Locomotion Latest coverage

Inaugural CMG World Robot Mount Tai Competition Concludes with UTree Securing One Gold and Two Silver Medals

The inaugural CMG World Robot Mount Tai Competition concluded in Tai'an, Shandong. Beijing Lingyi Technology's team using the UTree A2 quadruped robot won the quadruped racing category with a final time of 43 minutes and 41 seconds after penalties. The Shanghai Gaoyi Technology team also used the A2 to take second place in racing, while the B2 model took second in the load-bearing race, carrying an effective load of 66kg (74kg total). During the event, a G1 development version retired due to overheating.

Laden with eggs, robots race up sacred Chinese mountain

Dozens of robots competed in the World Mountain Robot Challenge on Mount Tai in China's Shandong province, carrying fragile goods like eggs and watermelons up a 3.9-kilometer course with over 600 meters of ascent. A canine robot from Beijing Lingyi Technology won the four-legged speed category in 43 minutes and 41 seconds, while a humanoid robot from Zhishen Lingyue completed a shorter race in 27 minutes and 26 seconds. The event, organized by China Media Group, featured categories for fastest robots and best load-carrying machines, with some competitors collapsing or tumbling during the race.

Unitree G1 robot exits Mount Tai race due to overheating, carried down on stretcher

On November 2, 2026, a Unitree G1 development version robot withdrew from the inaugural CMG World Robot Mount Tai Race in Shandong Taian after overheating during competition. The operator safely retired the unit, which was then carried down the mountain by staff on a stretcher. The race featured multiple categories including humanoid racing and legged locomotion over a 3.9 km course with over 3,100 steps.

Online Learning of Heterogeneous Locomotion Dynamics under Reinforcement Learning Policies for Precise Loco-Manipulation

This research addresses the challenge of reusing pretrained locomotion policies for precise loco-manipulation by introducing an online method to learn closed-loop dynamics under frozen policies. The authors propose a contaminated Gaussian model combined with Gaussian processes and random Fourier features to approximate heterogeneous responses caused by unobserved latent conditions. By weighting online updates based on the probability of predictable responses, the method reduces bias and fluctuations in dynamics estimates. Model predictive control (MPC) is then used for accurate floating-base motion prediction. The study establishes a finite-sample error bound ensuring uniform convergence and demonstrates consistent end-effector tracking with errors of 0.01 m across various manipulator configurations and tasks through both simulation and hardware experiments.

Joint-Health-Aware Reinforcement Learning for Robust Robot Control Under Actuator Degradation

This paper introduces a joint-health-aware reinforcement learning framework designed to maintain robust robot control despite actuator degradation. The method encodes actuator condition in a continuous joint-health vector and models degradation as multiplicative attenuation of actions, using a HealthNet estimator to infer per-joint health from observations. Evaluated on Walker, Go2, Cassie, and Panda-based tasks under diverse degradation masks, the approach outperforms nominal baselines, with task-level locomotion returns improving by up to 250.1% and manipulation success rates by up to 15.2 percentage points relative to the nominal baseline.

Humanoid Robots Face Rainy Conditions at Inaugural Mount Tai Competition

On October 26, the qualifying round of the inaugural CMG World Robot Mount Tai Competition took place at the Mount Tai scenic area. Due to rain, the humanoid robot racing segment was cancelled, while other robots conducted outdoor tests wearing makeshift raincoats. Prior to this, on October 22, local team Shandong Youbaote Intelligent Robotics Co., Ltd. tested its 'Xingzhe Taishan E1' robot on irregular stone steps, having previously optimized its foot sole structure to handle the challenging terrain.

Embodied AI Robots Face Real-World 'Final Exam' in Shanghai

The 2026 Global Developer Pioneer Conference and International Embodied AI Skills Competition was held in Shanghai, featuring a rigorous real-world testing environment with nine major tracks and 23 competition items. The event highlighted the gap between simulated and real-world performance, where robots trained on billions of yuan failed to perform effectively in actual home settings. Key scenarios included industrial inspection tasks like navigating complex terrain and reading gauges within 30 minutes, and retail operations requiring stable manipulation of soft-packaged goods without spilling. Post-event, a 2,000-square-meter space was permanently converted into a training and validation platform for embodied AI robots, focusing on manufacturing, commercial services, and public utility applications.

URKL Global Humanoid Robot Free Fighting League Advances Real-World Evaluation of Motion Control and Adaptability

The first URKL global humanoid robot free fighting league's 32-to-16 round concluded with 16 teams advancing, each receiving a T800 robot for algorithm development and real-world testing. The event evaluates motion control, dynamic balance, and environmental adaptation through standardized challenges, offering a unified platform for algorithmic and engineering validation across diverse teams.

Video Friday: Spot Demonstrates Whole-Body Manipulation

IEEE Spectrum's Video Friday highlights Spot's whole-body manipulation capabilities, along with other robotics projects such as humanoid mobility, robotic hands, and specialized industrial robots. The video also includes demonstrations of AI-driven drone racing and energy-efficient amphibious robots, showcasing the breadth of current robotics innovation.

Digu Robot and URS Robotics Launch Embodied Intelligence Education Solution with SunRay S100

At the Changsha Education Equipment Expo, Digu Robot and URS Robotics announced a strategic partnership to develop an embodied intelligence education solution. The collaboration aims to expand into industrial applications and build a scalable educational model.

Robotic Systems Lab@leggedrobotics· 10:12SignalEditorial score6565

The ETH Robotic Systems Lab introduces 'Anticipated Perception for Humanoid Locomotion,' a new method that prioritizes terrain perception for the feet's upcoming landing points, aiming to enhance stability and navigation in humanoids.

KAIST Humanoid v0.9 Robot Pushes 77 Pounds and Lifts 44 While Walking

KAIST's Humanoid v0.9 uses deep reinforcement learning and onboard vision to coordinate walking with heavy loads, pushing 35 kg (77.2 lb) and lifting 20 kg (44.1 lb) while walking without external cameras. The demonstration highlights the challenge of whole-body locomanipulation, balancing forces during physical interaction with objects.

Rollbot 2: Agile Locomotion by a Single-Actuator Spherical Robot

Rollbot 2 improves upon the original Rollbot by maintaining a single-actuator design while introducing a redesigned mass distribution for more direct movement. It uses onboard inertial and ultra-wideband sensing to autonomously navigate toward beacons and follow waypoints, achieving a 468-meter indoor route at 0.87 m/s and completing a 4.8-meter 'N' benchmark in 10.8 seconds with a mean deviation of 7 cm.

Push the Limit: Learning High-Speed Sprinting and Aggressive Cornering on a Full-Scale Humanoid

This paper presents a learning-based framework that enables a full-scale bipedal humanoid to sprint at over 7 m/s with motion-prior-guided gait and perform aggressive cornering at high speed with a pronounced trunk lean of up to 25°. The framework addresses challenges like high-frequency yaw-rate oscillations and skill-specific reward design through causal multi-head attention and skill-conditioned discriminators, achieving stable high-speed sprinting and aggressive cornering in both simulation and real-robot deployment.

Soft Robotic Fish Combines High-Speed Swimming with 3D Maneuverability

Researchers from the Shenyang Institute of Automation have developed a soft robotic fish that can swim at high speeds and perform agile three-dimensional maneuvers. The design integrates a rigid–flexible coupled propulsion system with dynamic buoyancy regulation, inspired by biological mechanisms such as muscle-skeleton coordination and swim bladder function. The robotic fish achieves a maximum speed of 2.13 body lengths per second and can perform complex 3D movements like turning, ascending, and spiral ascent, offering a potential approach for high-performance underwater robots.

Next-gen hopping robot is the smart flea we didn't know we needed

Engineers at the University of Washington have developed DirectHop, a hopping robot inspired by the flea's energy-efficient jumping mechanism. The robot can jump up to 50 times its body height and is controlled via an external power source. Future versions may include onboard batteries and sensors, with the goal of creating an independent robot-explorer for tasks like environmental monitoring and inspection.

Feather star-inspired underwater robot gets 3D maneuverability from only two actuators

Researchers have developed an aquatic soft robot inspired by feather stars that can move in all three dimensions using only two actuators. The design utilizes mechanical intelligence to achieve efficient 3D maneuverability through three modes: jellyfish, fish, and rotor. The robot can explore underwater spaces, lift objects, and work collaboratively with other robots, with future plans to develop a fully wireless version.

Robotic Systems Lab@leggedrobotics· 16:29SignalEditorial score7878

The team at ETH Robotic Systems Lab demonstrated high-speed rough-terrain locomotion on ANYmal using an automatic curriculum learning approach called LP-ACRL. This method dynamically samples terrain types, difficulty levels, and velocity commands based on policy performance, without requiring pre-defined training sequences. The work was presented at RAL 2026.

Small robot propulsion: low-power twisting enables hopping, swimming

Researchers at the University of Michigan and UCLA have developed a new propulsion mechanism for small robots using low-power twisting of elastic rods. This method enables hopping and swimming motions by utilizing snapping mechanics. The mechanism works on challenging surfaces such as slippery cloth and grass-covered ground, producing frog-like motion. The study, published in Science Advances, was co-led by Khalid Jawed and Xiaonan (Sean) Huang, and demonstrates the potential for miniature robots to maneuver over uneven or slippery terrain.

F.03 Arrives at BMW

Figure's latest generation robot, F.03, has arrived at BMW Group Plant Spartanburg, demonstrating advanced dynamic whole-body control and sequencing use cases. Powered by Helix 02, the robot performs complex material manipulation tasks that require both precision and force, marking progress in embodied AI for manufacturing.