Independent Design Project: Rough Draft

Abstract

The world aging population requires a better solution. Many researchers have estimated a higher growth rate by the year 2050. A suggestion of a robotic system with the ability to feed the elderly provides not only a caring solution but also a relief to governments. This paper established the entropic circuit robot model with RetinaNet and other parts which would facilitate the working of the Robot. The paper found identification and grasping of different foods as a challenge. Therefore, the paper recommended cognitive learning which will help the robot learn and adapt to become better in feeding the elderly.

Introduction

The invention of the robotic system has supplemented human unending needs. The understanding and creation of robots is significant in the current society for various purposes. This paper will detail the rough design of a robotic system for the elderly.

The robotic system has unlimited capabilities necessary for today's needs. The robot’s ability to sense, feel, respond and understand makes robots more efficient and better. Robots are believed to be more accurate and reliable than human and they do not get tired from too much work. The number of elderly people currently in high and continuous to grow. Caregivers' abilities to perform all duties and attend to the elderly is limited. The introduction of Robots to feed the elderly would provide relief for caregivers to work on other things (Bajcsy, Aloimonos & Tsotsos, 2018). These type of robots is ground operational.

Literature review

The world aging population is currently high and continues to grow even faster. Aging and health. (2018) argues that by 2050 the aging population growth-rate will be at 22%. The shift in responsibility of the elderly towards the government has risen the burden of the government. Chamie, (2019) asserts that the improvement of healthcare is the reason for this fast-aging population. Aging population comes with health challenges such as old-age illness which require care. With the high number of elderly people, caregivers are becoming limited. If the problem is not resolved, the government may strain in supporting this population and increase death-rate resulting from poor care. The introduction of a robotic system with the ability to bath, interact and feed the elderly would not only relieve the government of the financial strain but address the limited caregiver shortage (Espingardeiro, (2017).

Design and development process and models

Related Research and Development

Technological Advancements

The designing of feeding robots can borrow knowledge of cognitive learning. The technology requires adaptation which is through understanding human behaviors to use the robots. Though this technology may be expensive, it can solve a larger part of the feeding robotic system.

Design Overview

The Robot will have various parts for different purposes. The controller will be the brain to give direction to the robot movable parts. Mechanical parts such as motor, the piston, gripper/folk, and gear will facilitate the movement of various robotic parts. RetinaNet algorithm will scan to detect the pressure of the object (McQuate-Washington, 2019).

Figure 1. Adapted from The robot learns to feed folks dinner – Futurity, pp.3. McQuate-Washington Sarah, 2019, Washington University:

Design Decisions

RetinaNet is meaningful in scanning the food and the face of the person its feeding. This helps in the skewness of the angles between the person and the folk when feeding. The controller conceptualizes the scanned items and sends directions to various responsible parts. The mechanical parts do not involve wheels but have a folk for picking the food, piston to allow movement and motor to power the activities. This is because the folk helps in gripping the food, unlike gripper which is not best suited for picking food. The RetinaNet will help in cognitive learning as scanning repetitive actions will enable the robot to adapt to the behavior faster.

Design Limitations

The robot finds difficulty in picking different varieties of food. The RetinaNet requires more time to study in order to learn and adapt better. The system cannot pick other foods other than fruits but through continues learning, the system can adapt and perform more tasks.

Logic Design

For the robot to perform its actions, the fruits need to be sliced into required piece-sizes and placed on a plate. The robot which is stationed in proximity will sense the food on the plate through the RetinaNet scanner, determine the energy required to pick the food and pick it. The Collector will then direct motion of mechanical elements to move the arm at a skewed angle towards the person, scan his face before directing the food near his/her mouth. The person will stretch slightly to grasp the food with the mouth and eat. After food has been taken from the folk the same process is repeated until the food is completed.

Conclusion

The aging population across the world requires a better solution. The introduction and development of a robotic system that can feed the elderly will serve best. This paper suggests a ground entropic circuit model of a robot. The robot contains various parts such as RetinaNet which will facilitate the functioning of the robot. Advancement of challenges experienced by the robot will be solved through cognitive learning to enable it to adapt better to new behaviors.

References