Autonomous Earth-Moving Vehicle Risk Triggers for Dig Site Pauses
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Solution Overview
Problem
Current earth moving vehicles require manual operators due to unpredictable earth movement, leading to increased human error and reduced work quality, and existing systems fail to detect precarious situations effectively.
Innovation Solution
An autonomous or semi-autonomous earth moving system integrating sensors to record vehicle and site conditions, generating digital representations, and controlling vehicle movements, with risk-based triggering conditions for pausing operations and notifying remote operators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual operators are used to operate earth moving vehicles, then human error and reduced work quality occur, but complete autonomous operation is limited by inability to detect precarious situations
Solution Approach 1:
The autonomous operation system is segmented into multiple independent sensor modules (LIDAR, cameras, GPS, inertial sensors) that each perform specific detection functions. This modular segmentation allows the system to achieve comprehensive monitoring capability while maintaining manageable complexity through specialized sensor components.
Solution Approach 2:
The sensor system is designed with multi-functionality to perform various detection tasks simultaneously - LIDAR for distance measurement and terrain mapping, cameras for visual monitoring of precarious situations, GPS for location tracking, and inertial sensors for vehicle state detection. This universal sensor platform handles multiple operational requirements without requiring separate specialized systems.
2Productivity
If autonomous operation is implemented without risk assessment, then operational efficiency increases, but safety risk increases due to unpredictable earth movement
Solution Approach 1:
The system implements continuous feedback loops where sensor data from LIDAR, cameras, and other sensors is constantly monitored and fed back to the control system. This real-time feedback enables the autonomous vehicle to detect changes in earth movement patterns, identify precarious situations, and adjust operations dynamically to maintain safety while preserving productivity.
Solution Approach 2:
The system performs preliminary risk assessment by continuously scanning the environment with LIDAR and cameras before executing earth moving operations. By detecting potential precarious situations in advance and evaluating risk levels, the system can take preventive actions or pause operations before harmful events occur, ensuring safety without significantly reducing efficiency.
3Extent of automation
If complete autonomous operation is implemented, then dependence on manual operators decreases, but ability to handle unpredictable situations deteriorates
Solution Approach 1:
The autonomous system incorporates dynamic decision-making capabilities that allow it to adapt to unpredictable situations. The control system can dynamically adjust operational parameters, pause operations when precarious situations are detected, and respond flexibly to changing conditions based on real-time sensor feedback, maintaining high adaptability despite complete automation.
Solution Approach 2:
The system uses remote operators as intermediaries who receive notifications about detected precarious situations and can provide high-level guidance or override decisions when necessary. This intermediary human element supplements the autonomous system's decision-making for highly unpredictable situations while maintaining predominantly autonomous operation, balancing automation extent with adaptability.
Data Source
AI summary
An earth moving vehicle (EMV) autonomously performs an earth moving operation within a dig site. If the EMV determines that a state of the EMV or the dig site triggers a triggering condition associated with a pause in the autonomous behavior of the EMV, the EMV determines a risk associated with the state or triggering condition. If the risk is greater than a first threshold, the EMV continues the autonomous performance and notifies a remote operator that the triggering condition was triggered. If the risk is greater than the first threshold risk but less than a second threshold risk, the EMV is configured to operate in a default state before continuing and notifying the remote operator. If the risk is greater than the second threshold risk, the EMV notifies the remote operator of the state pauses the performance until feedback is received from the remote operator.