Forklift Acceleration Adaptation for Manual-to-Automated Transition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Materials handling vehicles face challenges in transitioning from manual to semi-automated driving modes, as existing systems rely on predefined acceleration limits that may not accurately reflect the operator's driving behavior, leading to suboptimal performance, especially when handling unstable loads or navigating complex paths.
Innovation Solution
A method and system that monitor and adapt vehicle drive parameters during manual operations to adjust semi-automated driving parameters, such as acceleration limits, based on recent driving behavior, ensuring more accurate and safe transitions to remote control operations by calculating weighted averages of acceleration values in multiple directions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If predefined acceleration limits are used for semi-automated driving, then the system is simple to implement, but the performance is suboptimal and does not accurately reflect operator driving behavior
Solution Approach 1:
The system monitors drive parameters (acceleration, speed, steering angle) during manual operation and uses this feedback to automatically adjust acceleration limits for semi-automated driving. The controller continuously adapts the acceleration profile based on the operator's recent driving behavior, creating a closed-loop system that improves adaptability without requiring complex manual configuration.
Solution Approach 2:
The system performs preliminary monitoring and analysis of operator driving behavior during manual operation before transitioning to semi-automated mode. By pre-calculating and storing the operator's typical acceleration patterns during manual use, the system prepares adaptive parameters in advance, enabling smooth transitions without real-time computational complexity during automated operation.
2Reliability
If acceleration limits are adjusted based on recent driving behavior, then safety and performance are improved, but data management and parameter calculation become more complex
Solution Approach 1:
The acceleration limits are made dynamic rather than static, automatically adjusting based on the operator's recent driving behavior. The system continuously updates the acceleration profile to reflect current operational conditions and operator preferences, improving safety and performance while using straightforward monitoring and calculation logic to manage the complexity.
Solution Approach 2:
The system automatically monitors, analyzes, and adjusts its own operating parameters without external intervention. By self-managing the adaptation process through automated monitoring of drive parameters and automatic adjustment of acceleration limits, the system improves reliability while minimizing the need for complex external data management or manual configuration.
3Measurement precision
If multiple drive parameters are monitored concurrently, then the accuracy of semi-automated control is improved, but the computational load increases
Solution Approach 1:
The system monitors multiple drive parameters (acceleration, speed, steering angle) concurrently during manual operation to gather comprehensive data for accurate adaptation. By collecting slightly more data than the minimum required during the monitoring phase, the system ensures high measurement precision while keeping computational requirements manageable through efficient processing algorithms.
Data Source
AI summary
A method for operating a materials handling vehicle is provided comprising: monitoring, by a controller, a first vehicle drive parameter corresponding to a first direction of travel of the vehicle during a first manual operation of the vehicle by an operator and concurrently monitoring, by the controller, a second vehicle drive parameter corresponding to a second direction different from the first direction of travel during the first manual operation of the vehicle by an operator. The controller receives, after the first manual operation of the vehicle, a request to implement a first semi-automated driving operation. Based on the first and second monitored vehicle drive parameters during the first manual operation, the controller controls implementation of the first semi-automated driving operation.