Forklift Task Classification for Adaptive Speed and Lift Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Material handling vehicles in industrial settings lack the ability to autonomously recognize activities and adjust their behavior to assist operators efficiently, leading to potential errors and inefficiencies in task performance.
Innovation Solution
A vehicle classification system that uses a network of sensors and a vehicle controller to identify activities and modify operational parameters, such as speed and lift height, to assist operators or enhance autonomous operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If material handling vehicles use fixed behavior modes, then device complexity is reduced, but adaptability to different tasks deteriorates
Solution Approach 1:
The vehicle controller dynamically switches between multiple behavior modes (autonomous, semi-autonomous, manual) based on detected task types. The system transitions from static fixed behavior to dynamic adaptive behavior by selecting appropriate control strategies for different operational contexts such as order picking, put away, or travel tasks.
Solution Approach 2:
The system changes operational parameters including control authority levels, speed limits, and intervention thresholds based on the identified task. For example, during autonomous order picking, the vehicle operates at reduced speeds with restricted control authority, while during manual operation, full control is granted to the operator.
2Productivity
If the vehicle autonomously recognizes activities and modifies behavior, then operational efficiency is improved, but device complexity increases
Solution Approach 1:
The behavior modification system is segmented into distinct modular components: task classification module, behavior selection module, and execution module. Each component handles specific functions independently, making the overall complex system manageable through functional decomposition and independent development of each module.
Solution Approach 2:
The vehicle autonomously performs task classification and self-adjusts its behavior without external intervention. The system monitors its own operational state, identifies the current task type, and automatically selects appropriate behavior modes, enabling self-service operation that improves productivity.
3Ease of operation
If the vehicle adapts behavior based on task classification, then operator assistance is enhanced, but measurement precision requirements increase
Solution Approach 1:
The system implements multiple levels of task classification with varying degrees of precision. Rather than requiring perfect classification for all scenarios, the system uses hierarchical classification where broad task categories are identified first, followed by more specific sub-task identification only when needed, reducing overall measurement precision requirements while maintaining adequate operator assistance.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Systems and methods for material handling vehicle task classification are provided. A method for task characterization on a material handling vehicle (12) comprises monitoring data communicated between one or more on-board sensors (103) and a vehicle controller (104) on the material handling vehicle. The method further comprises identifying a repletion or pattern in the monitored data, and determining that the repetition or pattern in the monitored data is a vehicle task. The method also comprises modifying an operational parameter of the material handling vehicle based on the determined vehicle task.