Autonomous Mobile Robots Training

Live Online & Classroom Enterprise Training

Learn the fundamentals, architecture, and applications of Autonomous Mobile Robots (AMRs) — from navigation and perception to control systems and real-world deployment in industrial and research environments.

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What is Autonomous Mobile Robots Course about?

The Autonomous Mobile Robots course provides a comprehensive understanding of how intelligent robots operate, navigate, and interact autonomously within dynamic environments. Learners will explore core concepts such as localization, mapping, motion planning, and sensor fusion, alongside key technologies like LIDAR, SLAM (Simultaneous Localization and Mapping), and AI-based perception. The course combines theoretical foundations with hands-on insights into robot software frameworks such as ROS (Robot Operating System) and their applications in logistics, manufacturing, and autonomous vehicles.

What are the objectives of Autonomous Mobile Robots Course ?

Understand the architecture and components of Autonomous Mobile Robots.
Learn about sensors, perception, and control algorithms used in AMRs.
Gain knowledge of navigation, path planning, and SLAM techniques.
Explore ROS-based implementation and integration of AMR systems.
Apply AMR concepts to industrial and real-world autonomous operations.

Who is Autonomous Mobile Robots Course for?

Robotics Engineers and Developers.
Automation and Mechatronics Professionals.
AI and Machine Learning Practitioners.
Research Scholars in Robotics and Autonomous Systems.
Students or professionals entering the field of industrial robotics.

What are the prerequisites for Autonomous Mobile Robots Course?

Prerequisites:

Basic knowledge of robotics and automation systems.
Understanding of programming languages (Python, C++, or MATLAB).
Familiarity with control systems and kinematics concepts.
Fundamental knowledge of sensors and embedded systems.
Interest in AI, machine learning, or computer vision.

Learning Path:

Introduction to Autonomous Mobile Robots and Applications
Sensors, Perception, and Localization Techniques
Path Planning, Control Systems, and SLAM
ROS Framework and AMR Software Implementation
Industry Use Cases, Simulation, and Deployment

Related Courses:

Mobile Robotics Fundamentals
Robot Operating System (ROS) Essentials
AI for Robotics and Automation
Computer Vision for Intelligent Systems

Available Training Modes

Live Online Training

5 Days

Course Outline Expand All

Expand All

Module 1 - Introduction and Motivation

Overview of mobile robots and their applications in various industries.

Core concepts of autonomy and mobility in robots.

Historical development and future trends in mobile robotics

Module 2 - Locomotion

Types of Locomotion

Wheeled Locomotion

Legged Locomotion

Mechanisms and Actuation

Overview of actuators (electric, hydraulic, and pneumatic).

Design considerations for efficient locomotion.

Module 3 - Mobile Robot Kinematics

Kinematic Models of Mobile Robots

Wheel-Terrain Interaction

Holonomic and Non-Holonomic Constraints

Motion Control

Case studies of kinematic models in real-world robots

Module 4 - Perception I

Introduction to Robot Perception

Proximity Sensors

Data Acquisition

Visual Sensors

Data Acquisition

Module 5 - Perception II

Laser Rangefinders and LiDAR

IMU (Inertial Measurement Units)

Sensor Fusion

Mapping the Environment

Module 6 - Perception III

Advanced Perception with AI

Point Cloud Processing

Semantic Understanding

Real-Time Perception

Module 7 - Localization I

Probabilistic Robotics

Bayesian Filters

Global vs. Local Localization

Landmark-Based Localization

Module 8 - Localization II

Advanced Localization Techniques

Monte Carlo Localization (MCL)

Localization in Dynamic Environments

Sensor Fusion in Localization

Case studies of localization systems in commercial autonomous robots

Module 9 - SLAM I

Mathematical Foundations

Sensor-Based SLAM

Feature-Based SLAM

Module 10 - SLAM II

Graph-Based SLAM

Grid-Based SLAM

Visual SLAM

Real-Time SLAM

Emerging Trends

Module 11 - Planning I

Graph-Based Path Planning

Sampling-Based Path Planning

Path Smoothing and Optimization

Module 11 - Planning II

Dynamic Path Planning

Multi-Robot Path Planning

Behavior-Based Planning

Real-Time Path Planning

Path Optimization

Applications and Tools

Who is the instructor for this training?

The trainer for this Autonomous Mobile Robots Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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