts rely on onboard LiDAR and laser SLAM for mapping and localization, enabling autonomous path planning and obstacle avoidance without ground infrastructure such as magnetic tape, guide wires, or reflectors; route changes are usually made via software. The REEMAN Ironhide 3.0 is a 1.5-ton autonomous forklift with ±5 cm pick-and-place accuracy on 1.2 × 1.2 m pallets, 6 hours of runtime at full load and 8 hours empty, and a maximum mapping area of 40,000 m².

Nov 8Sun
  1. New Strategy Robotics25

    Linde Material Handling Showcases Flexible Automation Logistics Solutions for the Future of Smart Logistics at Its Ninth Consecutive CIIE Appearance

    At the ninth China International Import Expo (CIIE), Linde Material Handling exhibited the compact pallet-handling robot L-MATIC, which demonstrated an automated workflow in unmanned operation. L-MATIC weighs 850 kg and has a load capacity of up to 1.2 tons; it features an ultra-narrow body design with built-in laser navigation and a multi-sensor fusion scheme. On site, a "threading the needle" segment, in which a thin steel wire at the front of the fork passes through a small-diameter ring, demonstrated positioning and control precision. Linde also presented KION's multimedia interactive software system, which can automatically generate suitable logistics solutions based on customer operating conditions and logistics needs.

  3. Guyuehome62

    Long-WAM explained: using autoregressive video pretraining for long-horizon robot decision-making

    Long-WAM learns visual dynamics through autoregressive video pretraining and uses asymmetric causal attention to connect video and action experts, enabling long-horizon decision-making based on historical information. Its approach predicts future frames in latent space, combines historical information to generate action chunks, and supports streaming encoding and asynchronous execution.

Nov 7Sat
  1. New Strategy Robotics38

    SUPMAST's Satongxue AGV unmanned transport robot debuts at the 22nd China International Grain and Oil Expo

    SUPMAST brought its "Satongxue" AGV unmanned transport robot and in-plant smart logistics solution to the 22nd China International Grain and Oil Expo in Xiamen, held November 6 to 8, with live demonstrations of fork picking, stacking, and alignment correction at Booth C123 in Hall C1. The AGV uses laser SLAM + reflective pillars + IMU fusion navigation and requires no magnetic strip guide rails; the accompanying Yunshu S7 RDS scheduling system supports a maximum concurrency of ≥20 units and task allocation latency of ≤500ms. In the Yihai Grain and Oil project, it handles a production takt of 3 minutes per pallet, reducing the error rate by more than 95% and the cargo damage rate by 94%.

  3. 优宝特 · 微信公众号45

    Ubot's "Xingzhe Taishan" humanoid robot climbs Mount Tai fully autonomously, takes second place at first CMG World Robot Mount Tai Climbing Competition

    Ubot's "Xingzhe Taishan" humanoid robot completed the official course as the only fully autonomous entrant in the first CMG World Robot Mount Tai Climbing Competition, taking second place. The entire climb was free of remote-control intervention, with the "brain" recognizing terrain and planning routes in real time and the "cerebellum" dynamically adjusting gait to handle uneven steps and slippery surfaces. Ubot says its commercial quadruped robot for inspection scenarios has carried out regular autonomous inspection in limited scenarios across multiple pilot projects in power and mining.

  4. 机器人前瞻 · 微信公众号83

    Apple releases HALO system, enabling Unitree G1 to perform whole-body skills such as crawling under tables and passing through door gaps zero-shot

    Apple released the HALO humanoid whole-body motion control system, which procedurally generates 1,000 virtual residential scenes and synthesizes nearly 300 hours of paired data, enabling the Unitree G1 to master skills such as sitting on chairs, turning sideways to pass through a half-open door, crouching under a table, and pushing boxes.

    Why it matters: Apple's HALO uses simulation-synthesized data to train humanoid whole-body skills, transfers them zero-shot to real scenes, and ablation experiments show the contribution magnitude of each module.

  5. 机器之心 · 微信公众号72

    Cainiao Guangzhou Tmall Supermarket warehouse deploys 135 ZeeBot climbing robots for 28-hour Double 11 fulfillment

    During Double 11, the Cainiao Zengcheng Tmall Supermarket warehouse in Guangzhou deployed 135 ZeeBot climbing robots to complete 28 hours of peak order fulfillment in a storage area with 9-meter-high, 20-tier racks and 42,000 bins, achieving a 99.99% on-time rate for wave outbound orders. The robots accumulated over 140 km of vertical travel, with a peak of 11 km in a single hour and a vertical climbing speed of 1.2 m/s; they attach to racks with dual grippers and require no dedicated tracks. Overall warehouse storage efficiency is about 3 times the original, labor efficiency has risen to about 2.5 times, and output per workstation equals 2 to 3 picking employees.

Nov 6Fri
  1. New Strategy Robotics33

    Galaxis Technology unveils full GALAXIS embodied intelligence product matrix

    At CeMAT, Galaxis Technology unveiled its GALAXIS embodied intelligence product matrix, built on a "logistics brain" foundation and planned around maximum payloads across four product tiers: the 1500 kg ultra-heavy-duty VFR, the 50 kg heavy-duty VPR-CP, the 10 kg light-duty wheeled humanoid robot, and the 5 kg small-item picking manipulator. The company proposed a three-layer intelligence system of "super brain—body brain—body cerebellum," and said the embodied intelligence picking workstation and VPR-Cyber Picker pallet solution shown at its booth are prototype demonstration results.

  2. IPLUS MOBOT/迦智科技29

    IPLUS MOBOT to showcase EMMA 1500L heavy-load AMR at ADM Montreal 2026

    IPLUS MOBOT will showcase its EMMA 1500L heavy-load autonomous mobile robot at ADM Montreal 2026 (Booth 900) at the Palais des congrès in Montreal on November 11–12. The robot has a rated payload of 1,500 kg, docking accuracy of ±2 mm, and positioning accuracy of ±10 mm. The platform uses laser navigation, requires no extensive floor markers, and is scheduled by CLOUDIA fleet management software; it can integrate with MES, WMS, and production equipment.

  3. 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.

  4. 36Kr Embodied Intelligence60

    EABOT completes nearly 400 million yuan in funding within a year, operates over 100 heavy trucks to validate heavy-duty physical AI

    Shanghai EABOT Technology (EABOT) recently completed two consecutive funding rounds totaling nearly 400 million yuan, with investors including Ge Weidong, Chentao Capital, Hony Capital, and Zero One Automotive. Founded in February 2026, the company focuses on heavy-duty industrial physical AI. It already operates more than 100 heavy trucks across 60 routes, mainly serving short-haul bulk material scenarios of 0-300 kilometers, and has conducted real-road zero-intervention testing in Xinjiang, Inner Mongolia, and other regions.

Nov 5Thu
  1. 深蓝AI · 微信公众号74

    HKUST's Shen Shaojie team proposes RAVEN: an active SLAM framework unifying UAV active exploration and loop-closure localization

    The Shen Shaojie team at HKUST has proposed RAVEN, a unified active SLAM framework that uses utility vectors to separately quantify exploration efficiency and localization accuracy, selects global tours according to Pareto optimality, and uses a priority parameter λ (0–1) to determine whether to favor exploration or localization.

  2. 锐曼REEMAN42

    How long does it take to deploy a REEMAN Ironhide 3.0 autonomous forklift? A one-day deployment case at a Zhejiang lighting factory

    A REEMAN Ironhide 3.0 autonomous forklift completed on-site deployment in about one day at a lighting equipment manufacturing plant in Zhejiang, handling pallet transport between a covered outdoor storage area and an indoor warehouse. The project has an actual load of about 600 kg, a one-way route of about 100 m, aisles 2–3 m wide, and performs 140–180 tasks per day; the vehicle model has a rated load of 1,500 kg. Laser SLAM navigation requires no floor QR codes or magnetic strips, but WMS/MES integration, elevators, automatic doors, and multi-route networks can extend deployment time.

  3. Reddit r/robotics22

    SmartGrid Mesh Flow feature: How to use vector fields to generate adaptive spray trajectories on 3D mesh surfaces

    A developer is seeking mathematical algorithm advice for the Mesh Flow feature of SmartGrid, an offline robotic spray trajectory planner, with the goal of generating and maintaining consistent trajectory patterns across different 3D mesh geometries. Their concerns include using vector fields to determine travel direction, controlling path spacing with geodesic distance fields or surface offsets, and letting local normals, tangent vectors, and curvature influence trajectories while suppressing jitter caused by mesh irregularities. The current focus is on deriving a general geometric algorithm that can reproduce reference patterns, rather than on programming implementation.

  4. New Strategy Robotics60

    Zhongli's 45-ton unmanned reach stacker leads railway full-chain unmanned solution at China Railway site meeting

    Zhongli shares displayed its 45-ton unmanned reach stacker and railway unmanned transfer system solution at the China Railway Group's railway modern logistics system construction site meeting held October 27-28. The reach stacker is said to achieve a fully closed-loop unmanned container transfer operation and supports switching between autonomous operation and remote teleoperation modes. The transfer solution covers box unloading from boxcars, platform transfer, in-warehouse intelligent management, and loading and outbound shipping, carried out collaboratively by a 1.5-ton omnidirectional loading and unloading robot, a 2.0-ton embodied loading and unloading robot, and a 25-ton unmanned flatbed vehicle.

  5. arXiv cs.RO47

    Low-cost 4-DoF arm RoArm-M2-S achieves vision-guided writing tool reorientation and color sorting

    The roughly $200 Waveshare RoArm-M2-S four-degree-of-freedom robotic arm, under a fixed overhead camera, uses a YOLO11n-OBB detector, an ArUco reference pose, and a color classifier to perform color sorting of writing utensils without a wrist rotation joint. For utensils deviating more than 45 degrees from the fixed approach direction, corrective sweeps bring them into a graspable pose within at most 4 attempts. In 196 single-utensil trials, 176 (89.8%) landed in the correct color bin; of the 20 failures, 19 were grasp slips or missed grasps and 1 was a color mislabel.

  6. arXiv cs.RO60

    MARLIN: Guiding Multi-Agent Reinforcement Learning with Language Negotiation

    MARLIN proposes a hybrid framework in which large language models guide policy learning by generating high-level action plans through inter-robot language negotiation before the reinforcement learning policy has learned effective behaviors, and it dynamically switches between reinforcement learning and language-model negotiation during training. The authors evaluated it on simulated and physical robots with local and remote language models; results show higher early-training performance than standard multi-agent reinforcement learning, with limited impact on final performance. The code is publicly available, and the paper was accepted to ROBIO2026.

  7. arXiv cs.RO84

    HALO: Humanoid Autonomy System Trained on Synthetic Simulation Data Achieves Zero-Shot Real-World Transfer

    The research team proposes HALO, a humanoid robot autonomy system that synthesizes vision-language-action data across roughly one thousand procedurally generated home scenes, eliminating reliance on teleoperation data collection. HALO learns skills including sitting on chairs, navigating to specified objects, stepping sideways through half-open doors, crouching and crawling under tables, and pushing boxes, and can combine them to complete long-horizon tasks. Without ever seeing real home scenes during training, HALO transfers zero-shot to the physical world, achieving a 91% success rate across 360 trials in six unmapped real-world environments.

    Why it matters: The paper presents a complete path from synthesizing vision-language-action data using procedurally generated home scenes to zero-shot transfer to real robots; its approach to data scaling is worth referencing.

  8. arXiv cs.RO62

    Uncertainty-Triggered Aerial Refinement for Off-Road Navigation

    The paper proposes a planner-conditioned air-ground assistance method that evaluates how map uncertainty affects the UGV's current MPPI rollouts. When navigation remains degraded, it re-scores the same rollouts under resolved map hypotheses, selects the map layer whose request yields the largest improvement, requests the corresponding aerial measurement, and fuses it to replan.

  9. arXiv cs.RO58

    Riemannian Optimization-Based Whole-Body Obstacle Avoidance Framework for Mobile Continuum Robots

    The study proposes a unified planning and control framework for mobile continuum robots, combining a global layer consisting of A* search and minimum-jerk planning with a local layer consisting of a geometry-consistent inverse kinematics solver and Riemannian optimization, to coordinate the mobile base and continuum deformation for obstacle avoidance. The authors compare it with multiple baseline planners in simulated pipe-traversal tasks and conduct real-world experiments on navigation among dense obstacles and manipulation in confined spaces. Results show improvements in motion consistency, feasibility, and adaptability.