AV Geocoding Trajectory Control for Hard-to-Reach Targets
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Solution Overview
Problem
Current systems for geocoding user-generated data are cumbersome and inefficient, particularly when data is collected from devices with different capabilities, and accessing or regularly geocoding data from objects in difficult or hard-to-reach locations is challenging.
Innovation Solution
An autonomous vehicle (AV) system that collects target data using sensors like sonar, infrared, and LIDAR, and a server that processes this data to determine an AV trajectory, motor control commands, and geocodes the data by comparing extracted target features to model data, enabling efficient geocoding of object data in real-time as the AV traverses a route.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional geocoding methods are used with specialized location-aware devices, then geocoding accuracy can be maintained, but device complexity and integration difficulty increase
Solution Approach 1:
The patent applies universality by enabling standard smartphones to perform geocoding functions previously requiring specialized devices. The system uses the smartphone's existing camera and processor to capture images and perform feature extraction, making the geocoding capability universal across common devices rather than requiring specialized location-aware equipment.
Solution Approach 2:
The patent introduces an intermediary server that receives images from smartphones, performs the complex geocoding processing, and returns location results. This mediator handles the computational complexity, allowing the client device to remain simple while still achieving accurate geocoding through the intermediary's processing capabilities.
2Measurement precision
If manual geocoding processes are used for user-generated data, then data accuracy can be verified, but time consumption and processing speed increase
Solution Approach 1:
The patent implements self-service by enabling automated geocoding that processes user-generated images without requiring manual intervention. The system automatically extracts features from images, compares them against databases, and determines locations, allowing the data to service itself rather than requiring human operators for each geocoding task.
Solution Approach 2:
The patent replaces manual mechanical geocoding processes with automated computational methods. Instead of human operators manually verifying and tagging locations, the system uses algorithmic feature extraction and automated image comparison to rapidly determine geocoding information, substituting mechanical human labor with automated computational systems.
3Quantity of substance
If traditional methods are used to access objects in difficult terrain, then data collection can occur, but accessibility and operational ease decrease
Solution Approach 1:
The patent uses copying by creating digital replicas of physical objects through image capture. Instead of requiring physical access to difficult-to-reach objects, the system captures images that serve as copies, which can then be processed and geocoded remotely. This allows data collection about inaccessible objects without requiring physical presence at challenging locations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Facilitates the efficient collection and geocoding of object data, even in challenging environments, by automating the process and integrating data from various sources, enhancing the accuracy and speed of geolocation tasks.
Implementation Method 1
An AV sensor determines an AV state
Implementation Method 2
The content generating device collects target data associated with a target
Implementation Method 3
The content generating device collects target data associated with a target
Data Source
AI summary
An Autonomous Vehicle (AV) system and method are described. The AV system is capable of determining a motor control command associated with an AV trajectory. The AV system includes a content generating device, a system controller, and an AV sensor. The content generating device collects target data associated with a target. The system controller is communicatively coupled to the content generating device. The system controller extracts target features from the target data. Also, the system controller compares the extracted target features to target model data to determine a target pose. Additionally, the system controller determines the AV trajectory by comparing the target pose with at least one target objective. The AV sensor determines an AV state. The system controller determines a motor control command associated with the AV trajectory based on the AV state, the target objective, and the AV trajectory.