Autonomous Mower Panel Detection for Obscured Post Navigation
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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, especially in environments like solar farms where obstacles change orientation and obstruct GPS signals.
Innovation Solution
The implementation of real-time obstacle detection systems using LIDAR data for autonomous vehicles, which allow for continuous 360-degree sensing and computational adjustments for vehicle motion, enabling the determination of dynamic and stationary object locations and orientations, even when obscured, to navigate safely and efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS coordinates are used for navigation, then the autonomous vehicle can operate with simple positioning, but the precision and availability are insufficient to navigate within desired proximity of obstacles
Solution Approach 1:
The patent combines multiple sensing systems (LIDAR, cameras, GPS) into an integrated obstacle detection system. The LIDAR directly senses the environment to produce direct sensing data, while cameras capture images for processing. These multiple sensing modalities are merged to compensate for individual system limitations and achieve the required positioning precision for navigating near obstacles.
Solution Approach 2:
The patent introduces LIDAR as an intermediary sensing device between the autonomous vehicle and obstacles. The LIDAR serves as a mediator that directly measures obstacle locations and orientations, bridging the gap between GPS coordinates and precise obstacle positioning. This intermediary system enables the vehicle to determine locations of both dynamic and stationary objects with the necessary accuracy.
2Difficulty of detecting and measuring
If the autonomous vehicle uses conventional sensing means, then the system structure is simple, but it cannot detect obscured stationary objects like posts behind dynamic obstacles
Solution Approach 1:
The patent employs dynamic sensing strategies where the autonomous vehicle moves to multiple positions and orientations to capture obstacles from different viewpoints. The system dynamically adjusts its sensing approach based on the presence of dynamic obstacles that may obscure stationary objects. By changing the vehicle's position and processing images from multiple angles, the system can detect stationary objects like posts that are hidden behind moving obstacles such as solar panels.
Solution Approach 2:
The patent utilizes the temporal dimension by capturing images at different times as the autonomous vehicle moves through the environment. This fourth dimension (time) allows the system to observe objects from multiple perspectives and infer the locations of obscured stationary objects. The processing system analyzes image sequences to distinguish between dynamic and stationary objects, enabling detection of posts that are not visible in any single static image.
3Productivity
If the autonomous vehicle navigates close to dynamic obstacles like solar panels, then task performance is improved, but the risk of collision increases due to changing obstacle positions and orientations
Solution Approach 1:
The patent implements real-time feedback loops where the LIDAR and camera systems continuously monitor the environment, detect dynamic obstacles, and provide updated position and orientation data to the navigation system. The processing system analyzes this feedback information to determine current obstacle configurations and adjusts the autonomous vehicle's navigation path accordingly. This continuous feedback enables the vehicle to maintain close proximity to obstacles for improved task performance while dynamically adapting to changing obstacle positions to ensure safety.
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
Enables autonomous vehicles to accurately detect and navigate around dynamic obstacles and obscured stationary objects, ensuring precise proximity and effective task performance in complex environments like solar farms.
Implementation Method 1
directly sensing, by the autonomous vehicle, the environment local to said autonomous vehicle to produce direct sensing data
Implementation Method 2
directly sensing, by the autonomous vehicle, the environment local to said autonomous vehicle to produce direct sensing data
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.