Autonomous Vehicle Path Coordination Using UWB and Virtual Pathways
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Solution Overview
Problem
Current autonomous vehicle navigation systems require significant time and effort for programming and are vulnerable to environmental changes, lacking flexibility and reliability, and they often require substantial computing power, which affects battery life and operating range, while also failing to account for the presence of other vehicles or persons in the environment.
Innovation Solution
The system uses ultrawideband communication to define a series of origination and destination positions with positional coordinates, allowing for real-time location tracking and trajectory updates, enabling safe and efficient navigation by determining current positions and issuing control commands for autonomous vehicles to follow a virtually approved pathway, while also considering the presence of other vehicles and persons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If electronic sensors such as vision cameras and LiDAR are used for navigation, then the autonomous vehicle can perceive the environment, but significant time and effort are required for programming and training, and the system is vulnerable to environmental changes
Solution Approach 1:
The navigation system is segmented into two independent components: (1) a pre-programmed virtual pathway system that provides reliable route guidance, and (2) a machine learning module that handles dynamic obstacle detection and avoidance. This segmentation allows each component to specialize, with the virtual pathway ensuring reliability and the ML component providing adaptability to environmental changes.
Solution Approach 2:
A centralized server acts as an intermediary between the autonomous vehicle and the environment. The server stores and manages virtual pathways, receives real-time position data from the vehicle via RTLS, and dynamically updates the pathway based on environmental conditions. This intermediary decouples the vehicle's navigation logic from environmental variability, improving both reliability and adaptability.
2Extent of automation
If electronic sensors and computing systems are used for autonomous navigation, then the vehicle can operate autonomously, but significant computing power is required, affecting battery life and operating range
Solution Approach 1:
The computationally intensive tasks of pathway generation, position calculation, and route optimization are extracted from the autonomous vehicle and relocated to a centralized server. The vehicle's onboard computer only needs to execute simple navigation commands and communicate position data, dramatically reducing its computing power requirements and energy consumption while maintaining full autonomous navigation capability.
Solution Approach 2:
Instead of processing raw sensor data and making navigation decisions locally, the system uses lightweight copies of position data exchanged between the vehicle and server. The server creates virtual copies of the pathway and sends simplified navigation instructions to the vehicle, reducing the computational burden on the vehicle's onboard systems and extending battery life.
3Measurement precision
If individual location tracking systems are used, then the vehicle can determine its own position, but the system lacks awareness of other vehicles and persons in the environment
Solution Approach 1:
The system merges individual vehicle position tracking with centralized environmental awareness by combining RTLS technology with a server that aggregates position data from multiple vehicles and persons. The server creates a unified view of all entities in the environment, enabling each vehicle to awareness of others while maintaining precise individual position tracking through the continued use of RTLS infrastructure.
Data Source
AI summary
Apparatus and methods for controlling a path of an autonomous mobile device based upon defining a series of origination positions and destination positions, each destination position correlating with position coordinates. A current position of an autonomous vehicle is determined via location automation such as real time communication systems and an approved pathway is generated to guide the autonomous vehicle. The position coordinates may be a set of values that accurately define a position in two dimensional 2D or three-dimensional (3D) space. Position coordinates may include cartesian coordinates.