Autonomous Earth-Mover Slope Control via Sensor Fusion
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Solution Overview
Problem
Existing techniques for autonomous control of powered earth-moving vehicles face challenges such as limited sensed data, inability to perform fully autonomous operations with on-site obstacles, and 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 on-vehicle sensors to determine and control vehicle motion, manage slope-based stopping operations, and coordinate autonomous actions between 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 compromised
Solution Approach 1:
The patent implements a multi-sensor system where each sensor type (cameras, LIDAR, GPS, IMU, slope sensors) serves multiple functions. For example, the camera system not only detects obstacles but also determines slope angles when combined with other sensors, and provides visual data for operator monitoring. This multi-functionality allows comprehensive autonomous operation capability without requiring separate dedicated hardware for each function, thus resolving the contradiction between device complexity and automation extent.
2Measurement precision
If bulky and expensive hardware systems are used to support autonomous operations, then measurement precision and reliability are improved, but device complexity and cost increase
Solution Approach 1:
The patent combines multiple existing sensors (cameras, LIDAR, GPS, IMU, slope sensors) into an integrated autonomous control system. Rather than using a single complex dedicated slope detection device, the system merges data from multiple standard sensors to achieve accurate slope measurement. This combining approach maintains high measurement precision while avoiding the bulk and cost of specialized heavy-duty hardware, as each sensor component is relatively small and commercially available.
Solution Approach 2:
The system uses data fusion techniques where multiple sensor copies (multiple cameras, LIDAR points, GPS readings) are processed to create an accurate slope measurement. Rather than relying on a single expensive high-precision sensor, the patent uses multiple standard sensors whose data is combined through computational algorithms to achieve equivalent or superior precision at lower cost and reduced hardware bulk.
3Productivity
If human operators control vehicle motion manually, then operational flexibility is maintained, but productivity and safety in autonomous coordination scenarios decrease
Solution Approach 1:
The autonomous control system performs preliminary actions by pre-planning vehicle paths, pre-detecting slope conditions, and pre-coordinating with other vehicles before manual intervention is needed. The system automatically handles routine control tasks such as maintaining slope-based stopping distances and coordinating motion with other autonomous vehicles, freeing operators from continuous manual control burdens while maintaining overall operational flexibility through operator oversight and intervention capabilities.
Data Source
AI summary
Systems and techniques are described for implementing autonomous control of powered earth-moving vehicles, including to automatically control movement of some or all of a powered earth-moving vehicle on a job site to manage vehicle motion based in part on the determined slope of surrounding surfaces. For example, the automated operations may include initiating a stop to vehicle motion (or alternatively, a change in a planned vehicle path) if a planned travel path of the vehicle is determined to have one or more slopes in one or more sections that exceed one or more defined thresholds or otherwise having one or more determined attributes that satisfy one or more criteria.