Lead Robot Task Allocation Using Capability-Aware Collaboration
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Solution Overview
Problem
Existing robotic control techniques result in 'swarm' behavior where robots are unaware of each other's presence and capabilities, leading to inefficient task execution and redundant programming.
Innovation Solution
A method where a lead robot designates tasks and communicates with subordinate robots to assess their physical and electronic characteristics, allowing for optimized task allocation and collaboration, thereby avoiding redundant efforts and enhancing network awareness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robots operate as a swarm with redundant programming, then task execution can be performed, but the robots are unaware of each other's presence and capabilities, leading to inefficient task execution
Solution Approach 1:
The patent implements feedback mechanisms where robots continuously broadcast their presence, capabilities, and task status to the network. Other robots receive and process this information, creating a feedback loop that enables network awareness. This allows robots to adjust their behavior based on real-time information about teammates, resolving the contradiction between maintaining simple swarm operation and achieving efficient coordinated execution.
2Device complexity
If robots are assigned tasks without assessing capabilities, then task allocation is simple, but redundant programming occurs and robots cannot collaborate effectively
Solution Approach 1:
The patent applies preliminary action by having robots broadcast their capabilities and receive task assignments before actually executing tasks. The lead robot assesses subordinate robots' capabilities in advance and allocates tasks accordingly. This preliminary assessment and allocation phase prevents redundant programming and ensures efficient task distribution, resolving the contradiction between simple allocation and effective collaboration.
3Ease of manufacture
If all robots have equal programming, then system design is simplified, but individual robot capabilities cannot be optimized for specific tasks
Solution Approach 1:
The patent implements local quality by allowing different robots to have different capabilities and task assignments based on their individual characteristics. While robots may share a common base programming framework, each robot can be optimized for specific tasks based on its capabilities. The lead robot assigns tasks locally to appropriate subordinates based on their specific skills, resolving the contradiction between uniform programming and task-specific optimization.
Data Source
AI summary
A method of robotic collaboration comprises designating a first robot a lead robot and assigning a first task in a task area to the lead robot. Broadcasting a work query in the task area seeks the presence of subordinate robots configured to perform tasks. Receiving a work confirmation signal from a subordinate robot in the task area answers the work query with an affirmation that the subordinate robot is in the task area to perform tasks. Transmitting a task command to the subordinate robot in response to the work confirmation signal comprises a directive to perform the first task. Receiving a task confirmation signal informs the lead robot of the subordinate robot electronic characteristics comprising processing capabilities, transmit signal profile, receive signal profile, and storage device capabilities. Processing confirms whether the subordinate robot can collaborate with the lead robot to do the first task.