Project Overview
This implementation case demonstrates advanced Physical Intelligence (PI) based sports robot technology realized through the quadruped robot ANYmal-D developed at ETH Zurich, Switzerland. ANYmal-D is a cognitive robot capable of engaging in actual badminton rallies with humans through reinforcement learning. It recognizes the trajectory of the shuttlecock using only on-board sensors without external sensors and performs agile plays by moving strategically using its entire body. This project is drawing attention as a practical demonstration of situational responsive automation technology, where robots judge and react independently in dynamic environments, going beyond simple automation.
Project Background & Objectives
Background
Conventional autonomous robots typically had limitations in performing repetitive tasks or following fixed trajectories in static environments. However, in unpredictable situations such as sports, advanced automation technology capable of real-time perception, judgment, and motion control is required. The research team at ETH Zurich pursued the ANYmal-D project with the goal of developing a robot system equipped with human-level athletic intelligence.
Objectives
Implementing autonomous responsive motion control in unstructured environments
Developing an integrated perception-motion system using on-board sensors
Technical demonstration of sports-type robots capable of collaborating with humans
Testing reinforcement learning algorithms based on Physical Intelligence (PI)
Components
| Robot | Robot ANYmal-D: A cognitive robot combining quadruped-based mobility with upper-body manipulation functions Robot Arm Actuator: A dedicated motion unit capable of holding a racket and striking |
|---|
Workflow
| STEP 1. | Detect shuttlecock and identify based on color using on-board sensors. |
|---|---|
| STEP 2. | Predict the trajectory of the shuttlecock and calculate the target landing point. |
| STEP 3. | Select movement strategy (Stop/Run/Jump, etc.). |
| STEP 4. | Counterattack the shuttlecock by swinging the racket with appropriate timing and posture. |
| STEP 5. | Automatically return to the center of the court after striking and prepare for the next move. ※ Notice: Unauthorized copying or recreation of any content within Marosol may violate the Unfair Competition Prevention Act and the Copyright Act. |
※ The content provided by Bigwave Robotics is protected under U.S. and Canadian copyright and intellectual property laws. Unauthorized reproduction, distribution, or use of this content is strictly prohibited.
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Project Overview
This implementation case demonstrates advanced Physical Intelligence (PI) based sports robot technology realized through the quadruped robot ANYmal-D developed at ETH Zurich, Switzerland. ANYmal-D is a cognitive robot capable of engaging in actual badminton rallies with humans through reinforcement learning. It recognizes the trajectory of the shuttlecock using only on-board sensors without external sensors and performs agile plays by moving strategically using its entire body. This project is drawing attention as a practical demonstration of situational responsive automation technology, where robots judge and react independently in dynamic environments, going beyond simple automation.
Project Background & Objectives
Background
Conventional autonomous robots typically had limitations in performing repetitive tasks or following fixed trajectories in static environments. However, in unpredictable situations such as sports, advanced automation technology capable of real-time perception, judgment, and motion control is required. The research team at ETH Zurich pursued the ANYmal-D project with the goal of developing a robot system equipped with human-level athletic intelligence.
Objectives
Implementing autonomous responsive motion control in unstructured environments
Developing an integrated perception-motion system using on-board sensors
Technical demonstration of sports-type robots capable of collaborating with humans
Testing reinforcement learning algorithms based on Physical Intelligence (PI)
Components
| Robot | Robot ANYmal-D: A cognitive robot combining quadruped-based mobility with upper-body manipulation functions Robot Arm Actuator: A dedicated motion unit capable of holding a racket and striking |
|---|
Workflow
| STEP 1. | Detect shuttlecock and identify based on color using on-board sensors. |
|---|---|
| STEP 2. | Predict the trajectory of the shuttlecock and calculate the target landing point. |
| STEP 3. | Select movement strategy (Stop/Run/Jump, etc.). |
| STEP 4. | Counterattack the shuttlecock by swinging the racket with appropriate timing and posture. |
| STEP 5. | Automatically return to the center of the court after striking and prepare for the next move. ※ Notice: Unauthorized copying or recreation of any content within Marosol may violate the Unfair Competition Prevention Act and the Copyright Act. |
※ The content provided by Bigwave Robotics is protected under U.S. and Canadian copyright and intellectual property laws. Unauthorized reproduction, distribution, or use of this content is strictly prohibited.
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Indoor Logistics Transport and Loading Using VisionNav VNPA15🏗️
AMR Logistics Robots Introduced to Manufacturing Factory ✨ Logistics Automation that Quickly Resolves Even 1 Ton of Waste Derbris (2 KUKA KMP 1500P Logistics Robots)