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Nov 3Tue
  1. Tech Xplore Robotics58

    ETH Zurich develops FlexiQuad flexible quadrotor that resists collisions and reaches a top speed of 80 km/h

    An ETH Zurich team has developed FlexiQuad, a ring-shaped flexible-frame quadrotor with no central body; on impact the frame deforms to absorb energy and the drone can keep flying. It reaches a top flight speed of 80 km/h, with collision tests at about 25 km/h; the frame material costs less than 15 Swiss francs, and it has been used to grasp and carry soft first-aid kits and payloads heavier than its own weight. The team also used reinforcement learning to let it stabilize its attitude after a collision before resuming autonomous flight, but reliable perception and autonomous navigation remain prerequisites for leaving the lab.

  2. 深蓝AI · 微信公众号71

    Shanghai Jiao Tong University's Zou Danping team proposes DiffDreamer, combining world models and differentiable simulation for agile quadrotor control

    Zou Danping's team at Shanghai Jiao Tong University proposes DiffDreamer, which couples a learned world model with differentiable simulation for agile quadrotor control; the paper has been accepted to RAL 2026. The method uses the world model to predict external dynamics and differentiable simulation to propagate the robot's physical state. In aggressive tracking tasks, distance error drops to 0.381 m, versus 0.793 m for the strongest baseline; in dynamic gate crossing at gate speeds of 1.0/1.5/2.0 m/s, the number of gates passed is 16/12/8, versus 12/4/1 for MPC.

  3. Xbotics具身智能实验室 · 微信公众号78

    GE-Sim 2.0 and π0.5 closed-loop simulation test: Why does reward hacking occur in VLA training?

    The Xbotics Embodied Intelligence Lab built a closed-loop simulation pipeline using the AgiBot GE-Sim 2.0 world model and the OpenPI π0.5 policy. In testing, the world model generated about 4.33 frames per second, the pure-policy closed loop ran at about 3.20 frames per second, and after adding MiMo online scoring, the rate dropped to about 0.88 frames per second.

    Why it matters: The author uses a four-stage test to break down the frame-rate bottlenecks and causes of reward hacking in world-model closed-loop simulation, which can be transferred to the design of VLA evaluation workflows.

  4. PsiBot/灵初智能71

    Lingchu Intelligence and collaborators propose FAFM, a continuous action generation method for heterogeneous-frequency data, accepted to NeurIPS 2026

    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.

  5. PsiBot/灵初智能71

    PKU-Spirit AI Joint Lab's RoboFFT Accepted to CoRL2026, Uses Reinforcement Learning Post-Training to Generate Robotic Policies

    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.

  7. Ken Goldberg30

    KEC combines Fable and Astra for parameter tuning to achieve real2sim

    KEC combines Fable with Astra to rapidly tune complex simulation parameters via RSS, including geometry, dynamics, deformation, materials, lighting, textures, and camera extrinsics, so that the simulation matches a given input video. This work targets the capability gap in agentic robotics for extending to new environments, new objects, and new tasks.

  8. Guyuehome52

    G1 Brunson: Humanoid Robot Between-the-Legs Dribbling Control Based on Deep Visual Reinforcement Learning

    G1 Brunson uses event-based rewards and asymmetric actor-critic training, bringing the depth camera directly into the observation loop during training to form a G1 whole-body dribbling policy. Reproducing the official weights locally in MuJoCo gave an average of 43.5 crossovers over 12 episodes with zero falls, matching the official results.

  9. Guyuehome57

    WAM: Training a world model with quadruped robot locomotion data for navigation planning

    WAM trains a forward-dynamics world model on quadruped robot locomotion data collected under convex model predictive control, replaces hand-crafted steering laws with receding-horizon sampling planning, and combines A* global paths with dynamic obstacle extrapolation to achieve navigation and obstacle avoidance. The material states that all numerical values come from local reproduction experiments.

  10. HuggingFace Daily Papers67

    H2RB co-trains with human demos and robot data to adapt VLA policies

    The study proposes H2RB, a human-robot co-training framework that adapts pretrained VLA policies on unpaired human and robot demonstrations through geometry-anchored alignment and a decoupled-decoder tokenizer. In real-world tasks, object transfer performance improved from 8.0 to 51.8, and the skill transfer score reached 62.7, while the co-training baseline completely failed to transfer human demonstration skills. Out-of-distribution transfer under object placement changes also improved from 6.0 to 45.3.

  11. Tech Xplore Robotics71

    Seoul National University proposes RISE framework to complete multi-stage humanoid tasks using separately collected locomotion and manipulation data

    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.

Nov 2Mon
  1. 机器之心 · 微信公众号74

    Zhejiang University and TeleAI propose GR-BC, using graph search to select effective actions from robot trial and error

    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.

  4. CVer · 微信公众号60

    NTU and other teams present MemSkill at NeurIPS 2026, letting agents learn and evolve memory skills

    A research team from Nanyang Technological University and other institutions presented MemSkill at NeurIPS 2026, packaging memory operations into learnable, reusable, and evolvable Memory Skills, optimizing skill selection through task feedback, and revising and expanding the skill library based on failure cases.

  5. CVer · 微信公众号58

    Soochow University undergraduate publishes TACHIP tactile chip results in Nature Communications as co-first author

    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.

  6. Robohub38

    University of Bristol uses ordinary electric motors to replicate muscle coordination, potentially improving robots

    A University of Bristol team built a tabletop physical model simulating muscle contraction using a row of ordinary electric motors coupled to each other through a shared mechanical skeleton, with results published in the Royal Society journal Interface. In the experiments, the motors made intermittent contact with the skeleton to transmit force, and without direct communication, muscle-like behaviors spontaneously emerged, including a load-velocity relationship, more units participating as load increased, and coordination waves. The researchers believe this approach, in which coordination is handled by the structure itself, could help improve how robots are actuated.

  7. Guyuehome19

    SoftCon: Octopus swimming control based on bionic muscle actuation and soft-body dynamics

    The SoftCon framework builds an octopus swimming control pipeline from tetrahedral soft-body dynamics, muscle constraints that contract along fibers, and traveling activation waves generated by keyframe matrices and propagation filtering, using PPO to learn coordination rather than reconstruction. The framework originates from SIGGRAPH Asia 2019.

  8. Guyuehome57

    G1 Dribble: End-to-End Reinforcement Learning for Humanoid Robot Soccer Dribbling Control

    G1 Dribble uses end-to-end reinforcement learning to achieve humanoid robot soccer dribbling; the walking task's weights are not adjusted, and velocity commands drive both the body and the ball. The author tested it locally in MuJoCo-Warp and recorded eighteen cloud sessions, reporting touch rhythm, the distance band for re-touching the ball, and failure modes, including that a centered start steps over the ball without touching it, a first touch occurs only when offset to the side, and at 1.5 meters per second it knocks the ball away directly.

  9. Guyuehome58

    HACMan++: Spatially Anchored Motion Primitives for Long-Horizon Robotic Manipulation

    HACMan++ targets long-horizon manipulation for six-dimensional object rearrangement, decomposing actions into three parts: selecting a primitive, anchoring a placement point on the point cloud, and continuous parameters, with unified decision-making via a per-point, per-primitive evaluation map. On this basis, the framework achieves closed-loop chaining of pushing, grasping, moving, and placing.

  10. Guyuehome58

    Neural-Fly: Online Adaptive Control for Quadrotors in Strong Winds

    Neural-Fly proposes a residual aerodynamic force adaptation law that combines wind-invariant representations with online least squares for online adaptive control of quadrotors in strong winds. The method trains a network on public flight data and conducts comparative figure-8 trajectory tracking experiments with a PyBullet quadrotor in a steady wind field, demonstrating rapid adaptation enabled by domain-shift separation.

  11. 3D视觉工坊 · 微信公众号78

    Any3R goes open source: one model unifies 3D reconstruction and pose estimation for pinhole, fisheye, and panoramic cameras

    South Dakota State University and other institutions propose Any3R, which uses a dense ray field to describe arbitrary central cameras, reconstructing a 3D point cloud and estimating pose from mixed-camera images in a single forward pass. The method replaces the row and column indices of rotary position encoding with angular coordinates and weights the pixel loss by solid angle, so one set of weights covers pinhole, fisheye beyond 180°, and 360° panoramic cameras. On benchmarks spanning 13 central camera types and 3 datasets, it leads in both reconstruction accuracy and pose accuracy; the inference code, 13 camera models, and weights are open-sourced.

    Why it matters: The article presents a feed-forward 3D reconstruction method that replaces the pinhole assumption with a dense ray field, offering insight into handling mixed inputs from multiple camera types.

  12. OFweek Robotics62

    CAS Institute of Automation and PaXini collaborative research: tactile reinforcement learning achieves sub-millimeter precision assembly

    A team led by Cheng Long at the Institute of Automation, Chinese Academy of Sciences, published research at IROS 2026 using tactile-enhanced reinforcement learning to complete sub-millimeter precision insertion, raising the success rate from 52% for a tactile-free approach to 67% under a 0.05 mm clearance.

  13. arXiv cs.RO62

    GenSight: A Unified Embodied World Model for Video Generation and 4D Perception

    GenSight is a unified embodied world model that integrates future video generation and dense perception into a single pretrained video diffusion Transformer. It uses a unified spatiotemporal representation covering video, depth, embodiment segmentation, and 2D optical flow relative to the first frame; built on a shared DiT backbone, it predicts each modality within the same architecture via lightweight task modulation, and jointly optimizes them in a unified velocity prediction space. At inference, it supports multi-step future video generation with aligned dense prediction, as well as single-step dense perception from an observed video. Training data covers a variety of robot embodiments and human hand interaction.

  14. arXiv cs.RO62

    Shared Modular Recurrence in Contextual MDPs for Universal Morphology Control

    The paper proposes a Transformer-based architecture with shared modular recurrence for universal morphology robot control and evaluates its generalization performance on a set of MuJoCo robots. The authors note that contextual features are often only partially available but can be recovered through modular interactions, improving multi-robot control and generalization to contexts unseen during training. Results show substantial improvement in zero-shot generalization performance on robots with unseen dynamics, kinematics, and topologies across four environments.

  15. arXiv cs.RO62

    MUSBRIC: LEGO-Compatible Pneumatic Muscle Modules for Reconfigurable Musculoskeletal Robots

    The authors present MUSBRIC, a modular hardware platform and accompanying MuJoCo simulator for reconfigurable musculoskeletal robots, which uses LEGO-compatible endcaps to turn fiber-reinforced extensile pneumatic artificial muscles into reusable, plug-and-play muscle modules. An elbow-joint prototype validated load-dependent flexion and extension, with pulley-guided routing enabling reversible motion and a mechanical stop stabilizing the straight posture; a robotic hand demonstrated compliant grasping and multi-joint construction, 15 leg configurations completed matched sweeps in hardware and simulation, and a quadruped assembled from four legs achieved walking. The hardware design and simulation code will be open-sourced.

  16. arXiv cs.RO64

    LOGIV: A Task-Graph Framework for Verified Execution and Causal Local Repair in Long-Horizon Robot Tasks

    LOGIV is a task-graph framework for long-horizon robot tasks that connects symbolic planning, observation-based verification, and embodied execution. During execution it checks the physical validity of condition-support and resource-ordering edges, and after a failure it uses dependency tracing to determine which parts must be restored.

  17. arXiv cs.RO72

    OpenFlyV2: An onboard vision-language-action model for aerial perception and navigation

    OpenFlyV2 is a unified onboard vision-language-action architecture that uses a shared vision-language representation to support semantic understanding, language-grounded perception, spatial reasoning, and continuous flight control within a single model. The authors built a simulation dataset of approximately 70,000 navigation trajectories and 60,000 vision-language instruction-response pairs. On an NVIDIA Jetson Orin NX, the model runs fully onboard and generates action chunks of 12 waypoints each at 10 Hz.

  20. arXiv cs.RO80

    TacClaw-Infinity: A Large-Scale Vision-Tactile-Language-Action Dataset for Dexterous Manipulation

    The research team released TacClaw-Infinity, a large-scale structured Vision-Tactile-Language-Action (VTLA) dataset for contact-rich manipulation, spanning over 10,000 hours, 1 million episodes, and 1 billion frames across more than 1,000 task types.

    Why it matters: This dataset provides a collection interface and quality control pipeline for ten-thousand-hour-scale tactile manipulation data, and its cross-embodiment transfer validation approach can serve as a reference.

  22. arXiv cs.RO52

    Detect and Suppress: A Mechanistic Defense Against Adversarial Patches on VLA Models

    The authors use a sparse autoencoder (SAE) to analyze the internal representations of a VLA model, identify a feature whose activation strongly correlates with the presence of adversarial patches, and suppress that feature at inference time only when a linear probe detects an attack, thereby improving robustness without fine-tuning the VLA. In adversarial patch attack tests on LIBERO-10, conditional intervention improved the success rate under intermittent attacks, whereas continuously applying the same intervention substantially degraded policy performance.

  23. arXiv cs.RO75

    D4orm diffusion-denoising framework extended into a family of multi-robot trajectory planners

    Based on the dynamics-aware diffusion-denoising framework D4orm, this paper builds a family of multi-robot trajectory planners for different operational requirements, including a decoupled planner, an online receding-horizon planner with feedback control, and a distributed planner. Evaluations with differential-drive and holonomic robots in 2D and 3D environments show that D4orm-based methods find high-quality solutions faster and more reliably than sampling-based optimization methods such as MPPI and a learning-based diffusion model method.

  24. arXiv cs.RO58

    CDIP: Compressed Delayed-Information Projection for Underwater Navigation Under Acoustic Measurement Latency

    The paper proposes compressed delayed-information projection (CDIP), which handles delayed-arrival acoustic position measurements in a 15-dimensional error-state Kalman filter (ESKF), retaining source-associated IMU snapshots and the current-to-snapshot cross-covariances, so delayed corrections can be projected without repeating the filter from the start.

  25. arXiv cs.RO60

    Study: Learning and Transferring Closed-Loop Robot Software

    The research treats complete closed-loop robot policy implementations as reusable execution experience: a coding agent generates policy code from a few successful demonstrations and iteratively improves it using simulation feedback. Across four source tasks in RoboCasa, iterative optimization raised the success rate from 28.3% with initially generated code to 64.2% with validation-selected code, and the learning approach was validated on a physical Unitree G1.

  26. arXiv cs.RO62

    Extending the Franka Emika Panda's Life: A ROS 2 Software Stack with a Reliable Position Interface

    This paper releases an open-source ROS 2 software stack that restores ROS 2 support for the Franka Emika Panda and resolves the long-standing unreliability of its external position control interface. The authors' analysis attributes vibrations and protective stops to external control loop timing and sampling jitter rather than to limitations of the robot itself, and on that basis they propose an asynchronous hardware interface that decouples real-time communication from the ROS 2 control loop, a rate-matching mechanism for slower command sources, and a position-domain reference generation strategy.

  27. arXiv cs.RO60

    UniCross: A Unified Cross-Skill Dexterous Manipulation Synthesis Framework

    UniCross proposes a unified framework that models four dexterous manipulation skills—grasping, relocation, in-hand rotation, and in-hand translation—as the same relational-target formulation, and distills a single policy that does not depend on skill identifiers. The policy performs well on each individual skill, generalizes to unseen objects, and supports long-horizon skill chaining and execution of relational targets unseen during training; the framework also applies to different hand morphologies.

  28. arXiv cs.RO67

    DR-LfD: Decomposing and Reorganizing Demonstrations with Atomic Skills and Visuomotor Policies for Bimanual Manipulation Planning

    The authors propose DR-LfD, a framework that integrates visuomotor policies into a TAMP-gated decision-making system, decomposes human demonstrations into atomic skills based on contact relationships, and then reproduces and reorganizes them using visuomotor policies or object-centric primitives. This method shifts the demonstration data requirement from growing exponentially with the skill sequence to growing with the number of skill types, and on two DexMimicGen tasks it outperforms a diffusion imitation policy trained on 1,000 demonstrations while using only 100 demonstrations. The paper has been accepted by T-RO.

  29. arXiv cs.RO58

    Using a Robotic Arm as an Attitude Actuator: Propellant-Free Attitude Maneuver Planning for Free-Floating Spacecraft

    This research uses manipulator motion for propellant-free attitude control of free-floating spacecraft, modeling it as a trajectory optimization problem with joint and collision-avoidance constraints and solving it with an interior-point method. Across a range of spacecraft-manipulator systems, the method computed rest-to-rest slew trajectories of up to 90° and detumble trajectories with a 40% reduction in angular velocity. The authors also directly compare the manipulator's control authority with that of reaction wheel arrays via momentum and torque envelopes, noting that manipulators could serve as a redundant or even primary attitude control system, with particular promise for in-space assembly and manufacturing involving the capture of high relative-mass payloads.