Robot Picking Task Assignment and Path Planning in Warehouses
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional distribution centers require significant human labor for picking and moving delivery objects, especially during peak seasons, leading to increased working hours and the need for temporary workers.
Innovation Solution
A system comprising a server that assigns tasks to multiple robots, guiding them to storage locations, enabling automatic loading and unloading of delivery objects, and optimizing their movement based on task completion and emergency situations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If human workers perform picking and moving delivery objects manually, then flexibility and adaptability are maintained, but labor costs and working hours increase significantly during peak seasons
Solution Approach 1:
The robot autonomously performs picking tasks by itself: navigating to storage locations, identifying delivery objects, picking them up, and transporting them to packing stations without continuous human intervention. The system self-manages the entire picking workflow, reducing dependency on human labor force while maintaining high productivity during peak seasons
Solution Approach 2:
The patent replaces the mechanical human labor system with an automated robot system equipped with sensors, processors, and mechanical arms. The robot uses optical sensors to detect delivery objects, processes navigation and picking decisions, and executes mechanical picking and transport actions, thereby substituting human physical labor with an automated electromechanical system
2Productivity
If multiple robots are deployed to handle increased order volume, then productivity increases, but system complexity and coordination requirements increase
Solution Approach 1:
The server implements a universal task management system that handles multiple functions: assigning tasks to robots, tracking robot locations, monitoring task progress, and coordinating movements of multiple robots simultaneously. This multi-functional system manages the entire robot fleet through a single integrated platform, reducing the complexity that would otherwise arise from multiple separate control systems
Solution Approach 2:
The system continuously collects feedback from robots about their locations, task completion status, and current activities. The server processes this feedback information and dynamically adjusts task assignments and robot routing to optimize overall system efficiency. This closed-loop feedback mechanism coordinates multiple robots effectively without requiring complex manual intervention or overly sophisticated control algorithms
3Extent of automation
If robots autonomously navigate to storage locations and packing stations, then human labor is reduced, but navigation and task coordination complexity increases
Solution Approach 1:
The server pre-calculates optimal paths for robots to navigate from their current locations to storage locations and packing stations. Task assignments are prepared in advance with routing information included, allowing robots to execute navigation autonomously without real-time complex decision-making. This preliminary path planning reduces the computational complexity during actual robot operation while maintaining high automation levels
Solution Approach 2:
The navigation and task coordination system is divided into separate functional modules: path planning, task assignment, robot monitoring, and collision avoidance. Each module handles a specific aspect of robot coordination independently, making the overall complex system more manageable and easier to implement. The segmentation allows each component to be optimized separately while working together to achieve autonomous robot operation
Data Source
AI summary
A task performance method of a system includes assigning, by the server, at least one task of a plurality of tasks stored in advance to a first robot among the plurality of robots, determining, by the server, a path for arranging the first robot to a first location in which at least one delivery object related to the task assigned to the first robot is stored, guiding, by the server, the first robot to the first location according to the determined path, and guiding, by the server, the first robot arranged in the first position to a second position.