Obstacle Map Updating for Autonomous Pile Driving Navigation
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Solution Overview
Problem
Current pile driving operations require manual labor, leading to high costs, extended project durations, and increased risk of human error due to dependence on skilled operators, limiting operations to daytime hours and reducing work quality.
Innovation Solution
Autonomous off-road vehicles (AOVs) perform autonomous pile driving operations, including path planning, basket assembly, pile loading, and quality control, using sensors and control systems to navigate, load, and drive piles into the ground based on a pile plan map, while generating obstacle maps to avoid obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual operators are used to operate heavy equipment vehicles, then the vehicles can be controlled with human judgment and adaptability, but the operation costs increase, project duration extends, and human error risk increases
Solution Approach 1:
The heavy equipment vehicle performs pile driving operations autonomously using onboard sensors, processors, and control systems. The vehicle self-navigates to target locations, self-adjusts operating parameters, and self-monitors performance without requiring manual operators, thereby eliminating human error while maintaining operational efficiency
Solution Approach 2:
The patent replaces the mechanical control system operated by human operators with an automated control system that uses sensors (LIDAR, cameras, GPS), processors, and actuators. This substitution enables the vehicle to autonomously perform navigation, pile driving, and quality control functions, resolving the contradiction between reliability and productivity
2Adaptability or versatility
If manual operators are required during entire earthwork operation, then human skills can be applied to handle complex situations, but labor costs increase and skilled labor shortage becomes a bottleneck
Solution Approach 1:
The autonomous heavy equipment vehicle integrates multiple functions including navigation, obstacle detection, pile driving, and quality control into a single automated system. The vehicle can perform various earthwork operations autonomously, providing operational adaptability without requiring multiple specialized operators or complex manual coordination
Solution Approach 2:
The patent introduces an automated control system as an intermediary between the operator and the vehicle's mechanical systems. This control system processes sensor data, makes decisions, and executes commands, enabling the vehicle to adapt to complex situations autonomously while simplifying the overall system architecture
3Reliability
If operations are limited to daytime hours due to manual operation requirements, then safety can be maintained with human operators, but project duration extends and costs increase
Solution Approach 1:
The autonomous heavy equipment vehicle enables continuous pile driving operations without interruption by human needs such as shifts, breaks, or daylight limitations. The vehicle can operate 24/7 autonomously, maintaining safety through automated monitoring and control while significantly reducing project duration
Solution Approach 2:
The vehicle autonomously monitors its own operational status, detects obstacles, adjusts parameters, and maintains safety protocols without requiring human intervention. This self-service capability enables safe continuous operation during nighttime and extended hours, eliminating the daytime-only constraint
4Manufacturing precision
If skilled operators are depended upon for vehicle operation, then human expertise can ensure quality work, but labor costs increase and operational flexibility decreases
Solution Approach 1:
The autonomous vehicle incorporates sensors and monitoring systems that continuously feedback operational data to the control system. This feedback mechanism enables real-time adjustments to maintain precise pile driving quality while operating at optimal productivity levels, eliminating the need for skilled operators to manually ensure work quality
Data Source
AI summary
An autonomous off-road vehicle (AOV) accesses a pile plan map indicating a plurality of locations within a geographic area at which piles are to be installed. The AOV generates an obstacle map indicating locations of obstacles within the geographic area. The AOV autonomously navigates to a first location of the plurality of locations using the pile plan map. In response to driving a pile into the ground at the first location, the AOV modifies the obstacle map to include a representation of the pile at the first location. The AOV autonomously navigates to a second location of the plurality of locations using the pile plan map. In response to driving a pile into ground at the second location, the AOV modifies the obstacle map that includes the representation of the pile at the first location to further include a representation of the pile at the second location.