Autonomous Robot Charging Schedules for Maximum Work Time
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous work robots face inefficiencies in operation due to fixed battery-charging schemes that do not align with their work schedules, leading to wasted working time when charging occurs during scheduled work periods.
Innovation Solution
A method to determine an optimized charging schedule for autonomous work robots by aligning it with their work schedule, using a cost function to maximize work time within the schedule, which involves acquiring and optimizing the charging schedule based on the work schedule, energy storage means, and power consumption, allowing for real-time or predicted state of charge monitoring and adjusting charging times to ensure sufficient battery levels for work without unnecessary recharging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed battery-charging scheme is used with preset minimum threshold and target level, then the charging operation is simple to implement, but the work time within the schedule is reduced due to unnecessary recharging
Solution Approach 1:
The charging scheme transitions from a fixed static threshold-based approach to a dynamic optimization approach. The system determines optimal charging schedules by considering the work schedule, battery capacity, charging time characteristics, and power consumption patterns. This dynamic adjustment allows the robot to charge only when necessary and for the minimum required duration, maximizing productive work time while maintaining adequate battery levels throughout the schedule.
2Reliability
If the robot returns to charging station when battery level reaches preset minimum threshold, then the battery charge level is maintained safely, but the remaining working time is wasted for charging instead of working
Solution Approach 1:
The system performs preliminary analysis of the work schedule and battery characteristics before execution. By calculating the required charging duration and optimal charging timing in advance based on the work schedule and power consumption patterns, the system ensures that charging operations are scheduled only when they will not conflict with productive work time. This preliminary planning prevents unnecessary interruptions and ensures that the robot maintains adequate battery levels without wasting productive time.
3Productivity
If charging schedule is optimized to maximize work time within time span, then the productivity is improved, but the device complexity increases due to cost function optimization
Solution Approach 1:
The system implements self-service through automated optimization algorithms that independently determine the optimal charging schedule. The cost function optimization process automatically analyzes the work schedule, battery characteristics, and power consumption patterns to generate the optimal charging timetable without requiring complex manual configuration or intervention. This self-service approach handles the computational complexity internally while presenting a simple interface and maximizing productivity automatically.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The present invention relates to a method for determining a schedule for charging an energy storage means (13) of an autonomous work robot (i). The method comprises a step (Si) of acquiring a work schedule of the autonomous work robot and a step (S3) of determining the charging schedule based on the work schedule in order to improve a cost function that is optimal when an optimal amount of work time within the work schedule is achieved.