Drone Beacon Tracking with IMU Dead Reckoning and Optical Reset
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Solution Overview
Problem
Conventional object tracking systems are limited by sensing resolution, computational power, and sensitivity to environmental conditions, making them ineffective for real-time tracking of small or fast-moving objects and vulnerable to line-of-sight losses and adverse environmental factors like snow, fog, and low light.
Innovation Solution
An autonomous object tracking method using a drone equipped with a beacon device featuring an inertial measurement unit (IMU) and wireless transceiver, which performs dead reckoning and optical triangulation to maintain tracking even without line of sight, combining IMU measurements with optical data to correct for errors and maintain accurate location estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional machine vision systems are used for object tracking, then they can detect and track objects, but they are limited by sensing resolution and require enormous computational power
Solution Approach 1:
The tracking system is divided into two independent components: an IMU-based dead reckoning system for continuous position estimation and an optical system for periodic correction. This segmentation allows each component to operate with reduced computational requirements while maintaining overall tracking precision.
Solution Approach 2:
Dead reckoning based on IMU measurements serves as an intermediary mechanism that bridges the gap between optical detection events. It continuously estimates position without requiring enormous computational power, while optical data periodically corrects accumulated errors, thus reducing the overall computational burden compared to pure vision-based tracking.
2Measurement precision
If machine vision systems process data locally, then tracking accuracy is maintained, but the systems become bulky and not portable
Solution Approach 1:
The system replaces heavy local processing hardware with lightweight IMU sensors that require minimal processing power. The IMU continuously provides position estimates with minimal computational requirements, eliminating the need for bulky local vision processing hardware while maintaining tracking accuracy through periodic optical corrections.
3Reliability
If conventional machine vision systems are used, then they can track objects, but they are vulnerable to network interruption and high latency when processing is performed remotely
Solution Approach 1:
The IMU continuously calculates position estimates in advance without requiring network communication. This preliminary action ensures that tracking information is always available locally, eliminating network latency and ensuring reliability even when network connections are interrupted or experience high latency.
4Measurement precision
If machine vision systems are used for tracking, then they can locate objects, but they require maintaining line of sight with the target which limits utility when LOS is lost
Solution Approach 1:
The IMU-based dead reckoning system continuously estimates position without requiring line of sight to the target. This continuous operation maintains tracking capability even when optical line of sight is lost, while periodic optical corrections reset accumulated errors, ensuring both location accuracy and robustness against LOS losses.
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
The system provides robust, portable, and efficient object tracking resistant to line-of-sight losses and environmental challenges, ensuring accurate tracking of moving objects in various conditions by integrating IMU and optical data for precise location calculation.
Implementation Method 1
obtaining an initial location coordinate of a beacon device carried by the user, wherein the beacon device comprises at least an inertial measurement unit (IMU)
Implementation Method 2
performing optical triangulation to determine a relative position of the user with respect to the drone
Data Source
AI summary
Disclosed are technologies for autonomous tracking. An initial coordinate of a beacon device carried by a user is registered as a dead reckoning waypoint with a drone configured to track the user. The drone receives IMU measurements from the beacon as the user moves. For each IMU measurement, a displacement vector characterizing user movement is calculated. Estimated beacon locations are calculated by dead reckoning, based on the displacement vectors and the dead reckoning waypoint. Later, an updated dead reckoning waypoint is calculated by obtaining the current location coordinate of the drone and performing optical triangulation to determine a relative position of the user with respect to the drone. The updated dead reckoning waypoint does not depend on previously estimated beacon locations, and accumulated IMU/estimation error is eliminated. Tracking continues, where subsequent estimated locations of the beacon are calculated by dead reckoning based on the updated dead reckoning waypoint.