Occupancy Map Synchronization Using Octree Data Structures
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Solution Overview
Problem
In scenarios where a follower vehicle lacks three-dimensional perception sensors, it faces challenges in receiving timely and efficient data from a leader vehicle for cognitive decision-aiding applications, leading to potential delays in responding to environmental objects due to the need for slow data transfer rates and delayed updates.
Innovation Solution
Implementing an occupancy map synchronization system that uses an octree data structure to efficiently transmit and update three-dimensional world model data between leader and follower vehicles, optimizing data transfer by using sub-trees and delta-trees to reduce bandwidth and processing requirements, ensuring rapid response and path adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If three-dimensional perception sensor data is transmitted from leader vehicle to follower vehicle, then follower vehicle can generate three-dimensional world model for cognitive decision-aiding applications, but data transfer rate is slow and response time is delayed
Solution Approach 1:
The occupancy map data is divided into discrete voxel elements and organized in an octree hierarchical structure, allowing selective transmission of only necessary spatial regions rather than complete datasets, thereby reducing transmission time while maintaining essential three-dimensional world model information
Solution Approach 2:
The system dynamically adjusts voxel resolution and octree depth parameters based on distance from leader vehicle and cognitive decision-aiding requirements, transmitting lower-resolution data for distant regions and higher-resolution data for nearby regions, optimizing the balance between data completeness and transmission speed
2Loss of information
If complete occupancy map data is transmitted to follower vehicle, then accurate three-dimensional world model is available, but bandwidth consumption increases
Solution Approach 1:
The occupancy map is segmented into hierarchical octree levels where only relevant voxel subsets are transmitted to the follower vehicle. The system identifies and transmits only the minimal necessary voxel data required for accurate cognitive decision-aiding, eliminating redundant information and reducing overall data volume while preserving essential spatial occupancy accuracy
Solution Approach 2:
Different regions of the occupancy map are transmitted at different resolution qualities based on their importance to the follower vehicle's cognitive decision-aiding. Regions closer to the follower vehicle or containing critical objects are transmitted with higher voxel resolution, while distant or less critical regions use lower resolution, optimizing bandwidth utilization while maintaining local accuracy where needed
Data Source
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AI summary
A method for occupancy map synchronization in multi-vehicle networks may include receiving three-dimensional perception sensor (3DPS) data. The method may include generating a data message including an occupancy map (OM) octree. The OM octree may be generated from an occupancy map constructed from the 3DPS data. The method may include reducing at least one of a messaging time or a messaging size of the data message including the OM octree. The method may include transmitting the data message including the OM octree via a leader vehicle controller communicatively coupled to a leader vehicle(102). The method may include receiving the data message comprising the OM octree via a follower vehicle controller (226) communicatively coupled to the follower vehicle. The method may include generating a local occupancy map from the data message comprising the OM octree via the follower vehicle controller (226).