Robotics & Autonomous Control

Kinematics and dynamics, state estimation, feedback and optimal control, and trajectory planning — the control-theoretic depth behind safe autonomy.

Private cohorts & on-site
Format: 3-day (8:30 a.m.–4:30 p.m.)
Level: Advanced
Location: Scheduled on demand · on-site at your facility or a regional venue
Date(s): Not yet scheduled for open enrollment. Get notified when it is, or book it privately for your team.
Includes: Certificate of Completion · printed slide binder · take-home reference text

Get notified when this course is scheduled

One email when dates are set. Or skip the wait: run it as a private cohort, on-site at your plant.

Talk to us about a private cohort
  • One email, no sequence
  • Never shared
  • Reply within one business day

Faculty

Faculty details for this seminar will be announced with the full schedule.

Fees

Early: $1,895 (payment 4+ weeks ahead)
Standard: $2,095 (check/ACH) · $2,165 (card)

Group discount: $200 off per attendee for 3+ from the same organization.

Also Available

  • Corporate on-site delivery at your facility
  • Private cohort sessions
  • Digital curriculum licensing

Seminar Overview

Adaptive cruise, lane keeping, automated parking, and full autonomy all sit on robotics and control foundations. Built from MIT OpenCourseWare's robotics, controls, and systems curriculum, this seminar teaches the core of robotics and autonomous control: kinematics and dynamics, sensing and state estimation, feedback and optimal control, and robot planning. It complements ETS's ADAS course by giving engineers the control-theoretic depth — estimation, feedback, and trajectory planning — that separates a marketed feature from a safe, working one.

Ideal Learner

  • ADAS and autonomous-vehicle engineers at OEMs and suppliers
  • Controls and systems engineers on vehicle programs
  • Robotics engineers and researchers
  • Engineers integrating sensing, planning, and actuation
  • Safety and functional-safety engineers reasoning about control behavior

Learning Objectives

  • Model robot and vehicle kinematics and dynamics
  • Apply state estimation and sensor fusion (Kalman filtering)
  • Design feedback and optimal controllers for vehicle motion
  • Implement trajectory planning and safe decision-making
  • Analyze autonomy architecture from sensing to control

Consulting Sessions

Seminar attendees can sign up for individual consulting sessions with the instructor. Sessions are free for registered attendees, first-come first-served — sign up when registering by calling 248-539-0473 or during the seminar.

Seminar Outline

  • Configuration, rigid-body motion, and 2D/3D kinematics
  • Kinematic and dynamic models of vehicles/robots
  • From math to the physical system
  • Sensors and their models and noise
  • Kalman filtering and sensor fusion
  • Estimating vehicle state from camera/radar/IMU
  • PID and state-space control
  • Stability, response, and robustness
  • Control of longitudinal and lateral motion
  • Optimal control formulation
  • Model-predictive control for trajectory tracking
  • Constraints, safety, and real-time feasibility
  • Path and trajectory planning
  • Handling uncertainty and edge cases
  • Safe decision-making and handover
  • The sensing-to-action pipeline
  • ISO 26262 / SOTIF interaction with control
  • Failure modes and validation of control systems
  • Attendees design a controller/planner for a motion task
  • Simulate and evaluate stability and safety
  • Present the control design and limits

More in Track H — Electrical & Electronic Engineering

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