Robotic Localization With Partial Maps and Modular Cartridges
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional robotic devices face inefficiencies in consumable replenishment, navigation, and task versatility, with manual consumable handling being laborious and inefficient, primitive navigation systems leading to wastage, and limited ability to reconfigure for different tasks without significant modifications.
Innovation Solution
A multi-function robotic device with a modular design that uses optical data mapping and partial maps for navigation, enabling selective configuration for various tasks through a cartridge system and advanced sensor arrays for efficient consumable management and obstacle avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a sophisticated sensor system is implemented for robot navigation, then navigation efficiency and environment mapping capability are improved, but device complexity and cost increase
Solution Approach 1:
The environment mapping is segmented into multiple partial maps, each representing a specific portion of the operating environment. The sensor system acquires optical data at discrete scan points and builds partial maps incrementally, which can be stored and processed separately. This segmentation allows the robot to navigate efficiently using only relevant local map data rather than processing entire environment maps, reducing computational complexity while maintaining navigation effectiveness.
2Reliability
If application-specific structural elements are designed for a particular function, then functional performance is improved, but adaptability to perform other operations is reduced
Solution Approach 1:
The robotic device employs dynamic reconfiguration capability where functional components can be added, removed, or modified during operation. The system allows sensor reconfiguration and software reprogramming to alter overall functionality. This dynamic approach enables the robot to transition between different task configurations while maintaining reliable performance for each specific function through dedicated structural elements.
3Device complexity
If conventional docking mechanisms are used for robot storage, then mechanical simplicity is maintained, but reliability of robot engagement with docking station is reduced
Solution Approach 1:
The docking system incorporates feedback mechanisms where the robot and docking station exchange information about their respective positions, orientations, and engagement status. This feedback allows the robot to adjust its approach and alignment automatically, ensuring reliable engagement with the docking station while maintaining relatively simple mechanical structures. The feedback loop enables compensation for positioning errors without requiring complex mechanical precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution allows for efficient consumable replenishment, improved navigation, and task versatility, reducing wastage and manual labor, while enabling reliable storage and charging, and flexible operation across different environments and tasks.
Implementation Method 1
acquiring optical data at a scan point associated with a partial map representing a portion of the operating environment
Data Source
AI summary
A multi-function robotic device may have utility in various applications. In accordance with one aspect, a multi-function robotic device may be selectively configurable to perform a desired function in accordance with the capabilities of a selectively removable functional cartridge operably coupled with a robot body. Localization and mapping techniques may employ partial maps associated with portions of an operating environment, data compression, or both.