Algorithm for Object Detection and Obstacle Avoidance for Medication Delivery Robot

Abstract

Seniors age 65 and older are projected to be 23.5% of the U.S. population by 2060. Today approximately 80% of the elderly population have at least one chronic disease such as heart disease, cancer, stroke, and diabetes. Chronic disease can affect seniors' health and quality of life and requires medication compliance for disease management. Today the number of residents in nursing homes is about 1.3 million in the U.S. Many residents have a strict medication regime averaging over four medications every day. With the increase in the aging population with chronic disease and the shortage of nurses in nursing homes, there is an increase in potential medication errors and non-compliance. Advanced technologies have great potential in improving clinical practice and increase the efficiency of medication adherence. This project extends existing work to standard delivery of medications to patients in nursing homes using robotics. A prototype system has been developed and implemented using an iRobot platform. The project includes the development of an ultrasonic sensor module for the detection of obstacles of different heights and shapes. Moreover, conducted tests examined the sensor system's performance for detecting and characterizing obstacles based on shape, edge, and material. Ultimately, the project aims are achieved by developing an algorithm to detect and avoid fixed and flexible obstacles along the delivery path in a simulated laboratory setting. The robot is able to navigate the path to reach its target destination.