This course is a hands-on introduction to algorithms required for autonomous driving, and more generally, mobile robots. We will cover a range of topics including time-optimal control, planning, and state estimation. Students will work in groups of two to implement the projects on actual scale 1/10 autonomous RC cars. There will be weekly assignments on implementing each building block, and that culminate in a final project to have your autonomous car autonomously explore an environment and visit prescribed locations to collect points.
Suggested text book: Probabilistic Robotics
Lectures: Mondays and Wednesdays, 9:00 - 10:00 AM Labs: Fridays, 9:00 - 10:00 AM
Instructor
Joydeep Biswas, joydeepb@cs.utexas.edu
Office hours: Fridays, 2:00-3:00 PM
Teaching Assitant
Jarrett Holtz, jaholtz@cs.utexas.edu
Office hours: Mondays, 1:00-2:00 PM
Assignments will be completed in groups of two. There will be three milestones, each with weekly checkpoints. Teams must maintain a report covering:
Final reports are due at the end of each milestone, but each checkpoint submission must include a weekly progress report.
Checkpoint 0 is ungraded, and must be completed individually during the first
lab.
Checkpoints 1-10: 50% Total (5% each)
Milestones 1-3: 30% Total (10% each)
Milestone 4: 20%
Each checkpoint is graded on the progress report, and a check for the deliverable for the week.
Each milestone is graded on the final report (contents listed below) and a live demonstration on the car.
Integration and Optimization will be key: each milestone involves integrating previous checkpoints, and offer an opportunity to improve upon past performance by optimizing the approach.
Each team is responsible for taking care of their own car and associated peripherals. You must follow all guidlines and safety instructions in the reference manual.
The computers in the GDC 1.310 lab have the necessary software packages installed for you to run the course software, including the simulator, visualizations, and handout code. We encourage teams to use the lab computers to work on the assignments.