Natural-Language Vehicle Control via Object Detection
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Solution Overview
Problem
Conventional vehicle control systems require specific address information to determine routes and cannot handle natural-language instructions, limiting their ability to navigate based on temporary or dynamic objects and scenarios not mapped in their data.
Innovation Solution
A method and system that utilize natural-language guidance instructions and image data from cameras mounted on vehicles to identify targets and determine control commands, allowing vehicles to navigate without relying on fixed addresses, and adapt to changes in the environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional vehicle control systems use map-based navigation with fixed addresses, then route determination is reliable and precise, but the system cannot handle natural-language instructions and dynamic objects not in the map data
Solution Approach 1:
The patent introduces an intermediary system that translates natural-language instructions into visual object identification tasks. The natural language processing module converts spoken instructions into object detection queries, which are then processed by the computer vision system. This intermediary translation layer enables the vehicle to understand dynamic, unstructured language while maintaining reliable navigation through established object recognition and map-matching algorithms.
Solution Approach 2:
The navigation system is segmented into distinct functional modules: natural language processing, object detection, map data processing, and route determination. Each module handles specific tasks independently, allowing the system to process natural-language instructions without compromising the reliability of core navigation functions. The segmentation enables parallel processing of multiple data streams (language input, visual input, map data) to achieve both adaptability and reliability.
2Adaptability or versatility
If the system requires pre-mapped addresses for navigation, then route accuracy is high, but the system cannot navigate to temporary or dynamic locations
Solution Approach 1:
The system performs preliminary object detection and identification before final route determination. By pre-identifying dynamic objects (parked vehicles, pedestrians, temporary structures) and storing their visual characteristics in advance, the system can quickly match these objects to natural-language instructions and determine accurate destinations without requiring pre-existing map entries for every possible location.
Solution Approach 2:
The system continuously compares detected objects with natural-language instructions and provides feedback to refine destination identification. When the vehicle detects objects that match the described destination characteristics, it confirms the location and adjusts the route accordingly. This feedback loop enables accurate navigation to dynamic locations by iteratively refining the destination match based on real-time visual data and language instruction alignment.
3Adaptability or versatility
If the system uses natural-language processing and object detection, then flexibility in handling various instructions is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal object detection framework that serves multiple functions: identifying destinations from natural-language instructions, verifying route progress, detecting dynamic obstacles, and providing contextual information for navigation decisions. This multi-functional detection system reduces overall system complexity by consolidating what could be separate specialized modules into a single versatile computer vision platform that handles diverse tasks through a unified architecture.
Data Source
AI summary
The present disclosure relates to systems, devices and methods for vehicle control with natural-language guidance instructions. In one embodiment, a method is provided for control vehicle operation based on natural-language guidance instructions and image data detected by a camera mounted to a vehicle. One or more targets may be identified based on the guidance instructions to identifying vehicle position and/or operation. Object detection may be performed on the image data and control commands may be determined in response to the object detection. Operation of the vehicle may be controlled based on the control command. Natural-language guidance instructions can allow for directions and/or destinations to be provided without an operator or passenger of the vehicle having an address or map identifier of a destination. Processes and configurations are provided for confirming natural-language instructions and assessing image data to control vehicle operation.