Multipurpose Autonomous Navigation Robot (M.A.N.R)

Abstract

The \"Multipurpose Navigation Robot\" project proposes the development of a highly versatile and adaptive robotic system capable of seamlessly navigating through diverse real-world environments such as restaurants, hospitals, and warehouses. The project centers around a modular design, featuring a flexible base chassis responsible for efficient and obstacle-free movement across various terrains and settings. The core innovation lies in the incorporation of easily attachable and detachable modules, enabling the robot to cater to specific tasks in different industries.

Introduction

I. INTRODUCTION

The primary objective of the project is to design and construct an intelligent robot capable of serving multiple purposes in diverse work environments. The driving force behind the Multipurpose Autonomous Navigation Robot project lies in the recognition of a crucial gap in the robotics landscape. Traditional robots struggle to adapt to the dynamic challenges posed by diverse environments such as restaurants, hospitals, and warehouses. This project is motivated by the vision of creating a versatile and adaptable robotic solution. In the restaurant setting, the robot will function as a serving bot, facilitating smooth and efficient customer service. In warehouses, the robot will transform into a robust package-moving bot, streamlining the logistics and distribution process. Furthermore, in healthcare environments, the robot will take on the role of a healthcare assistant, providing valuable support to medical staff and patients alike.

The successful realization of the Multipurpose Navigation Robot holds the promise of revolutionizing industries by offering a cost-effective and multi-functional robotic solution. This project serves as a stepping stone towards a future where robots can be dynamically deployed to serve multiple purposes across various work environments, enhancing operational efficiency, reducing human workload, and ultimately contributing to the advancement of automation and robotics in society.

II. PROBLEM STATEMENT

The project goal is to develop a highly adaptable "Multipurpose Autonomous Navigation Robot" with modular attachments, ensuring autonomous navigation, safety compliance, and optimal task performance. The aim is to provide industries a scalable, cost-effective, and innovative robotic solution for diverse environments.

III. LITERATURE SURVEY

1. “Intelligent Warehouse Management System”, Mohamed Dhouioui; Tarek Frikha

This paper presents the design and implementation of an intelligent warehouse management system. The main emphasis is on three software components: An Xamarian IOT application that acts as the exchange interface with end users, a web application that communicates with a database and ensures the persistence and communication between the different components of the system, and a robot that moves products in the warehouse according to storage and shipping requests.

2. “Path Planning of Restaurant Service Robot Based on Astar Algorithms with Updated Weights”, Ruijun Yang; Liang Cheng

This paper introduces an improved A-star algorithm for optimal path selection for autonomous navigation robots in restaurants. This uses a real-time gridded restaurant congestion map, aiming at the shortest weighted path, and based on the degree of channel congestion to change the weight of the restaurant channel in real-time.

3. “Research and Implementation of Autonomous Navigation for Mobile Robots Based on SLAM Algorithm under ROS”, Jianwei Zhao; Shengyi Liu; Jinyu Li

This paper aims at the problem of low mapping accuracy, slow path planning efficiency, and high radar frequency requirements in the process of mobile robot mapping and navigation in an indoor environment. This paper proposes a four-wheel drive adaptive robot positioning and navigation system based on ROS.

4. “Development of a wireless communication platform for multiple-mobile robots using ROS ”, Pipit Anggraeni; Mariem Mrabet; Michael Defoort; Mohamed Djemai

The paper discusses the development of a wireless communication platform for coordinating multiple mobile robots using the Robot Operating System (ROS). The authors present the MiniLab Enova mobile robot as the focal point and detail the implementation of a multi-master system using ROS to manage a wireless communication network among multiple robots.

5. “ZigBee based Small-World Home Area Networking for Decentralized Monitoring and Control of Smart Appliances”, Rakesh Das; Jitendra Nath Bera

The paper presents a novel approach to decentralized monitoring and control of smart electric appliances within homes, utilizing ZigBee mesh topology for home area networking (HAN). All communication nodes within the household are interconnected via ZigBee, with the operational status of individual smart appliances displayed on an in-home display (IHD) or smartphone via Wi-Fi internet connectivity

C. Robot Structure

1. Microcontrollers

Microcontrollers are often called the brain of the robot. They collect information from input devices such as sensors, switches, and others, and then execute programs that control output devices such as motors and LEDs. The output signals from the microcontroller are given to motors (wheels, legs, etc.) or light or any other actuator, making the robot walk or move. The best microcontroller is the one that does what you need at the least possible cost of power, size, and money. Thus the microcontrollers used in our projects are Arduino UNO, Arduino Mega, Raspberry Pi.

2. Motor Driver

We use motor drivers to give high power to the motor by using a small voltage signal from a microcontroller or a control system. If the microprocessor transmits a HIGH input to the motor driver, The driver will rotate the motor in one direction keeping the one pin as HIGH and one pin as LOW. Motor Driver used in our projects are Cytron Motor Driver for 10A current(MD 10C).

3. Power Supply

Power supplies play an important role in the proper operation of industrial robotics. Most industrial robots will be powered by a battery source, either chargeable or non-rechargeable. The power supply will help deliver power to different components, like a motor drive or inverter circuit within the robotic circuit. Our robot is equipped with 12V DC Battery which provide the power supply to motor driver and all the other electrical components to operate. Also we provide step-down voltage of 5V to our microcontroller for its operation.

4. Chassis

A two-wheeled robot with a dead wheel in front is used along with maintaining its modular design. A modular upper body offers significant flexibility and versatility for various applications such as warehouse automation, hospital logistics, and restaurant services. This modular design allows for easy customization and adaptation of the robot's functionality to meet specific requirements in different environments

V. IMPLEMENTATION

A. Integration of Methodologies

In our project, the A* algorithm, LiDAR, and odometry work together synergistically to enable the robot to navigate autonomously in various environments. Here's how these components interact:

1. Environment Mapping with LiDar

• The LiDAR sensor scans the robot's surroundings and creates a detailed map of the environment, including obstacles, walls, and other features.
• This map is used as the basis for path planning by the A* algorithm.

2. Path Planning with A* Algorithm

• The A* algorithm uses the map created by the LiDAR sensor to plan an optimal path from the robot's current position to its goal. This map is used as the basis for path planning by the A* algorithm.
• It takes into account the location of obstacles and navigable areas to determine the most efficient route.

3. Localisation with Odometry

• Odometry data from the wheel encoders is used to track the robot's movement and estimate its current position.
• This position estimate is used by the A* algorithm to determine the robot's starting point for path planning.

4. Dynamic Obstacle Avoidance

• As the robot moves along its planned path, the LiDAR sensor continues to scan its surroundings
• If a new obstacle is detected, the A* algorithm can re-plan the path in real-time to avoid the obstacle, using the updated LiDAR map and odometry data.

5. Feedback Loop

• The robot's movement is a continuous feedback loop between odometry, LiDAR, and the A* algorithm.
• Odometry data is used to update the robot's position, LiDAR data is used to update the map and detect obstacles, and the A* algorithm uses this updated information to plan the next move.

B. Implementation if UI/UX

The User Interface (UI) and User Experience (UX) play a critical role in ensuring the effective operation and interaction of the Multipurpose Autonomous Navigation Robot. This section outlines the design and implementation of the UI/UX components tailored to the diverse operational environments of warehouses, hospitals, and restaurants.

1. GUI Design

• The Graphical User Interface (GUI) is designed to provide an intuitive and user-friendly platform for commanding the robot. The design principles emphasize clarity, simplicity, and adaptability to accommodate various user preferences and operational requirements

2. Environment Selection

• Upon launching the GUI, users are presented with an environment selection panel. This panel allows users to choose the specific operational environment for the robot, such as warehouse, hospital, or restaurant. The selection process is facilitated through clearly labelled buttons or dropdown menus, ensuring ease of use.

3. Environment-Specific Actions:

Once the environment is selected, the GUI dynamically adjusts its interface to display environment-specific actions and functionalities.

• Warehouse Environment: If the warehouse environment is selected, the GUI presents options related to crate handling, inventory management, and navigation through aisles.
• Hospital Environment: In the hospital setting, the GUI showcases functionalities such as medication delivery to patients, transportation of medical supplies, and navigation to different wards or rooms.
• Restaurant Environment: For restaurant operations, the GUI displays options for food delivery, table service, and navigation through dining areas.

4. Command Inputs

• Users can input commands or set waypoints for the robot's navigation through the designated input fields or interactive map interfaces. The GUI provides clear feedback on the accepted commands and planned routes, enhancing user confidence and control over the robot's actions.

5. Real-Time Feedback

• During operation, the GUI continuously provides real-time feedback on the robot's status, including its current location, planned trajectory, and any encountered obstacles or challenges. This feedback loop enables users to monitor the robot's progress and make informed decisions as needed.

6. Customization Options

• The GUI offers customization options to cater to the preferences and requirements of different users and operational scenarios. Users can adjust settings such as navigation speed, obstacle avoidance sensitivity, and display preferences to optimize the robot's performance for specific tasks and environments.

VI. FUTURE WORK

As we look to the future, there are several areas of potential improvement and expansion for multipurpose autonomous navigation robots. Autonomous navigation robots can play a central role in the factories of the future, working alongside human workers to streamline production processes, perform repetitive tasks, and optimize logistics within manufacturing facilities.

Future innovations may include robots equipped with specialized sensors for patient monitoring, telepresence capabilities for remote consultations, and the ability to navigate complex healthcare environments with precision and care. Autonomous navigation robots can contribute to the development of smarter and more sustainable cities ,Home and personal assistance, Outdoor Exploration and Disaster Response, Education and Research.

Overall, future work on multipurpose autonomous navigation robots should focus on advancing the state-of-the-art in navigation, perception, collaboration, interaction, and reliability to enable these robots to operate effectively and autonomously in a wide range of environments and applications. As technology continues to evolve and mature, autonomous navigation robots will play an increasingly integral role in shaping the future of work, healthcare, transportation, urban development, and beyond.

Conclusion

The development of a multipurpose autonomous navigation robot marks a significant milestone in robotics and automation. The multipurpose autonomous navigation robot promises to enhance efficiency, safety, and productivity across diverse applications. By leveraging advanced sensors, artificial intelligence, and adaptive algorithms, these robots can navigate complex environments with ease, perform tasks autonomously, and adapt to dynamic surroundings. As we continue to refine and expand the capabilities of these robots, we move closer to a future where intelligent machines seamlessly collaborate with humans, unlocking new opportunities and transforming the way we live and work.

References

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Copyright

Copyright © 2024 Sanket Bhole, Nirmal Gharpure, Vrushali Mohite, Tanishq Shinde, Prof. G. S. Wayal. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.