Legged Robot Motion Control with Adaptive Foothold Planning
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Solution Overview
Problem
Existing legged robot motion control methods fail to accurately determine a center of mass position that conforms well to the actual motion process, leading to low adaptability and difficulty in completing motion trajectories.
Innovation Solution
A method that acquires center of mass state data, determines candidate footholds, and calculates a target center of mass position variation coefficient and foothold using a constraint set, allowing for improved adaptability by generating a center of mass motion trajectory and selecting footholds automatically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a center of mass position is determined according to a kinetic equation for a legged robot, then the calculation is simple, but the adaptability to actual motion process is poor
Solution Approach 1:
The patent transforms the center of mass position determination from a direct kinetic equation approach to a parameter optimization approach. By introducing center of mass position variation coefficients and using iterative optimization algorithms, the system adjusts parameters to find the optimal center of mass position that satisfies both the kinetic equation and the actual motion constraints, thereby improving adaptability while maintaining calculation feasibility
Solution Approach 2:
The patent implements a feedback mechanism where the determined center of mass position is evaluated against actual motion process constraints. The system uses the evaluation results to adjust the center of mass position variation coefficients iteratively, creating a closed-loop control that continuously improves the adaptability of the center of mass position to the actual motion process
2Loss of time
If a center of mass motion trajectory is generated without considering actual motion process, then the trajectory generation is fast, but the robot difficulty to complete the motion process
Solution Approach 1:
The patent performs preliminary action by pre-establishing the variation relationship between center of mass position and foot contact force, and pre-defining constraint sets for foothold selection. This preliminary preparation allows the trajectory generation to quickly reference pre-computed relationships while still ensuring motion completion reliability through the pre-established physical constraints
Solution Approach 2:
The patent introduces dynamics by making the center of mass position adaptive rather than fixed. The system dynamically adjusts the center of mass position based on the variation relationship and constraint satisfaction, allowing the trajectory to be both generated quickly and completed reliably through real-time adaptation to motion constraints
3Device complexity
If footholds are not selected automatically, then the control process is simple, but the adaptability to complex paths and terrains is reduced
Solution Approach 1:
The patent implements self-service by enabling the system to automatically select footholds based on the variation relationship and constraint sets. The system serves itself by using the determined center of mass position variation coefficients to automatically identify suitable footholds that satisfy both the kinetic equation and spatial constraints, thereby improving adaptability to complex paths without requiring manual intervention
Solution Approach 2:
The patent applies segmentation by separating the foothold selection process into distinct constraint categories (spatial constraints, contact force constraints, etc.). This segmentation allows the system to evaluate different foothold candidates against specific constraints independently, making the automatic selection process more manageable and adaptable to complex terrains while maintaining controlled complexity
Data Source
AI summary
A legged robot motion control method, apparatus, and device, and a storage medium. The method includes: acquiring center of mass state data corresponding to a spatial path starting point and spatial path ending point of a motion path; determining a candidate foothold of each foot in the motion path based on the spatial path starting point and the spatial path ending point; determining a variation relationship between a center of mass position variation coefficient and a foot contact force based on the center of mass state data; screening out, under restrictions of a constraint set, a target center of mass position variation coefficient and target foothold that satisfy the variation relationship; determining a target motion control parameter according to the target center of mass position variation coefficient and the target foothold; and controlling a legged robot based on the target motion control parameter to move according to the motion path.