Mobile Robot Task Merging for Power and Time Efficiency
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Solution Overview
Problem
Existing electronic devices, such as social robots, face challenges in efficiently managing multiple tasks and optimizing task execution in dynamic environments, leading to suboptimal performance and increased power consumption.
Innovation Solution
An electronic device equipped with a processor, memory, sensors, and communication circuits that can receive and analyze user requests, determine the sequence of tasks by merging sub-tasks based on type, execution target, time, and location, and execute these tasks efficiently, thereby optimizing task performance and reducing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the electronic device performs multiple tasks separately without merging, then task execution completeness is maintained, but power consumption increases and execution time extends
Solution Approach 1:
The patent merges multiple tasks into a single integrated task when they share common sub-tasks. For example, when Task 1 requires moving from Location A to Location B and Task 2 requires moving from Location B to Location C, the system combines these into one continuous movement sequence rather than executing them separately, thereby reducing redundant operations and power consumption while maintaining complete task execution
Solution Approach 2:
The patent segments tasks into sub-tasks to identify commonalities that can be merged. By breaking down tasks into smaller components (such as movement, object manipulation, communication), the system can recognize overlapping sub-tasks across different tasks and consolidate them, improving overall efficiency without losing task completeness
2Loss of time
If the electronic device merges multiple tasks into one sequence, then power consumption and execution time are reduced, but task management complexity increases
Solution Approach 1:
The system continuously monitors task execution status and provides feedback to the task management module. This feedback mechanism allows the system to dynamically adjust task sequences, identify completion points, and manage merged task complexity through real-time status updates and adaptive re-planning
Solution Approach 2:
The patent implements dynamic task management where the task sequence is not fixed but can be adjusted based on execution progress, changing environmental conditions, and new user requests. This dynamic approach allows the system to handle complexity adaptively rather than requiring rigid pre-planning for all scenarios
3Productivity
If the electronic device determines task sequences based on multiple parameters (type, target, time, location), then task optimization improves, but processing complexity increases
Solution Approach 1:
The patent segments the task analysis process into distinct parameter evaluation stages: type matching, target identification, time window validation, and location verification. This segmented approach allows the system to process multiple parameters systematically rather than evaluating all parameters simultaneously, reducing processing complexity while maintaining comprehensive optimization
Solution Approach 2:
The system applies different processing depths to different parameters based on their importance and variability. For example, location and time parameters may require precise matching while task type may allow for broader categorization. This local quality approach optimizes processing resources by applying appropriate analysis depth to each parameter
Data Source
AI summary
An electronic device is provided. The electronic device includes a housing, a user interface, a battery positioned inside the housing, a driving unit disposed at the housing or connected to the housing to move the housing, at least one sensor positioned at the housing or inside the housing, a wireless communication circuit positioned inside the housing, a processor operatively connected to the user interface, the driving unit, the at least one sensor, and the wireless communication circuit, and a memory operatively connected to the processor. The processor determines one sequence performed by connecting or merging the first task and the second task, based at least partly on at least one of a type, execution target, execution time, or execution location of the first task and at least one of a type, execution target, execution time, or execution location of the second task.