Autonomous bot with ML-based reactive navigation for indoor environment

by   Yash Srivastava, et al.

Local or reactive navigation is essential for autonomous mobile robots which operate in an indoor environment. Techniques such as SLAM, computer vision require significant computational power which increases cost. Similarly, using rudimentary methods makes the robot susceptible to inconsistent behavior. This paper aims to develop a robot that balances cost and accuracy by using machine learning to predict the best obstacle avoidance move based on distance inputs from four ultrasonic sensors that are strategically mounted on the front, front-left, front-right, and back of the robot. The underlying hardware consists of an Arduino Uno and a Raspberry Pi 3B. The machine learning model is first trained on the data collected by the robot. Then the Arduino continuously polls the sensors and calculates the distance values, and in case of critical need for avoidance, a suitable maneuver is made by the Arduino. In other scenarios, sensor data is sent to the Raspberry Pi using a USB connection and the machine learning model generates the best move for navigation, which is sent to the Arduino for driving motors accordingly. The system is mounted on a 2-WD robot chassis and tested in a cluttered indoor setting with most impressive results.


page 3

page 5

page 6

page 8

page 9

page 11


Localization and Navigation System for Indoor Mobile Robot

Visually impaired people usually find it hard to travel independently in...

Intelligent Indoor Mobile Robot Navigation Using Stereo Vision

Majority of the existing robot navigation systems, which facilitate the ...

DRQN-based 3D Obstacle Avoidance with a Limited Field of View

In this paper, we propose a map-based end-to-end DRL approach for three-...

HouseExpo: A Large-scale 2D Indoor Layout Dataset for Learning-based Algorithms on Mobile Robots

As one of the most promising areas, mobile robots draw much attention th...

Learning control for transmission and navigation with a mobile robot under unknown communication rates

In tasks such as surveying or monitoring remote regions, an autonomous r...

Visual Based Navigation of Mobile Robots

We have developed an algorithm to generate a complete map of the travers...

Adaptive Acoustic Flow-Based Navigation with 3D Sonar Sensor Fusion

Navigating spatially varied and dynamic environments is one of the key t...

Please sign up or login with your details

Forgot password? Click here to reset