Autonomous Vehicle Obstacle Detection for Obscured Solar Panel Posts
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating and performing tasks near dynamic and obscured obstacles, such as solar panels and posts, due to limitations in GPS precision and availability, as well as obstacles created by changing solar panel orientations and vegetation growth.
Innovation Solution
The implementation of systems and methods that enable autonomous vehicles to real-time detect and determine the location and orientation of dynamic obstacles, such as solar panels, and infer the location of stationary obstacles, like posts, using direct sensing data from LIDAR and other sensors, even when these obstacles are obscured or dynamically changing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS coordinates are used for navigation, then the autonomous vehicle can locate obstacles, but the precision and availability are insufficient to navigate within desired proximity of obstacles
Solution Approach 1:
The patent introduces LIDAR and other sensing devices as intermediary tools between the autonomous vehicle and obstacles. These sensors directly detect obstacles and their positions, providing high-precision measurement data that compensates for GPS limitations. The sensing devices act as mediators that bridge the gap between coarse GPS location and precise obstacle positioning.
Solution Approach 2:
The patent replaces reliance on satellite-based GPS electromagnetic signals with direct optical and electromagnetic sensing using LIDAR and cameras. This substitution enables the vehicle to obtain precise obstacle location data through direct sensing rather than indirect satellite signal triangulation, improving both precision and reliability in GPS-denied environments.
2Use of energy by moving object
If solar panels are oriented dynamically for optimal sunlight exposure, then energy efficiency is improved, but the lower edge creates dynamically-changing navigational obstacles
Solution Approach 1:
The patent implements continuous real-time sensing and monitoring of solar panel positions and orientations. The autonomous vehicle continuously tracks the moving lower edges of solar panels through persistent LIDAR scanning and image processing, ensuring uninterrupted detection capability despite the panels' dynamic movement for energy optimization.
Solution Approach 2:
The system employs feedback mechanisms where sensor data about solar panel positions is continuously fed back to the navigation system. This real-time feedback loop allows the autonomous vehicle to adjust its path dynamically, responding to the changing lower edge positions of solar panels while they move to optimize energy capture.
3Ease of operation
If conventional sensing systems are used to detect posts, then detection is straightforward, but posts obscured by vegetation growth become difficult to detect
Solution Approach 1:
The patent employs a multi-functional sensing system that combines LIDAR, cameras, and other detection devices. Each sensor type serves multiple functions: LIDAR detects both unobscured and obscured posts through vegetation, cameras provide visual confirmation and contextual information, and the combined system maintains ease of operation while overcoming obscuration challenges.
Solution Approach 2:
The system implements nested sensing capabilities where multiple sensing layers operate together. Primary LIDAR detection penetrates vegetation to locate posts, while secondary camera systems and additional sensors provide complementary detection. This nested approach allows the system to maintain simple operation through integrated processing while detecting obscured obstacles through multiple redundant sensing pathways.
4Productivity
If the autonomous vehicle navigates close to obstacles to perform tasks, then task performance is improved, but the risk of collision with dynamic obstacles increases
Solution Approach 1:
The patent implements dynamic navigation where the autonomous vehicle continuously adapts its speed, position, and trajectory based on real-time obstacle detection. The system dynamically adjusts clearance distances from solar panels and posts, maintaining close proximity for efficient task performance while automatically increasing safety margins when dynamic obstacles are detected, thus balancing productivity and collision avoidance.
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
This approach allows autonomous vehicles to navigate and perform tasks, such as mowing, within a desired proximity of obstacles, ensuring safe and efficient operation even in complex and dynamic environments.
Implementation Method 1
directly sensing data from LIDAR and other sensors
Data Source
AI summary
Disclosed are solutions for an autonomous vehicle to real-time detect and determine dynamic and/or obscured obstacles to support navigation and services to within a desired proximity of said obstacles. Certain such implementations are specifically directed to autonomous mowers, for example, capable of real-time object detection to determine location and orientation of solar panels in a solar farm, for example, and based on the location and orientation of such solar panels further determine the location of their corresponding posts that may be otherwise obstructed from direct detection by the autonomous mower's other sensing systems possibly due to vegetation growth around the posts or other reasons.