Mobile Robot Control 2023 Ultron

Group members:

Name	student ID
Sarthak Shirke	1658581
Idan Grady	1912976
Ram Balaji Ramachandran	1896067
Anagha Nadig	1830961
Dharshan Bashkaran Latha	1868950
Nisha Grace Joy	1810502

Design Presentation Link

https://tuenl-my.sharepoint.com/:p:/g/personal/a_nadig_student_tue_nl/EdIzlDXy5tZAm3MElMK_-lYBLcIrJx99aSsqLKZ5dCZlyQ?e=nhG68W

Introduction

//This page contains the details of the Restaurant Challenge in which the team was tasked with safely navigating an autonomous robot (in this case the robot was HERO) through a makeshift restaurant and delivering //orders to tables whose sequence was predetermined.

//A brief description of the challenge, its rules and ultimate goal is mentioned first so as to give an understanding of the various requirements that have to be met in order to complete it. These requirements were //divided into three categories: Stakeholder requirements, Border requirements and System Requirements.

In an increasingly autonomous world, robotics plays a vital role in performing complex tasks. One such task is enabling a robot to autonomously locate and navigate itself in a restaurant environment to serve customers. While this may seem like a straightforward task for humans, there are various challenges when considering robots. Planning the best routes for the robot to follow in order to navigate is one of the main challenges. Global path planning algorithms like A* or Dijkstra's algorithm, which guarantee effective route planning based on a predefined map, are just two examples of techniques that can be used to address this issue.

Techniques like the artificial potential field method or the dynamic window approach can be used for local navigation to achieve real-time obstacle avoidance and adaptation to dynamic objects, addressing the challenges posed by unknown and dynamic scenes.

Another difficulty is localization, which is required for an autonomous robot to determine its precise position and orientation. Particle filtering and Kalman filtering are two techniques that can be used to combine sensor measurements with a predetermined map, compensating for imperfections and adapting to real-world scenarios.

Combining localization and navigation techniques is the final challenge. A robot can identify its location on a map, plan an optimal path, and successfully complete complex tasks by maneuvering precisely to the designated table by developing the necessary software.

Stakeholder (or environmental) requirements of the challenge are:

• Safety - The robot should be able to avoid obstacles and humans without bumping into them
• Time - The robot should take minimal time to complete all deliveries
• Intimate the customer - The robot should announce that it has arrived at the respective table

The border requirements are derived from the stakeholder requirements and encompass the different strategies and considerations taken by the team to cater to each of the overarching stakeholder requirements. The system requirements/specifications give the constraints of the robot and the environment in which it is operated. These were taken into account when trying to implement the border requirements.

The next segment describes the system design incorporated by the team in order to complete the challenge. Initial data and state flow diagrams were created and used as reference to form a structure to work with. These were then modified and updated as necessary. This segment also contains a detailed description of the methods or algorithms used to achieve the different requirements.

The challenge and deliverables

The basic map for the challenge contains the tables and their numbers correspondingly, walls and doors. During the challenge, the robot starts at an area of 1x1 meters in an arbitrary orientation. The robot then has to make its way to each of the tables, orient itself and announce that it has arrived at the respective table before moving to the next table in the sequence. To make things more challenging, a few unknown static and dynamic obstacles were also added to the map. The presence of these obstacles is not known to the robot prior to the commencement of the challenge. And it has to safely navigate around the obstacles without bumping into any of them.

Discussion and future scope

//On what we saw and why