MAE 6245 — Robotics Systems
MAE 6245 · Graduate Course

Robotics Systems

A systems-level introduction to robotics, focusing on how robots sense, reason, and act under uncertainty.

Topics span dynamics and control, sensing and vision, estimation, planning, and learning in integrated robotic systems.

2026 Spring Details →
Robotics Systems — overview visual
Robotics systems often fail in the real world not because of “one bad module,” but because small modeling, sensing, and decision errors compound through the pipeline. This course treats robotics as an integrated system and emphasizes assumptions, uncertainty, and system-level evaluation.
The class is research-oriented: critical reading, student-led paper discussions, and a semester-long open-ended project.
Project Tracks

Manipulation

  • learning policies from demonstrations / datasets
  • generalization across objects, scenes, and tasks
  • benchmarking and reproducible evaluation
  • sim-to-real transfer and real-robot testing

Navigation

  • offline / interactive navigation learning
  • robustness and generalization to new environments
  • comparisons with classical planning baselines
  • evaluation in simulation and (when possible) real settings

Students are welcome to propose related topics with instructor approval.

Resources

Simulators

Gazebo — ROS-integrated sim-to-real workflowPyBullet — lightweight Python-first simulatorNVIDIA Isaac Lab — robot learning framework

Learning / Systems

LeRobot — data-driven pipelines for manipulationNaVILA — vision-language-action navigationsqrtVINS — reference VIO / localization system

Deep Learning

Google Colab — lightweight GPU accessPyTorch — common DL framework in robotics
MAE 4182 — Electromechanical Control System Design
Fall 2025 · MAE 4182

Electromechanical Control System Design

Modeling and feedback design for real electromechanical systems, emphasizing stability, performance, and robustness in time and frequency domains.

Students learn classical control (PID, root locus, Bode) and use Python to simulate, analyze, and validate controller behavior in practice.

ModelingStabilityRobustnessPython