Multi-Sensor 3D Pile Volume Estimation for Autonomous Machines
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Solution Overview
Problem
Current robotic equipment is limited in accurately sensing and estimating material volumes in a timely manner, hindering autonomous tasks at industrial sites, and struggles with navigating and autonomously moving piles of material due to field of view limitations and complex processes.
Innovation Solution
An autonomous machine equipped with a controller system and multiple sensors, including cameras and LIDAR, uses machine learning models to generate 3D representations of material piles, estimate volumes, and communicate this information for autonomous operation, enabling efficient task performance across various industries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If robotic equipment is used to move piles of material, then automation is improved, but accurate sensing and estimation of material volumes in a timely manner deteriorates
Solution Approach 1:
The patent combines multiple sensor types (cameras, LIDAR, radar) into an integrated sensing system that captures data from different modalities simultaneously. This fusion of sensor data enables accurate volumetric estimation while maintaining automation, as the complementary information from each sensor type compensates for individual sensor limitations.
Solution Approach 2:
The patent transforms 2D sensor data from cameras and LIDAR into 3D representations of material piles through point cloud processing and volumetric reconstruction algorithms. This dimensional transformation enables accurate volume calculation by creating a three-dimensional model from two-dimensional sensor inputs.
2Productivity
If complex processes are used to move piles of material, then task completion is improved, but time consumption deteriorates
Solution Approach 1:
The patent performs preliminary volumetric estimation and pile characterization before the material moving operation begins. By pre-calculating volume, identifying material boundaries, and planning the operation in advance, the system reduces on-site processing time and enables more efficient execution of the material moving task.
Solution Approach 2:
The patent replaces complex mechanical processes with sensor-based detection and computational algorithms. Instead of using elaborate mechanical systems to handle material piles, the invention uses optical and electromagnetic sensing combined with software processing to achieve accurate measurement and control, thereby reducing time consumption.
3Extent of automation
If robotic arms are used for picking and sorting material, then automation is improved, but field of view limitations and navigation capabilities deteriorate
Solution Approach 1:
The patent employs a multi-functional sensor system that serves multiple purposes: cameras provide visual identification and color information, LIDAR generates precise 3D point clouds for volumetric measurement, and radar detects material boundaries. This universal sensing platform handles diverse tasks including picking, sorting, and navigation, overcoming the limited field of view of traditional robotic arms.
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
The system enables accurate and timely volumetric estimation and navigation of material piles, enhancing the efficiency and autonomy of industrial tasks by integrating sensor data and machine learning for precise volume calculation and operation planning.
Implementation Method 1
An autonomous machine equipped with a controller system and multiple sensors, including cameras and LIDAR
Data Source
AI summary
The present disclosure relates generally to the operation of autonomous machinery for performing various tasks at various industrial work sites, and more particularly to the volumetric estimation and dimensional estimation of a pile of material or other object, and the use of multiple sensors for the volumetric estimation and dimensional estimation of a pile of material or other object at such work sites. An application and a framework is disclosed for volumetric estimation and dimensional estimation of a pile of material or other object using at least one sensor, preferably a plurality of sensors, on an autonomous machine (e.g., robotic machines or autonomous vehicles) in various work-site environments applicable to various industries such as, construction, mining, manufacturing, warehousing, logistics, sorting, packaging, agriculture, etc.