AI Agent Collaboration Using Shared Grid Maps for Robot Coverage
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Solution Overview
Problem
Existing methods for collaborative intelligence among AI agents lack autonomous dynamic connection and collaboration, requiring user input and not allowing for autonomous task completion among robotic devices.
Innovation Solution
A system of AI agents that generate and update grid maps of environments, track work progress, determine operational schedules, and communicate with each other to autonomously collaborate and share intelligence for efficient task completion, using machine-readable mediums and AI home assistants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If hierarchical structure with remote control unit is used to coordinate multiple robots, then task coordination is achieved, but autonomous collaboration capability is lost requiring continuous user input
Solution Approach 1:
The robotic devices are equipped with processors that enable them to autonomously determine their own operational parameters, share sensor data with peer devices, and dynamically adjust task allocation without requiring user input. Each robot serves itself by making independent decisions based on shared environmental information.
Solution Approach 2:
The system implements continuous feedback loops where robotic devices share sensor data and operational status with each other in real-time. This feedback mechanism enables autonomous agents to adapt their behavior dynamically based on the current state of the environment and other robots, achieving coordinated collaboration without human intervention.
2Productivity
If multiple robotic devices operate independently without sharing intelligence, then device complexity is reduced, but task completion efficiency decreases
Solution Approach 1:
The system segments the intelligence sharing function into discrete data packets that are exchanged between robotic devices. Each robot maintains its own processor and decision-making capabilities while sharing specific sensor data and operational status information, avoiding the need for a centralized complex control system.
Solution Approach 2:
The processors in each robotic device are designed to perform multiple functions: local environmental perception, autonomous decision-making, and inter-robot communication. This multi-functionality allows robots to achieve high task completion efficiency without adding separate dedicated systems for each function, thereby limiting the increase in overall device complexity.
3Reliability
If robotic devices continuously share sensor data and operational parameters, then collaborative intelligence is enhanced, but communication overhead and processing requirements increase
Solution Approach 1:
The system extracts and shares only the essential sensor data and operational parameters that are critical for task coordination, rather than transmitting complete data sets. Each robotic device selectively transmits relevant information such as position, task status, and key environmental observations, reducing communication overhead while maintaining sufficient situational awareness.
4Productivity
If dynamic task allocation among robotic devices is implemented, then overall system productivity increases, but coordination complexity and communication requirements increase
Solution Approach 1:
The task allocation mechanism is designed to be dynamic rather than static. Robotic devices continuously evaluate their own capabilities, current workload, and environmental conditions to adjust task assignment in real-time. This dynamic approach allows the system to adapt to changing conditions and optimize productivity without requiring complex pre-planned coordination schedules.
Data Source
AI summary
A system of two robots, including: a first robot, including: a plurality of sensors; a control system; and medium storing instructions that when executed by the control system of the first robot effectuates operations including: generating or updating a grid map of an environment; and transmitting a message to a control system of a second robot; and the second robot, including: a plurality of sensors; a control system; and a medium storing instructions that when executed by the control system of the second robot effectuates operations including: generating or updating a grid map of the environment independent from the gird map generated by the control system of the first robot; and actuating the second robot to begin performing coverage of the environment upon receiving the message from the control system of the first robot.