Autonomous Ripper Tool Control for Earth-Moving Vehicles
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Solution Overview
Problem
Existing techniques for autonomous control of powered earth-moving vehicles face limitations, including reliance on limited sensed data, inability to perform fully autonomous operations with on-site obstacles, and lack of coordination between multiple vehicles, along with the need for bulky and expensive hardware systems.
Innovation Solution
The implementation of an Earth-Moving Vehicle Autonomous Operations Control (EMVAOC) system that uses data from various sensors to determine and control the motion of powered earth-moving vehicles, including the automatic control of hydraulic arms and tool attachments, to perform autonomous operations such as loosening ground materials with a ripper tool for subsequent blade tool operations, while ensuring safety and coordinating with multiple vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If limited types of sensed data are used for autonomous control, then device complexity is reduced, but the ability to perform fully autonomous operations with on-site obstacles is lost
Solution Approach 1:
The patent employs multiple sensor types (cameras, LIDAR, GPS, inertial sensors) that serve multiple functions: obstacle detection, positioning, navigation, and terrain mapping. This multi-functional approach enables fully autonomous operation without requiring separate specialized systems for each function, thus maintaining adaptability while controlling complexity.
Solution Approach 2:
The patent introduces a centralized autonomous control system that acts as an intermediary between various sensors and vehicle actuators. This control system integrates data from multiple sensor types and coordinates their information to make autonomous decisions, allowing the vehicle to handle on-site obstacles without each sensor directly controlling specific components.
2Measurement precision
If multiple sensors are used to gather comprehensive data for autonomous operations, then measurement precision and adaptability improve, but device complexity and cost increase
Solution Approach 1:
The patent combines multiple sensor types (visual cameras, LIDAR for depth, GPS for positioning, inertial sensors for orientation) into an integrated sensing system. These sensors work together to provide comprehensive environmental data with high precision, while their combined use reduces overall system complexity compared to using each sensor type independently for different functions.
Solution Approach 2:
The patent implements feedback loops where sensor data is continuously processed and used to adjust vehicle operations in real-time. The autonomous control system receives feedback from multiple sensors, processes the information, and makes corrective adjustments to maintain precise positioning and navigation, thereby achieving high measurement precision without proportionally increasing system complexity.
3Productivity
If autonomous control coordinates multiple vehicles operations, then productivity increases, but device complexity and communication requirements worsen
Solution Approach 1:
The patent introduces a centralized coordination system that acts as an intermediary between multiple autonomous vehicles. This system receives status and position data from each vehicle, processes the information, and distributes coordinated task assignments, enabling multiple vehicles to work together efficiently without requiring complex direct peer-to-peer communication between each vehicle pair.
Solution Approach 2:
The patent implements inter-vehicle feedback mechanisms where each vehicle reports its status, position, and operational state to the coordination system, which then adjusts task assignments in real-time. This feedback loop enables dynamic coordination that increases productivity while managing system complexity through standardized communication protocols and centralized processing.
Data Source
AI summary
Systems and techniques are described for implementing autonomous control of powered earth-moving vehicles, including to automatically control use of a ripper tool attachment to loosen ground materials for subsequent blade tool operations, such as to determine placements of the ripper tool for multiple ripping passes so that its teeth perform ground-loosening operations that in the aggregate span the width of a blade tool to be used for subsequent pushing/cutting operations. For example, the techniques may include obtaining information about a width of a ripper tool attachment and placement of one or more teeth on the ripper tool, obtaining information about a width of a blade tool attachment, and determining multiple placements of the ripper tool attachment during ripping operations that in the aggregate cover the width of the blade tool attachment to be used for subsequent pushing/cutting operations.