Continuous Track Trajectory Control for Terrain Slip Compensation
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Solution Overview
Problem
Existing trajectory control systems for continuous track vehicles often result in skidding or dragging of the ground, causing positional slippage of one or more of the tracks across the ground, which makes it difficult to accurately estimate the center of rotation and/or future position of the continuous track vehicle given the planned trajectory of the continuous track vehicle given the steering operations, which can result in skidding or dragging of the tracks across the ground, which can result in positional slippage of one or more of the tracks across the ground, which can result in skidding or dragging of the tracks across the ground, causing positional slippage of one or more of the tracks across the ground, which can make it difficult to accurately estimate the center of rotation and/or future position of the continuous track vehicle given the current states of the vehicle and the planned velocities of the different tracks thereof.
Innovation Solution
Implementing an adaptive trajectory control system for continuous track vehicles using a model library of pre-trained models, such as Gaussian Process models, that generate control signals based on terrain classification and vehicle state inputs, allowing for individualized control of each track to account for terrain interactions and reduce errors between planned and actual trajectories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional steering operations are used to turn the vehicle by varying track speeds, then the vehicle can change direction, but skidding or dragging of the tracks occurs causing positional slippage and inaccurate trajectory estimation
Solution Approach 1:
The system employs feedback by continuously monitoring actual track positions and comparing them against planned trajectory positions. The feedback loop uses sensor data to detect deviations caused by skidding or dragging, then adjusts control signals to compensate for these errors in real-time, improving trajectory estimation accuracy while maintaining steering capability
Solution Approach 2:
The system performs preliminary action by pre-calculating compensation values for expected skidding and dragging based on terrain characteristics and vehicle state. Before executing steering maneuvers, the system adjusts the planned trajectory to account for anticipated slippage, thereby improving measurement precision without sacrificing steering responsiveness
2Ease of operation
If the tracks are slowed down or stopped during steering to enable turning, then the vehicle can pivot around a central point, but this causes skidding or dragging that results in positional slippage
Solution Approach 1:
The feedback mechanism continuously monitors the actual positions of both tracks during steering operations and compares them against the expected positions based on the pivot model. When skidding or dragging is detected through position deviations, the system generates compensatory control signals to correct the trajectory estimation, maintaining reliability despite the stopping/slowing of tracks during turns
Solution Approach 2:
The system dynamically changes parameters by adjusting track velocities and acceleration profiles based on real-time feedback from position sensors. During steering, the system modifies the velocity parameters of individual tracks to minimize skidding while achieving the desired turn, thereby maintaining position estimation reliability without compromising turning capability
Data Source
AI summary
Embodiments of a methodology for controlling a vehicle includes (i) determining a first command signal for a first locomotion component of a vehicle and a second command signal for a second locomotion component of the vehicle, (ii) based upon a terrain classification, selecting a first pre-trained model for the first locomotion component and a second pre-trained model for the second locomotion component, (iii) determining a first signal for the first locomotion component of the vehicle by utilizing the first command signal and the second command signal as input to the first pre-trained model and a second signal for the second locomotion component of the vehicle by utilizing the first command signal and the second command signal as input to the second pre-trained model, and (iv) controlling the first locomotion component of the vehicle using the first signal and the second locomotion component of the vehicle using the second signal.