Free Space Polygon Estimation for Real-Time Autonomous Movement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies for estimating free space around moving vehicles are computationally intensive, require large data storage, and cannot provide real-time, accurate data for dynamic environments, especially during unforeseen changes.
Innovation Solution
A computationally efficient, data-lightweight free space estimator system that uses a combination of ultrasonic and camera sensors to generate a virtual polygon representing the boundary of free space around a vehicle, employing AI models and neural networks for accurate and efficient data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If occupancy grid generation is used to provide detailed understanding of free space, then measurement precision is improved, but device complexity and computation time increase significantly
Solution Approach 1:
The patent segments the continuous occupancy grid representation into discrete virtual polygon boundaries. Instead of processing every cell in a high-resolution grid, the system identifies and processes only the critical boundary elements that define free space limits, significantly reducing computational complexity while maintaining estimation accuracy.
Solution Approach 2:
The patent extracts only the essential boundary information from the environment data to create virtual polygons. Rather than processing the complete occupancy grid, the system extracts key geometric features (vertices and edges) that define the free space boundaries, reducing data volume and computation while preserving the necessary precision for autonomous navigation.
2Measurement precision
If occupancy grid generation is used to provide high-detail free space understanding, then measurement precision is improved, but loss of time increases due to computationally intensive processing
Solution Approach 1:
The patent segments the processing task from generating complete occupancy grids to only identifying virtual polygon boundaries. This segmentation allows the system to achieve sufficient precision for navigation decisions without the time cost of processing the entire grid, enabling real-time response to dynamic environmental changes.
Solution Approach 2:
The patent applies partial action by generating only the necessary portion of the environmental model (virtual polygons defining free space boundaries) rather than the complete occupancy grid. This partial modeling approach provides sufficient accuracy for autonomous movement while dramatically reducing processing time and computational resource requirements.
3Measurement precision
If occupancy grid generation is used to provide comprehensive free space data, then measurement precision is improved, but quantity of substance (data storage volume) increases
Solution Approach 1:
The patent extracts only the essential boundary geometry (vertices and edges) from the environmental data to represent free space. This extraction creates a compact virtual polygon representation that occupies minimal storage space while maintaining the precision needed for navigation, avoiding the need to store large occupancy grid datasets.
Solution Approach 2:
Instead of generating detailed occupancy grids and then extracting boundaries, the patent inverts the approach by directly generating simplified virtual polygon representations from sensor data. This inverted workflow produces the necessary precision information in a compact format from the start, eliminating the need for large data storage.
4Measurement precision
If traditional free space estimation methods are used, then measurement precision is improved, but productivity decreases due to inability to provide real-time data for moving vehicles
Solution Approach 1:
The patent creates a dynamic free space estimation system where virtual polygons are continuously updated based on real-time sensor data from moving vehicles. The system adapts to the vehicle's motion and environmental changes, maintaining precision while enabling real-time productivity through efficient boundary-based representation and updates.
Data Source
AI summary
One or more embodiments herein can enable identification of an obstacle free area about an object. An exemplary system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise an obtaining component that obtains raw data defining a physical state of an environment around an object from a vantage of the object, and a generation component that, based on the raw data, generates a dimension of a portion or more of a virtual polygon representing a boundary about the object, wherein the boundary bounds free space about the object. A sensing sub-system can comprise both an ultrasonic sensor and a camera that can separately sense the environment about the object from the vantage of the object to thereby generate separate polygon measurement sets.