Trailer Coupler Localization via Sensor Fusion
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Solution Overview
Problem
Current systems lack the capability to autonomously detect and localize a trailer coupler in real-time, hindering the automated hitching process between a tow vehicle and a trailer.
Innovation Solution
A method and system utilizing data processing hardware that receives images from a rear camera, determines a region of interest, and combines sensor data from wheel encoders, acceleration sensors, and an inertial measurement unit to generate a 3D point cloud, allowing the tow vehicle to autonomously maneuver towards the coupler by projecting points onto camera and road planes and calculating distances for precise alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If real-time coupler detection and localization is implemented, then automated hitching capability is improved, but system complexity increases
Solution Approach 1:
The patent combines multiple sensor types (camera, LIDAR, ultrasonic sensors, wheel encoders, inertial measurement unit) into an integrated sensor system that feeds data to a single controller. This merging approach enables comprehensive automated hitching functionality while managing system complexity through centralized coordination rather than distributed control of multiple independent systems.
Solution Approach 2:
The controller performs multiple functions including processing data from various sensors, generating 3D point clouds, localizing the coupler in real-time, calculating distances, and controlling the towing vehicle's movement. This multi-functionality reduces the need for separate dedicated systems for each task, thereby improving automation extent while controlling overall system complexity.
2Measurement precision
If multiple sensors are integrated for accurate coupler localization, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent merges data from heterogeneous sensors (optical camera, laser-based LIDAR, acoustic ultrasonic sensors, and inertial measurement units) into a unified 3D point cloud representation. This combination leverages the complementary strengths of each sensor type to achieve high measurement precision for coupler localization while managing complexity through integrated processing in a single controller.
Solution Approach 2:
The controller acts as an intermediary that receives raw data from multiple complex sensors, processes and fuses this information into a coherent 3D point cloud, and outputs simplified localization results. This intermediary processing layer manages the complexity of multiple sensors by providing a unified interface and standardized data format for coupler localization.
3Speed
If 3D point cloud processing is performed in real-time, then coupler detection speed is improved, but computational requirements increase
Solution Approach 1:
The system performs preliminary processing by continuously capturing sensor data and pre-generating 3D point clouds even before coupler detection is initiated. This preliminary action allows the computationally intensive 3D processing to be distributed over time, enabling real-time detection speed while managing energy consumption through pre-computation during idle periods.
Solution Approach 2:
The sensor system and controller operate continuously to maintain an updated 3D point cloud representation of the environment. This continuous operation eliminates the need for repeated intensive processing when the coupler needs to be detected, as the data is already available in real-time, thereby improving detection speed while spreading computational energy consumption evenly over time rather than in intensive bursts.
Data Source
AI summary
A method for detecting and localizing a trailer coupler of a trailer is provided. The method includes receiving images from a camera positioned on a back portion of a tow vehicle and determining a region of interest within the images. The region of interest includes a representation of the trailer coupler. The method includes determining a camera plane and a road plane. In addition, the method includes determining a three-dimensional point cloud representing objects inside the region of interest and within the camera plane and the road plane. The method also includes receiving sensor data from a sensor system and determining a coupler location of the trailer coupler based on the 3D point cloud and the sensor data. The method also includes sending instructions to a drive system causing the tow vehicle to autonomously drive along a path in a rearward direction towards the coupler location.