Autonomous Mobile Robot Task Segmentation for Simplified Work Planning
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Solution Overview
Problem
Current autonomous mobile robots have limited capabilities for user-defined planning of work movements, requiring complex and time-consuming manual programming, which can only be done by experienced users.
Innovation Solution
A method for controlling autonomous mobile robots that involves receiving work assignments, automatically dividing them into subtasks, determining the sequence of subtasks, and integrating time-specific task planning to avoid conflicts and optimize resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual programming is used to plan work movements, then task execution precision is improved, but operation complexity and time consumption increase significantly
Solution Approach 1:
The patent segments the work area into multiple zones and divides work assignments into subtasks that can be automatically sequenced. This allows the system to maintain precision through structured planning while reducing operational complexity by automating the decomposition and sequencing processes.
Solution Approach 2:
The robot system performs self-planning by automatically dividing work assignments into subtasks and determining execution sequences without requiring manual programming. The system uses its own map and sensor data to autonomously generate optimized work plans, eliminating the need for complex user programming while maintaining task precision.
2Manufacturing precision
If manual programming is used to plan work movements, then task execution precision is improved, but time consumption increases
Solution Approach 1:
The system performs preliminary automatic planning by pre-dividing work assignments into subtasks and determining optimal execution sequences before actual task execution. This preliminary automated planning eliminates the need for time-consuming manual programming while ensuring precise task execution through pre-calculated optimized paths and sequences.
Solution Approach 2:
The robot autonomously generates its own work plans by automatically decomposing tasks and sequencing subtasks based on its map and current state, eliminating the need for external manual programming and significantly reducing the time required to prepare for task execution.
3Ease of operation
If automatic task division and sequencing is implemented, then ease of operation is improved, but system complexity increases
Solution Approach 1:
The robot system autonomously performs task decomposition and sequencing using its own map, sensor data, and embedded algorithms. This self-service capability provides users with simple operation interfaces while the complex automatic planning functions are handled internally by the system's own processing units and algorithms.
Solution Approach 2:
The patent introduces an automatic planning module that acts as an intermediary between the simple user interface and the complex task execution system. This module automatically divides work assignments into subtasks and determines sequences, shielding users from system complexity while enabling sophisticated automated planning capabilities.
4Productivity
If detailed work movement planning is enabled, then productivity is improved, but ease of operation deteriorates
Solution Approach 1:
The robot autonomously generates detailed work movement plans by automatically dividing tasks into subtasks and optimizing execution sequences based on its map and real-time conditions. This self-service capability delivers high productivity through detailed planning while maintaining ease of operation, as users simply need to issue high-level commands without manual programming.
Solution Approach 2:
The system segments work assignments into manageable subtasks with optimized sequences, enabling detailed and efficient work movement planning. This segmentation approach allows the system to achieve high productivity through comprehensive task decomposition and sequencing while keeping the user interface simple, as users don't need to manually create these detailed plans.
Data Source
AI summary
A method for controlling at least one autonomous mobile robot, wherein the at least one robot is designed to navigate within a functional area on the basis of a map of said functional area, and to perform at least one task autonomously in the functional area. The method involves: receiving a job request which contains instructions for carrying out at least one task in the functional area, automatically dividing the job request into at least two sub-tasks, and automatically determining a sequence in which said sub-tasks are to be processed by the at least one robot, the job request being fully completed once all sub-tasks have been processed.