MARINE ROBOTICS

EMA/ME 458

Feedback control theory fundamentals; numerical optimal control algorithms underpinning autonomous systems; quadcopter kinematics dynamics; quadcopter control and trajectory planning; hands-on labs on a nano quadcopter platform.

ME 468

Introduction to the Robot Operating System (ROS). Concepts of vehicle dynamics modeling and simulation, with focus on tire, suspension, steering system, and powertrain modeling. Simulation of sensors (camera, lidar, radar, GPS, IMU). Terramechanics modeling for mobility on deformable terrains. Introduction to the autonomy stack (sensing, perception, planning, and control). Elements of artificial intelligence in autonomy. Elements of verification and validation.

ECE/ME 439

Hands-on introduction to key concepts and tools underpinning robotic systems in use and development today. Intended to give students the tools to understand robotic systems, to explore robotics for their own purposes, and to pursue advanced study in the field. Students are expected to have familiarity with a high level programming language such as Python (recommended), MATLAB, Java or Julia.

ME 738

Rigid body models of robots, constraints and contact, motion planning methods including sampling based, trajectory optimizations, state estimation algorithms including linear observers and filters, Kalman filters, optimization-based filters, feedback control methods including linear controls, Impedance Control, optimization-based controllers, Differential Dynamic Programming, Lyapunov Analysis and Design, and Underactuations. Knowledge of robotic systems [such asE C E/​M E  439andE C E/​M E  441] is strongly recommended.

ECE/ME 441

Robotics analysis and design, focusing on the analytical fundamentals specific to robotic manipulators. Serial chain robotic manipulator forward and inverse kinematics, differential kinematics, dynamics, trajectory generation, and controls. Builds on knowledge of high-level computational programming language such as Matlab.