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World Humanoid Robot Games in Beijing Highlight Dance Competitions with Advanced Robotics

World Humanoid Robot Games in Beijing Highlight Dance Competitions with Advanced Robotics

The 2nd World Humanoid Robot Games are set to take place at the National Speed Skating Oval in Beijing from August 22 to 26. This event will feature a variety of competitions, with a significant focus on dance routines. The dance competitions are divided into street dance, cheerleading, and dancesport categories. These events require robots to perform complex routines autonomously, without human intervention. The dancesport competition, in particular, involves pairs of humanoid robots executing synchronized movements in styles such as waltz and samba. The scoring for these competitions is based on motion control, multi-robot coordination, and artistic choreography, judged by a panel of nine judges. The event aims to showcase the advanced capabilities of humanoid robots in replicating human dance movements.
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RoboBusiness 2026 Opens Registration for Robotics Industry Leaders

RoboBusiness 2026 Opens Registration for Robotics Industry Leaders

RoboBusiness 2026 Opens Registration for Robotics Industry Leaders
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MGI Engineering Develops Autonomous Vortex Aircraft for UK Defense Competition

MGI Engineering Develops Autonomous Vortex Aircraft for UK Defense Competition

MGI Engineering has unveiled its T-022 Vortex, an autonomous collaborative platform designed to work alongside crewed jets. The Vortex is being promoted as a potential solution for the UK's Royal Air Force's Storm Fighter requirement. With a maximum take-off weight of 3.5 tons and a range of over 2,160 nautical miles, the aircraft is capable of carrying a payload of up to 1 ton. It is designed for various missions, including intelligence gathering and electronic warfare.
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Industrial Sensor Design: Enhancing Safety and Reliability in Automated Systems

Industrial Sensor Design: Enhancing Safety and Reliability in Automated Systems

Industrial Sensor Design: Enhancing Safety and Reliability in Automated Systems
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Robotics Startup Generalist AI Seeks $3 Billion Valuation in New Funding Round

Robotics Startup Generalist AI Seeks $3 Billion Valuation in New Funding Round

Robotics Startup Generalist AI Seeks $3 Billion Valuation in New Funding Round
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Grip Develops AI-Driven Robotics for Waste Management

Grip Develops AI-Driven Robotics for Waste Management

Grip Develops AI-Driven Robotics for Waste Management
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DoorDash Launches Drone Delivery Program Following FAA Certification

DoorDash Launches Drone Delivery Program Following FAA Certification

DoorDash Launches Drone Delivery Program Following FAA Certification
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Fortescue's Autonomous Mining Truck Achieves Charging Milestone with 6-Megawatt System

Fortescue's Autonomous Mining Truck Achieves Charging Milestone with 6-Megawatt System

Fortescue's Autonomous Mining Truck Achieves Charging Milestone with 6-Megawatt System
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Kodiak Robotics Advances Autonomous Trucking with Simulation Expertise

Kodiak Robotics Advances Autonomous Trucking with Simulation Expertise

Kodiak Robotics Advances Autonomous Trucking with Simulation Expertise
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MIT Researchers Develop System to Enhance Robot Speed and Efficiency

MIT Researchers Develop System to Enhance Robot Speed and Efficiency

Researchers at MIT have developed a new system called VLASH, designed to improve the speed and efficiency of robots by enabling them to predict future states and plan actions accordingly. This system allows robots to overlap their thinking and execution processes, significantly reducing pauses between actions. The VLASH system uses vision-language-action (VLA) models to predict the robot's future state and plan subsequent actions while current tasks are being executed. This approach addresses the common issue of computational delays in robotic systems, enhancing their ability to react swiftly to environmental changes. The research, led by Associate Professor Song Han, will be presented at the Intelligent Robots and Systems Conference.
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Tsinghua University and ByteDance Develop Vision-Driven Soccer Skills for Humanoid Robots

Tsinghua University and ByteDance Develop Vision-Driven Soccer Skills for Humanoid Robots

Researchers from Tsinghua University and ByteDance have developed a unified reinforcement learning-based controller that enables humanoid robots to learn vision-driven reactive soccer skills. This innovation allows robots to coordinate agile locomotion with visual perception in dynamic environments. The robots are trained in simulation to acquire soccer behaviors, with Adversarial Motion Priors guiding policy learning towards natural motion patterns. The system introduces an encoder-decoder architecture and a virtual perception system to model key characteristics of onboard vision, exposing the policy to perceptual noise and detection failures during training. This approach has resulted in a controller that produces coordinated soccer behaviors using only onboard vision, achieving significant improvements in performance metrics.
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Enigma Secures $70 Million to Revolutionize Human-Robot Interaction

Enigma Secures $70 Million to Revolutionize Human-Robot Interaction

Enigma Secures $70 Million to Revolutionize Human-Robot Interaction