Abstract
Robots in assisted living (RAL) are an alternative to support families and professional caregivers with a wide range of possibilities to take care of elderly people. Navigation of mobile robots is a challenging problem due to the uncertainty and dynamics of environments found in the context of places for elderly. To accomplish this goal, the navigation system tries to replicate such a complicated process inspired on the perception and judgment of human beings. In this work, we propose a novel nature-inspired control system for mobile RAL navigation using an artificial organic controller enhanced with vision-based strategies such as Hermite optical flow (OF) and convolutional neural networks (CNNs). Particularly, the Hermite OF is employed for obstacle motion detection while CNNs are occupied for obstacle distance estimation. We train the CNN using OF visual features guided by ultrasonic sensor-based measures in a 3D scenario. Our application is oriented to avoid mobile and fixed obstacles using a monocular camera in a simulated environment. For the experiments, we use the robot simulator V-REP, which is an integrated development environment into a distributed control architecture. Security and smoothness metrics as well as quantitative evaluation are computed and analyzed. Results showed that the proposed method works successfully in simulation conditions.
Highlights
Nowadays, there is a dramatic increase in the aging of the population
In order to validate our proposed nature-inspired controller system for mobile robot navigation implementing an As mentioned controller (AOC) enhanced with Hermite optical flow (OF) and convolutional neural networks (CNNs), we develop a set of experiments to independently prove each of the components of the system in an incremental fashion. ese experiments measure the output response of (i) avoiding a mobile obstacle using the Hermite OF, (ii) avoiding a mobile obstacle as well as free navigating using the Hermite OF and AOC, (iii) avoiding a fixed obstacle using CNN, and (iv) avoiding fixed and mobile obstacles as well as free navigating using the whole proposed nature-inspired controller system
Three smoothness indexes are employed to indirectly evaluate the consistency between the decisionaction relationship of the control navigation in the robot and the ability to react to events with sufficient speed [48]. e bending energy (BE) measures the energy for steering or bending during the trajectory, and it is calculated as Equation (6), where kt represents the curvature of the trajectory f(t) computed as Equation (7), n is the number of points in the discrete trajectory, and t is the current time
Summary
It is expected that the number of people over 60 years will go from 962 million in 2017 to 1.4 billion in 2030 and 2.1 billion in 2050 [1] Along with this increasing in elderly people and higher life expectancy, there is a necessity of the creation of new care strategies. Some experts argue that it is desirable for elderly to stay in their own home with a certain level of independence and a sense of comfort and security. It requires to maintain an acceptable quality of life and independence capability [2]. Robots in assisted living (RAL) are an alternative to support families and professional caregivers with a wide range of possibilities to take care of elderly people. ere are many issues where robots have high potential for assistance such as social isolation, diminishing independent living, physical and cognitive impairment, loss of mobility, lack of recreation, and risk of falls. ese problems can be tackled with different robot designs categorized as service, assistance, social, and rehabilitation robots [2]
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