Legged Robot CoM Estimation Using ZMP-Based Inverted Pendulum
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Solution Overview
Problem
Existing methods for estimating the state of a biped robot, particularly the position of the center of mass (CoM), are inaccurate due to reliance on the supporting position of the ankle, which does not fully consider the influence of the zero-moment point (ZMP) changes.
Innovation Solution
A robot state estimation method that calculates the ZMP of the legs in a world coordinate system based on force information from six-dimensional force sensors, and then uses this ZMP as the supporting point in a linear inverted pendulum model to accurately estimate the CoM position and velocity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the CoM position is estimated based on the supporting position of the ankle, then the estimation method is simple, but the accuracy of CoM estimation is poor
Solution Approach 1:
The patent introduces ZMP (zero-moment point) as an intermediary parameter to bridge the gap between force sensor measurements and CoM estimation. By calculating ZMP position from force sensor data and using it as a mediator in the inverted pendulum model, the system achieves accurate CoM estimation without directly measuring ankle position, thus resolving the contradiction between simplicity and accuracy
Solution Approach 2:
The patent replaces the traditional mechanical approach of directly measuring ankle position with a computational approach using force sensors and inverted pendulum dynamics. This substitution allows the system to derive CoM position through force measurements and ZMP calculations rather than direct mechanical position sensing, improving accuracy while maintaining computational efficiency
2Measurement precision
If the ZMP position is calculated using force information from six-dimensional force sensors, then the accuracy of CoM estimation is improved, but the device complexity increases
Solution Approach 1:
The patent makes the six-dimensional force sensor multi-functional by using it not only for force measurement but also for ZMP position calculation and CoM estimation. This universal utilization of the force sensor data eliminates the need for additional position sensors, thereby improving measurement precision without proportionally increasing device complexity
Solution Approach 2:
The patent transforms the raw force sensor measurements into ZMP position parameters through coordinate transformation and moment calculation. By changing the parameter representation from direct force values to derived ZMP positions, the system achieves accurate CoM estimation while the computational complexity is managed through efficient parameter transformation rather than additional hardware
Data Source
AI summary
A robot state estimation method, a computer-readable storage medium, and a legged robot are provided. The method includes: obtaining force information of a left leg of a robot and a right leg of the robot; calculating a ZMP of the robot in a world coordinate system based on the force information of the left leg and the force information of the right leg; and calculating a position of a center of mass (CoM) of the robot based on a preset linear inverted pendulum model. In this manner, a brand-new linear inverted pendulum model is constructed in advance, which uses the ZMP of the robot as a supporting point of the model, thereby fully considering the influence of the change of the position of the ZMP of the robot on the position of the CoM.