Autonomous Load Transport Vehicle Obstacle Sensing and Positioning
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Solution Overview
Problem
Autonomous material transport vehicles face challenges in navigating around obstacles and identifying intended targets within their environment, requiring effective collision avoidance and load positioning mechanisms.
Innovation Solution
An autonomous material transport vehicle equipped with a sensing system and a processor that monitors the environment, determines the location of a load, and executes collision avoidance maneuvers by adjusting its path or speed, using image segmentation and neural networks to identify and position the load for transportation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle uses a sensing system to monitor for objects within detection range, then collision avoidance capability is improved, but the complexity of the system increases
Solution Approach 1:
The sensing system is divided into multiple independent sensors (cameras, LIDAR, ultrasonic sensors) that monitor different aspects of the environment. Each sensor type handles specific detection tasks, allowing the system to achieve comprehensive collision avoidance through modular components rather than a single complex system
Solution Approach 2:
The processor acts as an intermediary that receives data from multiple sensing systems, processes the information, and generates control signals for the drive system. This intermediary layer simplifies the overall system architecture by centralizing the decision-making logic and coordinating between different sensing modalities
2Measurement precision
If the vehicle determines whether the load is within detection range using image segmentation and neural networks, then load identification accuracy is improved, but processing time increases
Solution Approach 1:
The neural network model is pre-trained offline on large datasets of load images. During actual operation, the pre-trained model performs rapid inference to identify loads, eliminating the need for time-consuming training during real-time operation. This preliminary preparation enables fast and accurate load identification
Solution Approach 2:
Image segmentation techniques divide the captured image into distinct regions, identifying the load area separately from the background and other objects. This segmentation focuses processing resources on relevant areas, improving identification accuracy while reducing overall processing time by ignoring irrelevant image regions
3Reliability
If the vehicle adjusts its operating speed to accommodate avoidance maneuvers, then collision avoidance effectiveness is improved, but transportation productivity decreases
Solution Approach 1:
The vehicle's speed is dynamically adjusted based on real-time environmental conditions detected by the sensing system. When obstacles are detected, the vehicle slows down or stops; when the path is clear, the vehicle maintains higher speeds. This dynamic speed adjustment ensures collision avoidance while minimizing the impact on overall transportation productivity
Solution Approach 2:
The vehicle performs brief, rapid deceleration and acceleration maneuvers to navigate around obstacles rather than maintaining reduced speeds for extended periods. These quick avoidance maneuvers minimize the time spent at reduced speeds, thereby reducing the impact on productivity while still ensuring safe collision avoidance
Data Source
AI summary
The various embodiments described herein generally relate to an autonomous material transport vehicle, and systems and methods for operating an autonomous material transport vehicle. The autonomous material transport vehicle comprises: a sensing system operable to monitor an environment of the vehicle; a drive system for operating the vehicle; a processor operable to: receive a location of a load; initiate the drive system to navigate the vehicle to the location; following initiation of the drive system, operate the sensing system to monitor for one or more objects within a detection range; and in response to the sensing system detecting the one or more objects within the detection range, determine whether the load is within the detection range; and when the load is within the detection range, operate the drive system to position the vehicle for transporting the load, otherwise, determine a collision avoidance operation to avoid the one or more objects.