Autonomous Vehicle Trajectory Correction Using Dual Coordinate Frames
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Solution Overview
Problem
Autonomous vehicles face discrepancies between planned and actual positions due to errors in position sensors or vehicle drift, leading to jerky movements and reduced operational safety.
Innovation Solution
A planning architecture that uses two coordinate frames (body-centric and Euclidian) to project and correct the vehicle's estimated state onto a planned trajectory, generating a new trajectory that is closer to the actual state, thereby reducing processing resources and improving decision and reaction times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the vehicle frequently corrects for position errors to maintain trajectory accuracy, then position precision is improved, but ride smoothness deteriorates due to irregular direction changes
Solution Approach 1:
The system performs preliminary projection of the estimated state onto the planned trajectory within the body-centric coordinate frame before generating correction commands. This preliminary action in a stable reference frame allows the system to anticipate and smooth out corrections before they are applied to the vehicle, preventing jerky movements while maintaining position accuracy.
Solution Approach 2:
The body-centric coordinate frame serves as an intermediary reference system between the vehicle's actual position and the planned trajectory. By performing projections and calculations in this intermediate frame rather than directly in the Earth-fixed frame, the system can generate smoother correction commands that account for the vehicle's orientation and motion state.
2Device complexity
If the system uses a single coordinate frame for trajectory planning and correction, then device complexity is reduced, but trajectory smoothness deteriorates due to frame transformation errors
Solution Approach 1:
The system segments the coordinate system usage into two distinct parts: the body-centric coordinate frame for projection and trajectory calculation, and the Earth-fixed coordinate frame for final correction output. This segmentation allows each coordinate frame to be used for its most suitable function, maintaining trajectory smoothness while managing complexity through clear separation of concerns.
Solution Approach 2:
Different coordinate frames are used for different aspects of the trajectory control problem. The body-centric frame is used locally for projection operations where stability relative to the vehicle is important, while the Earth-fixed frame is used for final correction commands where absolute position accuracy is important. This local optimization of coordinate frame selection improves overall trajectory smoothness.
3Reliability
If the vehicle corrects for position discrepancies in real-time, then operational safety is improved, but computational time increases due to complex trajectory recalculations
Solution Approach 1:
The system performs preliminary projection of the estimated state onto the planned trajectory within the body-centric coordinate frame before generating correction commands. This preliminary action in a stable reference frame allows the system to anticipate and smooth out corrections before they are applied to the vehicle, preventing jerky movements while maintaining position accuracy.
4Stability of the object's composition
If the system projects the estimated state onto the planned trajectory within the body-centric frame, then trajectory smoothness is improved, but device complexity increases due to dual coordinate frame management
Solution Approach 1:
The system segments the coordinate system usage into two distinct parts: the body-centric coordinate frame for projection and trajectory calculation, and the Earth-fixed coordinate frame for final correction output. This segmentation allows each coordinate frame to be used for its most suitable function, maintaining trajectory smoothness while managing complexity through clear separation of concerns.
Data Source
AI summary
Techniques for compensating for errors in position of a vehicle are discussed herein. In some cases, a discrepancy may exist between a measured state of the vehicle and a desired state as determined by a system of the vehicle. Techniques and methods for a planning architecture of an autonomous vehicle that is able to provide maintain a smooth trajectory as the vehicle follows a planned path or route. In some cases, a planning architecture of the autonomous vehicle may compensate for differences between an estimated state and a planned path without the use of a separate system. In this example process, the planning architecture may include a mission planning system, a decision system, and a tracking system that together output a trajectory for a drive system.