Handout 7: Lag and PI compensation Eric Feron Lag Compensation goals: Raise gain at low frequencies while leaving rossover &z higher frequencies untouched b≥0. When b=0: Add an integrator in the loop Typical lag Bode Plot

Handout 4: Root-Locus Review Eric Feron Feb17,2004 Summary of Guidelines for plotting a root-locus 1. Mark Poles X and Zeros O 2. Draw the locus on the real axis to the left of an odd number of real poles plus zeros

Handout 6: Proportional Compensation Eric Feron Feb25,2004 Plant under study: 1/10 G(s)=(s+1)(s/10+1)2 Compensation Scheme: We adjust the gain K in the feedback loop (draw the feedback loop below)

Handout 2: Gain and Phase margins Eric Feron Feb6,2004 Nyquist plots and Cauchy's principle Let H(s) be a transfer function. eg H(s)= s2+s+1 (s+1)(s+3) Evaluate H on a contour in the s-plane. (your plots here)

Partially Observable Markov Decision Processes Part II Additional reading: Anthony R. Cassandra. Exact and Approximate Algorithms for Partially Observable Markov Decision Processes. Ph. D. Thesis. Brown University Department of Computer Science, Providence, RI

Defining problem and model so| ution: Minimizing localization error Comb imize gain in explored map bined Information Utilities Integrated Adaptive Information-based Exploration Algorithm

Vision-based SLAM Mobile Robot Localization And Mapping With Uncertainty using Scale-Invariant Visual Landmarks -e,lowe, Little Vikash Mansinghka Spren Riisgaard Outline

Outline Model-based programming The need for model-based reactive planning The Burton model-based reactive planner Artificial Intelligence Space Systems

Massachusetts Institute of Technology 16.412/6.834 Cognitive Robotics Distributed: Monday, 3/31/04 Objective The purpose of the following handout is to walk you step by step through the execution of the FF planning algorithm, on a simple example. The FF algorithm is presented in the paper:

Cognitive Robotics Outline Temporal Action Graph Walksat: Stochastic Local Search Better Neighbor Relaxed Plan A. Gerevini, A. Saetti, I. Serina \Planning through Stochastic Local Search and Temporal Action Graphs\, to appear in Journal of Artificial Intelligence