Follower Vehicle Path Generation for Smooth Relative Positioning
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Solution Overview
Problem
Conventional methods for guiding a follower vehicle to maintain a specific relative distance from a leader vehicle during material transfer suffer from errors and noise due to latency and yaw changes, leading to harsh steering commands and discomfort for the driver and passengers.
Innovation Solution
A kinematic model, such as a bicycle model, is used to predict the leader vehicle's position and generate a navigable path for the follower vehicle, iteratively adjusting the steering angle and speed to minimize errors and ensure smooth navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to guide the follower vehicle to maintain relative distance, then the positioning function is achieved, but errors and noise due to latency and yaw changes cause harsh steering commands
Solution Approach 1:
The system predicts the leader vehicle's future position and orientation based on current motion states before generating steering commands. This preliminary prediction compensates for latency effects, allowing the follower vehicle to plan smooth trajectories in advance rather than reacting to delayed position data, thereby reducing harsh steering adjustments
Solution Approach 2:
The system continuously monitors the leader vehicle's position, orientation, and motion parameters, and uses this feedback to dynamically adjust the predicted trajectory. By incorporating real-time feedback on relative position errors and leader vehicle yaw changes, the system can smooth out navigation commands while maintaining accurate relative positioning
2Measurement precision
If the follower vehicle adjusts steering frequently to maintain precise relative positioning, then positioning accuracy is improved, but driver comfort deteriorates due to harsh steering commands
Solution Approach 1:
The system dynamically adjusts the navigation trajectory by continuously predicting the leader vehicle's motion and recalculating optimal control points. Instead of rigid, frequent steering corrections, the system generates smooth, adaptive paths that account for changing relative positions and orientations, maintaining positioning accuracy while reducing harsh steering commands
Solution Approach 2:
The system changes the parameter representation from direct position control to predicted trajectory control. By using predicted future positions and orientations of the leader vehicle, the system transforms the control problem into one that naturally produces smoother steering commands while maintaining the required relative positioning accuracy
3Productivity
If conventional path generation methods are used, then basic navigation is achieved, but resource consumption increases due to computational overhead
Solution Approach 1:
The path generation process is segmented into distinct computational stages: predicting leader vehicle motion, calculating control points, generating trajectory segments, and executing steering commands. This segmentation allows the system to process information in manageable chunks, reducing overall computational overhead while maintaining navigation efficiency
Data Source
AI summary
Vehicles, methods, and non-transitory computer-readable media are provided for dynamic path generation. A vehicle including a steering mechanism, and processing circuitry configured to cause the follower vehicle to generate a control point based on a first model and location information corresponding to a leader vehicle, the first model corresponding to the follower vehicle, and the location information including a location of the leader vehicle and a heading of the leader vehicle, generate at least a portion of a path based on the control point, the path being toward a first position relative to the leader vehicle, and control a steering angle of the steering mechanism based on the at least the portion of the path.