Pharmacy Robot SLAM Navigation for Wheel Slip Correction
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Solution Overview
Problem
Current pharmacy automation systems rely on inaccurate dead reckoning methods for navigation, leading to errors in prescription dispensing and potential patient harm due to wheel slips and skidding.
Innovation Solution
Implementing Simultaneous Localization and Mapping (SLAM) technology in autonomous robots to create accurate maps and track their location, using a combination of rotary encoders and laser scans to correct for wheel slips and skidding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If dead reckoning is used for robot navigation in pharmacy, then the system is simple to implement, but navigation accuracy deteriorates due to wheel slips and skidding
Solution Approach 1:
The patent introduces laser scanners and range finders as intermediary devices between the robot and its environment. These sensors act as mediators that provide external reference points for localization, compensating for the inaccuracies of wheel-based dead reckoning. The laser range finders measure distances to fixed features in the environment, creating a feedback mechanism that corrects position estimates and eliminates the harmful effects of wheel slip and skid.
2Measurement precision
If SLAM technology is implemented for accurate mapping and localization, then navigation accuracy improves, but device complexity increases
Solution Approach 1:
The patent implements SLAM (Simultaneous Localization and Mapping) technology that allows the robot to perform multiple functions simultaneously: creating environmental maps, localizing itself within those maps, and navigating to targets. This multi-functional approach consolidates what would otherwise require separate systems into a unified framework, making the increased capability more manageable despite the inherent complexity.
Solution Approach 2:
SLAM technology incorporates continuous feedback loops where the robot's sensed environment is compared against its internal map model. This feedback mechanism allows the system to detect and correct localization errors in real-time, improving navigation accuracy while managing complexity through iterative refinement rather than requiring perfect initial conditions.
3Device complexity
If rotary encoders are used for position tracking, then the system is simple and low-cost, but measurement accuracy deteriorates due to wheel slips
Solution Approach 1:
The patent introduces laser range finders and environmental features as intermediary reference points. Instead of relying solely on wheel encoders, the system uses these external intermediaries to verify and correct position estimates. The laser measurements provide independent data about the robot's location relative to known environmental features, creating a cross-validation mechanism that eliminates the harmful effects of wheel slip.
Data Source
AI summary
A pharmacy automation system having a robot having a hardware device and a software for internal mapping to perform simultaneous localization and mapping (SLAM) is disclosed herein. The robot is configured to use the SLAM technique to carry out at least the following different interactions: the robot communicates autonomously with a physician or an assistant directly or via an intermediary; the robot interacts with an inventory of goods and browses the inventory of goods to determine if a prescribed medication is available in the pharmacy; if the prescribed medication is available in the pharmacy, the robot interacts with a medication dispenser, using the internal mapping to fill a container with the prescribed medication, and store the container; when a patient or a proxy arrives to pick up the prescribed medication, the robot checks and approves an identification of the patient or the proxy; and when the patient or proxy presents a prescription containing the prescribed medication, the robot retrieves the container with the prescribed medication and hands the container with the prescribed medication over to the patient or proxy.