A fuzzy logic navigation controller implemented in hardware for an electric wheelchair

Mario Rojas,Arturo Molina,Pedro Ponce

doi:10.1177/1729881418755768

Mario Rojas, Arturo Molina + Show 1 more

Open Access

https://doi.org/10.1177/1729881418755768

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Abstract

In this article, we present an obstacle avoidance controller implemented in a field programmable gate array for an electric wheelchair. It is based on a traditional approach with ultrasonic sensors and fuzzy logic. Various tests were conducted to characterize the prototype and to evaluate the controller performance. The results showed that the system is able to acquire data from sensors and make decisions 46.16 times per second. The sensors’ coverage extends 3 m to the front, rear, left, and right sides of the wheelchair; moreover, the sensors detect 0.95-cm diameter objects at 40 cm. The power consumption was evaluated, and it was found that the hardware architecture reduces the battery life by only 0.87%. Furthermore, the controller helped to navigate in confined areas, avoiding obstacles with cautious movements and decreasing the likelihood of collision. The proposed methodology uses data from eight sonars distributed around the wheelchair to make navigation decisions, besides the hardware-based architecture guarantees real-time control and on-time response.

Highlights

According to the study by Fehr et al.,[1] a survey about wheelchair users in the United States reported that up to 40% find difficulties in maneuvering as a consequence of disabilities
The forward obstacle avoidance (FOA) controller is able to detect objects in the dark areas covered by sensors S1–S5, the object is likely to be detected before reaching the clear positions
The controller is independent from software execution, which assures data acquisition from eight channels and data calculations within 21.66 ms

Summary

Introduction

According to the study by Fehr et al.,[1] a survey about wheelchair users in the United States reported that up to 40% find difficulties in maneuvering as a consequence of disabilities. Those individuals experiment limited mobility due to visual impairments, spasticity, tremors, or cognitive deficits. “Smart wheelchairs” integrate navigation systems and add-on modules in conventional power wheelchairs, as presented by Simpson.[2] Nowadays, the state of the art and other trends have been presented by Leaman and La3 and Desai et al.[4] It is recommended the use of a collaborative scheme or semiautonomous control by Nisbet[5] and Hsu et al.,[6] and the user is still able to drive the wheelchair by himself and the semiautonomous system complements the driver’s skills

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