Lower Limb Exoskeleton Trajectory Planning with Time-Based Phases
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Solution Overview
Problem
Existing trajectory planning methods for lower limb exoskeletons rely on state-related phase variables that require multiple sensors, which can be unreliable when sensors are lacking, affecting stability and increasing the risk of accidents such as tipping over.
Innovation Solution
A method using time-related phase variables for trajectory planning, based on Hybrid Zero Dynamics (HZD), which reduces sensor reliance by employing dynamic analysis to determine a state space equation and an objective function, allowing for offline nonlinear optimization and interpolation to generate accurate gait trajectories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If state-related phase variables are used for trajectory planning, then trajectory planning can be performed, but sensor dependency increases and reliability decreases when sensors are lacking
Solution Approach 1:
The patent extracts the dependency on state-related phase variables and their associated sensors by introducing time-related phase variables instead. This removes the need for multiple sensors while maintaining trajectory planning capability, directly resolving the contradiction between reliability and device complexity
Solution Approach 2:
The patent changes the parameter basis from state-related phase variables (requiring sensor measurements) to time-related phase variables (using time as the independent variable). This parameter substitution eliminates sensor dependency while preserving the ability to perform trajectory planning, thereby improving reliability without increasing device complexity
2Measurement precision
If multiple sensors are used for trajectory planning, then state-related phase variables can be obtained, but system complexity increases and stability may be compromised when sensors fail
Solution Approach 1:
The patent removes the requirement for multiple sensors by extracting the essential timing information needed for trajectory planning. By using time-related phase variables, the system obtains necessary measurement data without relying on complex sensor arrays, thus reducing device complexity while maintaining measurement precision through temporal rather than spatial sensing
3Productivity
If sensor-based trajectory planning is used, then gait trajectories can be generated, but the risk of accidents increases when sensors are lacking or fail
Solution Approach 1:
The patent enables the exoskeleton system to perform trajectory planning using its own internal timekeeping mechanism rather than relying on external sensors. This self-service approach uses the system's inherent time variable to generate gait trajectories, ensuring continuous operation and maintaining walking stability even when external sensors are lacking or fail
Data Source
AI summary
A trajectory planning method for a lower limb exoskeleton includes: determining a state space equation corresponding to the lower limb exoskeleton using dynamic analysis; determining an objective function for trajectory planning of the lower limb exoskeleton according to the state space equation, wherein a phase variable corresponding to the objective function is a time-related phase variable; and performing trajectory planning of the lower limb exoskeleton according to the objective function to obtain a first gait trajectory corresponding to the lower limb exoskeleton, wherein the first gait trajectory is a gait trajectory corresponding to the time-related phase variable.