Composite Mission Data for Multi-Robot Navigation
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Solution Overview
Problem
Existing robotic systems are limited in their ability to dynamically define and execute missions, particularly in environments where multiple robots need to collaborate or where mission data needs to be shared across different robots.
Innovation Solution
A method and system that allow for the generation of composite mission data by combining first and second mission data associated with different robot missions. This composite data can include portions of both mission data sets and is used to instruct navigation of at least one robot, while also verifying the mission data based on the characteristics of the robot, such as its sensors, arm, gripper, or processing units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robotic systems execute single missions sequentially, then mission execution is simple and reliable, but productivity and collaboration efficiency deteriorate
Solution Approach 1:
The patent segments missions into modular mission data components that can be independently combined. The system divides complex multi-robot missions into discrete, manageable units that can be assembled through composite mission data generation, allowing parallel execution while maintaining individual mission integrity and simplifying management of complex operations.
Solution Approach 2:
The patent merges multiple mission data sets into composite mission data that can be executed by one or multiple robots simultaneously. This combining approach enables collaborative missions where different robots perform different tasks based on the same composite mission data, improving productivity without requiring separate mission management for each robot.
2Reliability
If mission data is customized for each robot, then mission execution reliability is improved, but adaptability and collaboration capability deteriorate
Solution Approach 1:
The patent creates universal composite mission data that can be adapted to multiple robots with different characteristics. The system generates mission data that is not tied to a specific robot but can be executed by any robot in the fleet by verifying compatibility with robot characteristics, enabling both reliable execution and cross-robot adaptability through a single unified mission data structure.
Solution Approach 2:
The patent dynamically adjusts mission data parameters based on robot characteristics verification. The system modifies mission execution parameters while maintaining the core mission structure, allowing the same composite mission data to be reliably executed across different robots by changing only the necessary parameters to match each robot's capabilities rather than creating entirely separate mission data for each robot.
3Adaptability or versatility
If composite mission data is generated from multiple sources, then versatility and collaboration capability are improved, but verification complexity and time consumption increase
Solution Approach 1:
The patent performs preliminary verification of robot characteristics before generating composite mission data. By pre-establishing robot capability profiles and verifying compatibility in advance, the system reduces the time required during actual mission execution, allowing rapid generation and deployment of versatile composite missions without extensive verification delays.
4Productivity
If robots execute multiple missions simultaneously, then productivity is improved, but navigation coordination and task management complexity increase
Solution Approach 1:
The patent introduces composite mission data as an intermediary structure that coordinates multiple robot missions. This intermediate layer manages the complexity of simultaneous mission execution by providing a unified framework that handles navigation coordination and task management, allowing robots to execute multiple missions in parallel while the composite mission data ensures proper synchronization and conflict resolution.
Data Source
AI summary
Systems and methods are described for dynamic and variable definition of robot missions and performance of the robot missions. A system can obtain first robot mission data associated with a first robot mission and second robot mission data. The second robot mission data may be associated with a second robot mission or a user-defined route edge. The system can generate composite mission data based on the first robot mission data and the second robot mission data. The system can instruct navigation of a robot through an environment according to the composite mission data.