Schedule

DateWeek DayClassTopicReadingsHW outHW in
8/261M1Introduction to roboticsCh1, Ch2  
8/28 W2Motion planning for point robotsCh8, Ch9.1-3, C.1, C.2HW1 
9/22M—  
9/4 W3Mobile robot planning, C-spaceCh9.4-6, Ch.11.1
9/93M4Mobile robot planning, C-space, cont  
9/11 W5Sampling-based motion planningCh10.1-3HW2HW1
9/164M6Sampling-based motion planning pt 2Ch10.4-6
9/18 W7Kinodynamic motion planningCh11.1-2
9/235M8Kinodynamic motion planning (cont)
9/25 W9Trajectory optimizationCh17.1,17.4-6HW3HW2
9/306M10Trajectory optimization pt 2Ch17.1,17.4-6
10/2 W11Constrained trajectory optimization
10/77M12Constrained trajectory optimization (cont)
10/9 W13Real time planning & controlHW3
10/148M14State estimation and uncertaintyA3, PR 2.1-3HW4
10/16 W15Probabilistic Gaussian filteringPR 2.4-6, 3.1. An Introduction to the Kalman Filter
10/219M16Probabilistic filteringPR 3.2-3, An Introduction to the Kalman Filter
10/23 W17Particle filteringPR 4 
10/2810M18System ID and predictionHW5HW4
10/30 W19System ID and prediction, cont 
11/411M20Rigid registrationCVAA 11.1-3 
11/6 W213D mappingPR 7.1-4
11/1112M22SLAMPR 7.5-6, 8.1-3 HW6HW5
11/13 W23Integrating planning and perception
11/1813M24Planning under uncertainty
11/20 W25Planning with partial observability 
11/2514M— 
11/27 W—   
12/215M26Reinforcement learning  HW6
12/9 W27Reinforcement learning, cont