Humanoid robot falling control method, device and equipment and storage medium

By obtaining the status data of the humanoid robot in real time and using the model prediction control algorithm to judge the risk of falls, performing targeted fall protection actions, solving the shortcomings of fall prediction and protection in the existing technology, and improving prediction accuracy and protection effect.

CN119717618AActive Publication Date: 2025-03-28UBTECH ROBOTICS CORP LTD
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Patent Information

Application Number
CN202411854879.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-16
Publication Date
2025-03-28
Estimated Expiration
2044-12-16

AI Technical Summary

Technical Problem

The prior art has significant shortcomings in the fall prediction and protection of humanoid robots. The limitations of IMU data affect the accuracy of fall prediction, while existing protection solutions are difficult to deal with complex fall scenarios due to lack of flexibility and adaptability.

Method used

By obtaining state data including the center of gravity position, motion speed and acceleration in real time, a model prediction control algorithm is used to determine whether the humanoid robot has met the preset triggering conditions. If it is a high-risk fall state, it will perform fall protection actions, including adjusting the joint angle, lowering the center of gravity, and enabling the flexible collision function.

Benefits of technology

Improves the accuracy of fall prediction, provides a more flexible and timely response mechanism, reduces the risk of structural damage, and reduces the safety threat to surrounding people, and enhances the environmental adaptability and autonomy of the robot.

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Abstract

The invention provides a humanoid robot falling control method, device and equipment and a storage medium, and relates to the technical field of humanoid robots. The control method comprises the following steps: acquiring state data of the humanoid robot in real time; predicting the current state of the humanoid robot according to the state data; and if the current state is the high-risk tumble state, controlling the humanoid robot to execute tumble protection action. According to the fall control method for the humanoid robot, the accuracy of fall prediction is improved by monitoring the gravity center position, the movement speed and the acceleration in real time. The method can quickly start the protection action under the high-risk condition, reduce the damage risk and protect the safety of surrounding personnel. The adaptability and autonomy of the robot are enhanced, the stability and safety are improved, the maintenance cost is reduced, and the service life is prolonged, so that the practicability and market competitiveness of the robot are enhanced, and the application range is widened.
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