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Micro-Diploma May-26

Robotics Systems Engineering

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Robotics systems engineering sits at the intersection of mechanical design, embedded software, and intelligent control, creating machines that sense, decide, and act in the physical world. This course gives you a structured path from foundational principles to advanced system integration, building the skills needed to design, analyze, and implement real robotic systems.

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Structured Phased path
Viable Real-world examples
Progressive Job-aligned skills
Demand for robotics engineers continues to grow across manufacturing, logistics, healthcare, and defense, yet most practitioners enter the field with deep knowledge in only one discipline while lacking the systems-level thinking required to build complete robots. A robotics system fails not because one component is poorly designed, but because the interfaces between components are misunderstood. This course addresses that gap by treating the robot as an integrated system, covering every layer from kinematics and actuators to perception pipelines and safety certification.

What You Will Learn

  • 1 Learn the foundational principles of robotics systems engineering, including robot classifications, coordinate frames, and the systems engineering lifecycle as applied to robotic platforms.
  • 2 Understand robot kinematics and dynamics, covering forward and inverse kinematics, Jacobian analysis, and the equations of motion that govern robot behavior.
  • 3 Apply actuator and sensor technologies by analyzing motor types, drive electronics, encoder feedback, and the sensor modalities used for perception and state estimation.
  • 4 Explore robot control architectures, including PID control, computed torque control, and behavior-based systems for autonomous decision-making.
  • 5 Implement robot operating system frameworks, understanding the ROS 2 computation graph, node communication patterns, and real-time execution constraints.
  • 6 Develop robot perception pipelines using point cloud processing, camera calibration, object detection algorithms, and sensor fusion techniques.
  • 7 Analyze motion planning and path planning algorithms, including configuration space theory, sampling-based planners, and trajectory optimization methods.
  • 8 Build mobile robot navigation systems covering simultaneous localization and mapping, occupancy grids, and autonomous navigation stacks.
  • 9 Understand human-robot interaction design principles, including safety standards, collaborative robot specifications, and user interface design for robotic systems.
  • 10 Create a complete robotics system integration framework by applying systems verification, validation testing, and functional safety certification processes.

What's Included

Core self-paced training
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