Autonomous Vehicle Control Using Trained Navigable Areas
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Solution Overview
Problem
Existing vehicle navigation systems require manual navigation to multiple destinations, which is time-consuming, especially in environments with several possible paths, and lack efficient autonomous navigation to secondary goals after initial navigation.
Innovation Solution
A control system for vehicles that allows autonomous navigation to secondary goals by utilizing vehicle control data collected during a first maneuver, identifying navigable areas, and using sensors to detect the environment for path determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the vehicle navigates to multiple destinations manually, then the vehicle can reach various navigation goals, but the navigation process becomes time-consuming
Solution Approach 1:
The system performs preliminary actions by recording control inputs and environment data during manual navigation to a first destination. This recorded data is then reused for subsequent autonomous navigation to second and third destinations, eliminating the need to manually repeat the same navigation steps and significantly reducing time loss
Solution Approach 2:
The system creates a copy of the control inputs and navigation path from the first manual navigation. This copied data is then applied to generate autonomous navigation commands for reaching additional destinations, allowing the vehicle to replicate successful navigation patterns without manual intervention
2Adaptability or versatility
If the vehicle simply reverses the predetermined path to navigate in reverse direction, then the navigation is simple, but the vehicle cannot efficiently navigate to multiple possible destinations
Solution Approach 1:
The system makes the navigation path multi-functional by using the same recorded control inputs and environment data to reach multiple different destinations. The first navigation path serves as a template that can be adapted and modified to generate paths to second and third destinations, eliminating the need for separate manual navigation to each location
Solution Approach 2:
The system dynamically adapts the recorded navigation data by modifying control inputs based on current environment conditions and different destination requirements. This allows the same base navigation routine to be flexibly adjusted for reaching multiple different destinations rather than being static and destination-specific
Data Source
AI summary
Embodiments of the present invention provide a control system (100). The control system (100) is for a host vehicle (10) operable in an autonomous mode and a non-autonomous mode. The control system (100) comprises one or more controllers (110). The control system (100) is configured to receive, when operating in a non-autonomous mode, a mode signal and environment data. The mode signal is indicative of the host vehicle (10) operating in a training mode. The environment data is indicative of a sensed environment of the host vehicle (10) during a first manoeuvre by the host vehicle (10) from a first location to a first navigation goal. In the training mode, the one or more controllers (110) identify a navigable area and output vehicle control data. The navigable area is in a vicinity of the first manoeuvre and is suitable to contain a plurality of possible navigation paths for subsequent navigation of the host vehicle (10), operating in an autonomous mode, to a second navigation goal within the navigable area. The second navigation goal is different to the first navigation goal. The navigable area is identified in dependence on the environment data. The vehicle control data is indicative of the navigable area. When subsequently navigating to the second navigation goal in the autonomous mode, the control system (100) utilises the vehicle control data to autonomously control the host vehicle (10).