Autonomous Drill Path Control Using Dual Image Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current autonomous surface drills in open-pit mining face challenges in maintaining accurate path control due to dynamic machine-ground interactions and environmental conditions, lacking a solution to correct deviations from intended paths and adapt to site-specific conditions.
Innovation Solution
The implementation of a method and assessment system using dual image capturing modules (e.g., LIDAR, cameras) to detect forward and rearward worksite conditions, determining the effect of machine movement on the site, and adjusting operational parameters to correct deviations from a baseline path.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous surface drills operate on worksites with dynamic conditions, then productivity is improved, but path control accuracy deteriorates due to machine-ground interactions and environmental factors
Solution Approach 1:
The system continuously monitors the actual machine path using image capturing modules and compares it with the baseline operational path. The controller receives feedback about path deviations and automatically adjusts movement parameters to correct the deviation, enabling the drill to maintain accurate path control while operating autonomously in dynamic worksite conditions
Solution Approach 2:
The system dynamically adjusts movement parameters based on real-time worksite conditions and detected path deviations. The controller modifies operational parameters adaptively to counteract the effects of machine-ground interactions and environmental factors, allowing the drill to maintain path accuracy while adapting to changing conditions
2Reliability
If the machine operates autonomously without manual intervention, then safety is improved, but the ability to adapt to site-specific conditions deteriorates
Solution Approach 1:
The autonomous drill system performs self-assessment by capturing images of worksite conditions before and after movement, automatically determines the effect of its operation on the worksite, and self-corrects by adjusting its movement parameters. This self-service capability enables the system to adapt to site-specific conditions autonomously while maintaining high safety standards through minimal manual intervention
Solution Approach 2:
The system uses feedback from image capturing modules to detect worksite conditions and path deviations, processes this information through the controller, and automatically adjusts operational parameters. This closed-loop feedback mechanism enables autonomous adaptation to varying worksite conditions while maintaining safety through consistent monitoring and correction
3Manufacturing precision
If the machine follows a predefined baseline path, then manufacturing precision is improved, but the ability to handle dynamic worksite conditions deteriorates
Solution Approach 1:
The system continuously monitors the actual path against the baseline operational path using image capturing modules. When deviations are detected due to dynamic worksite conditions, the controller receives feedback and automatically adjusts movement parameters to correct the deviation, allowing the drill to maintain geometric consistency while adapting to environmental factors
Solution Approach 2:
The system dynamically adjusts movement parameters based on real-time detection of path deviations from the baseline. The controller modifies operational parameters adaptively to counteract the effects of dynamic worksite conditions, enabling the drill to maintain path accuracy while responding to environmental changes
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 solution enables autonomous surface drills to accurately maintain their intended path by analyzing site conditions and adjusting movement parameters, enhancing operational efficiency and safety in dynamic environments.
Implementation Method 1
detection of a forward worksite condition and a rearward worksite condition relative to the machine. The forward worksite condition is detected by a first image capturing module
Implementation Method 2
The rearward worksite condition is detected by a second image capturing module
Data Source
AI summary
A method for operating a machine on a worksite is disclosed. The method includes detecting a forward worksite condition and a rearward worksite condition relative to the machine, respectively by a first image capturing module and a second image capturing module. Thereafter, the method includes determination of a measure of effect of the machine on the worksite by comparing the rearward worksite condition with the forward worksite condition. The measure of effect is one of a deviation of an actual machine path with a baseline operational path or an impression left by the machine on the worksite. Finally, controlling one or more parameters related to a movement of the machine over the worksite, based on the measure of effect, is carried out.