Modern Robotics: Foundations + Kinematics
Course provided by Model Institute of Engineering & Technology
4 modules
Build smarter solutions with drone data & Python.
5 Level NCrF
National Credit Framework
90 Hours
Flexible Learning
Beginner Level
No prior experience required
Micro Course
03 Credit
Course Overview
This course introduces learners to the fundamentals of data science applied to unmanned aerial systems (UAS). Students will gain hands-on experience in processing, cleaning, and analyzing drone-collected datasets using Python. By the end of the course, learners will be able to transform raw aerial data into meaningful patterns, insights, and visualizations to support decision-making in various industries.
Key Learning Highlights
- Learn Python programming for drone data analysis
- Process aerial imagery and sensor-based datasets
- Apply statistical and machine learning techniques to UAS data
- Create impactful data visualizations and reports
- Practical, project-driven learning with real drone datasets
Tools & Platforms Used
Learning Outcome
By the end of this course, students will be able to:
Describe robotic configurations using configuration space and degrees of freedom.
Analyze holonomic and non-holonomic constraints in robotic mechanisms.
Represent spatial velocities and forces using twists and wrenches.
Compute forward and inverse kinematics using the Product-of-Exponentials (PoE) formula.
Implement velocity kinematics and statics for serial-chain manipulators.
Master the course with just 4 Modules
Gain a solid foundation in modern robotics through 4 carefully designed modules. From understanding robot configurations and rigid-body motion to mastering kinematics, each module builds practical skills and theoretical knowledge, enabling you to design, analyze, and control robotic systems efficiently.
Introduction to Robot Configuration and Motion
- Overview of robot manipulators and configuration space
- Degrees of freedom, C-space topology
- Holonomic vs. non-holonomic constraints
- Implicit and explicit representations of configurations
Mathematical Modeling of Motion
- Coordinate frames, transformation matrices
- Representation of rotation and translation
- Introduction to Lie groups and SE(3)
- Spatial velocities and forces: twists and wrenches
Forward and Inverse Kinematics
- Forward kinematics using the PoE formula
- Homogeneous transformation matrices
- Velocity kinematics: Jacobians
- Statics of manipulators: relating joint torques to end-effector forces
- Inverse kinematics: closed-form and numerical methods
Robot Chains and Mechanism Analysis
- Kinematics of robots with closed chains
- Redundancy and singularity in kinematic chains
- Case studies of industrial arms and robotic platforms
