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#Motion control
Nov 5Thu
  1. Guyuehome58

    OpenFleX: Omnidirectional Mobility and Dual-Arm Coordinated Manipulation Control for a Wheeled Humanoid Robot

    The OpenFleX wheeled humanoid robot reproduces omnidirectional chassis kinematics, damped least-squares inverse kinematics, and whole-body redundant coordinated control in MuJoCo. A single end-effector motion can be achieved through various combinations of chassis, lift, and dual-arm degrees of freedom; the experiments compare pseudoinverse and damped least-squares performance near singular configurations.

  2. Guyuehome58

    Dexterous Hand Practice 13: Using Polynomial Trajectory Planning to Eliminate Position Jumps and Achieve Smooth Motion

    The 13th post in Gu Yue Ju's "Dexterous Hand Practice" series explains how to use polynomial trajectory planning to turn position jumps in a dexterous hand into smooth motion. The material provides only the title and summary; it does not give specific polynomial orders, parameters, or experimental data.

  4. Tech Xplore Robotics60

    Shenzhen Institute of Advanced Technology, CAS develops underwater exoskeleton PEAKED, reducing divers' breathing volume by up to 29.77%

    The team led by Wu Xinyu at the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, has developed a wearable underwater exoskeleton. Its representative system, PEAKED, is a soft underwater hip exoskeleton that assists hip flexion and extension, supporting flutter kicking, breaststroke kicking, and underwater walking. In prior human experiments, PEAKED reduced per-minute breathing volume by 29.77% during flutter kicking, 25.70% during breaststroke kicking, and 18.35% during underwater walking.

Nov 4Wed
  1. Tech Xplore Robotics62

    Tohoku University develops electronics-free mechanical reflex module, reproduces knee-jerk reflex and achieves bipedal walking

    A team at Tohoku University has developed a mechanical reflex module that requires no electronic sensors or circuits. Integrated into a musculoskeletal robot, it reproduced the knee-jerk reflex, and combined with high-level control that adjusts activation thresholds according to movement phase, it achieved bipedal walking. The module integrates sensing, computation, and actuation within its physical structure: it mechanically detects when an artificial muscle is stretched beyond a threshold and contracts automatically, inspired by human muscle spindles.

  2. New Strategy Robotics60

    Youibot Semiconductor Mobile Manipulator Robot Project Wins First Prize of Guangdong Provincial Technology Invention Award

    The project "Key Technologies and Systems for Highly Stable Mobile Manipulator Robots for Semiconductor Manufacturing," led by Youibot, won the first prize of the Technology Invention Award at the 2025 Guangdong Provincial Science and Technology Awards. The project claims breakthroughs in three areas: material vibration control, wide-range navigation and positioning with end-effector grasping precision, and integrated "hand-eye-foot" safety control. The OW series and ATS series mobile manipulator robots have entered more than ten wafer fabs in China and abroad, integrating into 8-inch and 12-inch wafer and 28nm chip production processes and operating 24/7.

  3. Guyuehome29

    crocoddyl: Feasibility-Driven Differential Dynamic Programming for Optimal Control

    Reproduced the core mathematical formulation of the crocoddyl solver isomorphically: Riccati backward sweep, LM regularization, and gap contraction expansion. On a large-amplitude cart-pole swing-up task, a three-way comparison was conducted; FeasShoot required fewer than 30% of the iterations of the shooting method, and regularization remained frozen.

  5. Guyuehome58

    How DiffTaichi's differentiable physics simulation uses gradients to drive control optimization

    The article analyzes the adjoint gradient mechanism of DiffTaichi's differentiable physics simulation, using loss gradients to directly optimize actuator control sequences in material point method soft body, mass-spring, and fluid scenarios. It shows that gradient methods can optimize soft-body motion forms that reinforcement-learning-style sampling methods struggle to reach.

  6. Guyuehome60

    Reproducing PPO Reinforcement Learning-Based Quadrotor Racing Flight Control

    The author loads an open-source pretrained policy in Isaac Sim to reproduce quadrotor racing on a figure-8 track, matching the official result with 25 gates and 3.12 laps. The content breaks down the three attitude phases of high-speed turns and uses a three-seed controlled experiment to test the real benefits of domain randomization.

  9. 机器人全球资讯 · 微信公众号47

    First CMG World Robot Mount Tai Climbing Competition concludes, Unitree A2 and B2 win 1 gold and 2 silvers

    The first CMG World Robot Mount Tai Climbing Competition concluded on the course from Hongmen to Zhongtianmen in Tai'an, Shandong. The Unitree A2 robot dog won the legged robot sprint with a time of 43 minutes 41 seconds (actual 41 minutes 41 seconds plus a 2-minute penalty), using fully autonomous mode throughout to perceive and make decisions in real time on irregular stone steps.

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. 优宝特 · 微信公众号58

    Yobotics' "Xingzhe Taishan" autonomously climbs more than 3,100 stone steps on Mount Tai

    Yobotics' "Xingzhe Taishan" humanoid robot fully autonomously traversed more than 3,100 stone steps on Mount Tai at the first CMG World Robot Mount Tai Climbing Competition, relying on its own perception and decision-making systems. The robot is equipped with multimodal perception, autonomously identifies step edges and obstacles, builds a map of the mountain path and plans its route, and then dynamically adjusts stride length, step height and landing posture through its self-developed joint modules and motion-control cerebellum. The team said the competition was a real-world validation of its full-stack self-development approach, and that it will next advance deployment in scenarios such as mountain inspection and emergency rescue.

  4. Guyuehome40

    Deep Vision Reinforcement Learning for Autonomous Quadrotor Flight: AirGym Control Hierarchies and Depth Observation Design Overview

    For quadrotor obstacle avoidance, AirGym incorporates depth perception, low-level control, and sensor noise into a single training pipeline, and outlines five control hierarchies, depth observation designs, and reward structures. The article also records the engineering finding that Blackwell GPUs cannot run Isaac Gym.

  5. Guyuehome58

    python-control: State-Space Design and the Physical Closed Loop of an Inverted Pendulum

    Using python-control as the vehicle, the article breaks down state-space control design, covering controllability and observability criteria, pole placement, the algebraic Riccati solution for LQR, the dual observer, and frequency-domain margins. It also deploys discrete LQR and an energy-based swing-up strategy into a MuJoCo cart-inverted-pendulum closed loop.

  6. 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.

  8. Guyuehome45

    Dexterous Hand in Practice 08: Making a Single Joint Obedient — How to Implement Position PID Closed-Loop Control

    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.

  10. 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.

  12. OFweek Robotics58

    Unitree G1 overheats and withdraws from Mount Tai climb: why humanoid robots can't handle mountain climbing

    On November 2, at the first CMG World Robot Mount Tai Climbing Competition, the Unitree G1 developer edition withdrew due to overheating and was carried down the mountain by staff on a stretcher. The author argues the problem is not just cooling components, but a zero-sum contest inside the chassis among compute, battery, and heat dissipation for limited space and power. The G1 has a 9000mAh battery and a runtime on the order of about two hours; during continuous ascent, joint motors sustain high-torque output, accelerating thermal degradation. The article also cites CAICT report data: in the first half of the year, global humanoid robot shipments exceeded 22,000 units, with more than 60% going to entertainment performances and science education/data collection, while intelligent manufacturing scenarios accounted for about 13%.

  13. 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.

  14. 机器人全球资讯 · 微信公众号58

    First CMG World Robot Mount Tai Climbing Competition qualifier kicks off, legged robots challenge 3.8 km of stone steps in the rain

    On October 26, the qualifier of the first CMG World Robot Mount Tai Climbing Competition started on the trail from Tai Shan's Red Gate to the Mid-Heaven Gate, with multiple domestic teams fielding legged and wheel-legged hybrid robots. The course runs about 3.8 km and includes more than 3,100 steps. Rain fell during the competition, and the slippery stone steps tested the robots' balance control, perception and decision-making, and endurance. The event also features a legged-robot load-carrying race and an all-terrain mobility pathfinding challenge. Zhishen Technology's "Tongchui M1" has a maximum payload of 30 kg and can clear obstacles 80 cm high; Dongtai Technology's robot finished the speed race in about 58 minutes with roughly 80% battery remaining.

Nov 2Mon
  1. 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.

  2. 北京理工大学 · 微信公众号36

    CCTV features BIT swarm intelligence research group: "BIT Zhixingzhe" humanoid robot and quadruped robot dog unveiled

    The swarm control research group at the School of Mechatronical Engineering, Beijing Institute of Technology, presented platforms including the "BIT Zhixingzhe" humanoid robot and a quadruped robot dog on CCTV's program "Amazing, We Are 'Science' People." At the 2026 Beijing Yizhuang Humanoid Robot Half Marathon, "Zhixingzhe" completed the full 21-kilometer course, achieving zero falls and zero interruptions across more than ten types of complex terrain including urban roads, wetland parks, steep slopes, and near-90-degree sharp turns, and won second place for "Best Gait." The research group also independently developed Sigma, a simulation system for single-drone and swarm algorithms, which supports multi-scenario, multi-weather simulation training.

  3. Xbotics具身智能实验室 · 微信公众号20

    Xbotics Embodied Intelligence Community October Event Recap: OmniHand O10 Dexterous Hand Experience, Qinglong Nano Motion Control Training, and MiniDuck Replication

    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.

  5. 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.

  6. Guyuehome58

    PlaCo Bipedal Gait Analysis: ZMP-Constrained Trajectory Optimization and Weighted Inverse Kinematics

    Gu Yue Ju analyzes the PlaCo humanoid gait pipeline: a linear inverted pendulum trajectory optimization using jerk as the decision variable keeps the ZMP inside the support polygon, cubic splines connect the swing foot, and weighted QP inverse kinematics maps the center of mass and both foot targets into 26-dimensional joint velocities, completing continuous turning walking.

  7. 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

    PPO Enables Autonomous Balance and Navigation Control for a Bicycle Robot in PyBullet

    This study takes a bicycle robot with a reaction pendulum as its subject, derives the roll dynamics and the speed-dependent instability mechanism, and uses proximal policy optimization (PPO) to train coordinated control of the steering, rear wheel, and reaction pendulum. Experiments are carried out in PyBullet: natural fall, training, balancing, navigation, and disturbance recovery, concluding with obstacle-avoidance training.

  10. Guyuehome72

    Robot Joint Backlash Compensation: From Dual-Encoder Principles to Play Operator Modeling and Python Simulation

    The article addresses the backlash and lost motion problem in robot joint reducers by building a dual-inertia backlash transmission model described with a Play operator, and designing a direction-reversal state machine with rate-limited feedforward compensation. It quantitatively compares three control schemes through three sets of experiments and provides a Python simulation implementation path.

  11. Guyuehome58

    do-mpc: Robust Model Predictive Control with Multi-Stage Scenario Trees

    Using bridge crane anti-sway as the object, the article derives the composite pendulum dynamics formed by the trolley, a homogeneous suspension rod, and the payload, and presents the construction of a multi-stage scenario tree, non-anticipative input sharing, and an equally weighted expected objective. The authors conducted measurement-intermittent comparative experiments between nominal and robust controllers in the MuJoCo physics engine.

  12. 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.

  13. Guyuehome58

    Explaining Ruckig's jerk-limited time-optimal online trajectory generation

    The article explains Ruckig's jerk-limited online trajectory generation, covering the seven-segment profile of the triple-integrator-chain time-optimal problem, the selection of synchronization instants across multiple axes, and the closed-form solution for braking when limits are exceeded. It also presents measured tracking and target-jump replanning results for a two-joint arm in MuJoCo.