Organization Welcome to § Zoom lectures: T/Th 10:00 – 11:20 (recordings on Canvas) § Zoom office hours CSE 571 Robotics § Dieter: Fri 9am § Chris: Mon 4pm § Xiangyun: Wed 2pm § Tasks § 4 homeworks covering Gaussian processes, particle filters, RRT planning, and deep learning Instructor Dieter Fox § Team project on simulation platform of your choice § Readings: Papers and chapters from Probabilistic Robotics Teaching Assistants § Web page: http://www.cs.washington.edu/571 Xiangyun Meng Chris Xie 3/31/20 CSE-571: Robotics 2 SA-1 • 1 • 2 High-level View on Robot Systems Industrial Robotics Today Sensor data Control system World model Actions 3/31/20 CSE-571: Robotics 3 3/31/20 CSE-571: Robotics 4 • 3 • 4 1
Minerva Architecture of the Control System (CMU + Univ. Bonn, 1998) 3/31/20 CSE-571: Robotics 5 3/31/20 CSE-571: Robotics 6 • 5 • 6 RoboCup: RoboCup-99, Stockholm, Sweden Integrated System Research • Focus on addressing all problems at once • Hardware development • Perception • Low level control • High level planning and decision making • Multi robot systems 3/31/20 CSE-571: Robotics 7 3/31/20 CSE-571: Robotics 8 • 7 • 8 2
RoboCup: Standard Platform DARPA Urban Challenge 2007 3/31/20 CSE-571: Robotics 9 3/31/20 CSE-571: Robotics 10 • 9 • 10 Self-Driving Cars Robots in Warehouses (Kiva@Amazon) CSE 571: Robotics 11 CSE 571: Robotics 12 • 11 • 12 3
Amazon Prime Air DARPA Robotics Challenge 2015 CSE 571: Robotics 13 3/31/20 CSE-571: Robotics 14 • 13 • 14 Getting out of Car Drilling Hole 3/31/20 CSE-571: Robotics 15 3/31/20 CSE-571: Robotics 16 • 15 • 16 4
Humanoid robots Boston Dynamics BigDog CSE 571: Robotics 17 3/31/20 CSE-571: Robotics 18 • 17 • 18 Boston Dynamics Spot Boston Dynamics Atlas 3/31/20 CSE-571: Robotics 19 3/31/20 CSE-571: Robotics 20 • 19 • 20 5
Boston Dynamics Handle Industrial Pick and Place 3/31/20 CSE-571: Robotics 21 3/31/20 CSE-571: Robotics 22 • 21 • 22 Manipulation Service Robots CSE 571: Robotics 23 CSE 571: Robotics 24 • 23 • 24 6
Dexterous Manipulation HaptX Dataglove 3/31/20 CSE-571: Robotics 25 3/31/20 CSE-571: Robotics 26 • 25 • 26 Current Trends / Topics Simulation • Self-driving cars, sidewalk delivery robots, warehouses, manufacturing sites, … • Drones • Industrial pick and place • Manipulation of everyday objects • Complex household tasks (cooking, cleaning, …) • Object detection, 3D mapping, tracking, interaction • Cobots, human robot interaction • Deep learning for perception, control, imitation learning, recognition 3/31/20 CSE-571: Robotics 27 3/31/20 CSE-571: Robotics 28 • 27 • 28 7
Course Outline Goal of this course Week Content • HW / Project Provide an overview of fundamental #1 Introduction / Probabilities problems / techniques in robotics Probabilistic Models / State Estimation #2 Gaussian processes, Bayesian filtering HW1 assigned • Understanding of estimation and decision #2 Motion and sensor models Filtering (localization, tracking, mapping) making in dynamical systems #3 Localization: grid, particle filters, EKF , UKF • Probabilistic modeling and filtering #4 / 5 Mapping: SLAM, RGBD 3D Mapping HW2 assigned Planning / Control • Deterministic and non-deterministic planning #6 / 7 Deterministic and sampling-based planning, exploration HW3 assigned • Learning for perception and modeling #8 Markov decision processes, inverse RL Deep Learning #9 Model learning, visual navigation HW4 assigned #10 Grasping 3/31/20 CSE-571: Robotics 29 3/31/20 CSE-571: Robotics 30 • 29 • 30 8
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