Difference between revisions of "Cognitive Robotics Lectures and Labs"

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#REDIRECT [[Cognitive Robotics Lecture Plan]]
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! Week
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! Lecture
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! Topic
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! Material covered
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! Required&nbsp;hardware
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! Required&nbsp;software
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! Pre-class&nbsp;reading
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! Homework&nbsp;exercises
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|- style="vertical-align: top;"
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| 1
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| 1
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| Cognitive robotics
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| Introduction to AI and cognition in robotics. Industrial requirements. Artificial cognitive systems. Cognitivist, emergent, and hybrid paradigms in cognitive science. Autonomy.
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| None
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| None
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| Vernon (2014), Chapters 1, 2, and 4.
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| Installation of software tools.
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| 1
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| 2
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| Robot&nbsp; vision I
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| Optics, sensors, and image formation. Image acquisition. Image filtering. Edge detection.
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| USB camera
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| OpenCV
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| Kragic and Vincze (2010). Szeliski (2010), Sections 1.1, 1.2, 2.3, 3.2, 4.2. Vernon (1991), Sections 2.1, 2.1
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|Image acquisition and image processing using OpenCV
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| 2
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| 3
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| Robot&nbsp; vision II
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| Segmentation. Hough transform: line, circle, and generalized transform; extension to codeword features. Colour-based segmentation.
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| USB camera
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| OpenCV
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| Szeliski (2010), Sections 3.1.2, 3.3.4, 4.3.2. Vernon (1991), Section 3.1, 3.2, 3.3, 4.2.1, 4.2.2, 5.3, 6.4.
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| Hough transforms and colour segmentation using OpenCV
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|- style="vertical-align: top;"
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| 2
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| 4
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| Robot&nbsp; vision III
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| Object recognition. Interest point operators. Gradient orientation histogram - SIFT descriptor. Colour histogram intersection. Haar features, boosting, face detection.
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| USB camera
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| OpenCV, Vienna University of Technology BLORT Library
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| Szeliski (2010), Sections 4.1.2, 4.1.3, 4.1.4, 4.1.5, 14.1.1.
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| Face detection and object recognition using OpenCV
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|- style="vertical-align: top;"
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| 3
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| 5
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|Robot&nbsp; vision IV
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|Homogeneous coordinates and transformations. Perspective transformation. Camera model and inverse perspective transformation. Stereo vision. Epipolar geometry. Structured light & RGB-D cameras.
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|USB camera
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|OpenCV
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|Szeliski (2010), Sections 2.1, 11.1, 11.2, 11.3. Vernon (1991), Section 8.6, 9.4.2.
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|Camera calibration
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|- style="vertical-align: top;"
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| 3
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| 6
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|Robot&nbsp; vision V
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|Visual attention. Plane pop-out. RANSAC. Differential geometry. Surface normals and Gaussian sphere. Point clouds. 3D descriptors.
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|Kinect RGB-D sensor
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|Vienna University of Technology RGB-D Segmentation Library and V4R Library
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|Szeliski (2010), Sections 12.4. Point Cloud Library tutorial.
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|Analysis of point cloud data from RGB-D camera
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|- style="vertical-align: top;"
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| 4
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| 7
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|Mobile robots I
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|Differential drive locomotion. Forward and inverse kinematics. Holonomic and non-holonomic constraints.  Cozmo mobile robot.
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|Anki Cozmo mobile robot
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|Anki Cozmo SDK, OpenCV
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|Python tutorial. Cozmo SDK API. OpenCV Python tutorial.
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|Cozmo locomotion (e.g. program Cozmo to drive along a pre-determined route and perform face detection)
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|- style="vertical-align: top;"
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| 4
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| 8
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|Mobile robots II
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|Map representation. Probabilistic map-based localization. Landmark-based localization.
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|Anki Cozmo mobile robot
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|Anki Cozmo SDK, OpenCV
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|Python tutorial. Cozmo SDK API. OpenCV Python tutorial.
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|Cozmo landmark recognition
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|- style="vertical-align: top;"
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| 5
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| 9
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|Mobile robots III
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|SLAM: simultaneous localization and mapping. Extended Kalman Filter (EKF) SLAM. Visual SLAM. Particle filter SLAM.
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|Anki Cozmo mobile robot
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|Anki Cozmo SDK, OpenCV
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|Python tutorial. Cozmo SDK API. OpenCV Python tutorial.
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|Cozmo object recognition
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|- style="vertical-align: top;"
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| 5
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| 10
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|Mobile robots IV
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|Graph search path planning. Potential field path planning. Navigation. Obstacle avoidance. Object search.
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|Anki Cozmo mobile robot
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|Anki Cozmo SDK, OpenCV
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|Python tutorial. Cozmo SDK API. OpenCV Python tutorial.
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|Cozmo navigation
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|- style="vertical-align: top;"
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| 6
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| 11
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|Robot arms I
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|Homogeneous transformations. Frame-based pose specification. Denavit-Hartenberg specifications. Robot kinematics.
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|Lynxmotion 5DoF arm, Arduino interface
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|Arduino sketch programs for Lynxmotion
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|Paul (1981), Chapters 1 & 2.
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|Move end-effector along various paths in joint space
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|- style="vertical-align: top;"
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| 6
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| 12
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|Robot arms II
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|Analytic inverse kinematics. Iterative approaches. Kinematic structure learning.  Kinematics structure correspondences.
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|Lynxmotion 5DoF arm, Arduino interface
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|Arduino sketch programs for Lynxmotion
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|Paul (1981), Chapter 3.
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|Move end-effector along various paths in Cartesian frame of reference
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|- style="vertical-align: top;"
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| 7
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| 13
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|Robot arms III
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|Robot manipulation. Frame-based task specification. Vision-based pose estimation.
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|Lynxmotion 5DoF arm, Arduino interface
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|Arduino sketch programs for Lynxmotion
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|Vernon (1991), Sections 8.1-8.4.
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|Compute the pose of a light cube
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|- style="vertical-align: top;"
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| 7
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| 14
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|Robot arms IV
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|Language-based programming. Programming by demonstration.
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|Lynxmotion 5DoF arm, Arduino interface
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|Arduino sketch programs for Lynxmotion
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|Vernon (1991), Sections 8.1-8.4
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|Implement a program to move light cube from one position/pose to another position/pose
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|- style="vertical-align: top;"
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| 8
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| 15
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|- style="vertical-align: top;"
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| 8
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| 16
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|- style="vertical-align: top;"
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| 9
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| 17
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|Cognitive architectures I
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|Role and requirements; cognitive architecture schemas; example cognitive architectures including Soar, ACT-R, Clarion, LIDA, and ISAC. The Standard Model.
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|
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|Vernon (2014) Chapter 3. Chella et al. (2013). Scheutz et al. (2013). Vernon et al. (2016).
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|Group discussion on which cognitive architectures are suitable for cognitive robotics
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|- style="vertical-align: top;"
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| 9
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| 18
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|Cognitive architectures II
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|CRAM: Cognitive Robot Abstract Machine. CRAM Plan Language (CPL). KnowRob knowledge processing and reasoning
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|
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|CRAM
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|Beetz et al. (2010)
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|CRAM test programs
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|- style="vertical-align: top;"
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| 10
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| 19
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|Learning and development I
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|Supervised, unsupervised, and reinforcement learning. Hebbian learning.
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|
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|MaxHebb library
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|Harmon and Harmon (1997)
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|Hebbian learning
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|- style="vertical-align: top;"
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| 10
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| 20
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|Learning and development II
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|Predictive sequence learning (PSL).
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|Anki Cozmo mobile robot
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|Anki Cozmo SDK, PSL library
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|Sun and Giles (2001). Billing et al. (2011, 2016).
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|PSL test programs
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|- style="vertical-align: top;"
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| 11
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| 21
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|Learning and development III
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|Cognitive development in humans and robots.
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|Anki Cozmo mobile robot
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|Anki Cozmo SDK
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|Vernon (2014), Chapters 6 & 9. |Lungarella et al. (2003). Asada et al. (2009). Cangelosi and Schlesinger (2015), Chapters 1 & 2.
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|PSL test programs
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|- style="vertical-align: top;"
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| 11
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| 22
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|Learning and development IV
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|Value systems for developmental and cognitive robots.
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|Merrick (2016). Vernon et al. (2016).
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|Group discussion on cognitive development in robotics
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|- style="vertical-align: top;"
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| 12
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| 23
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|Memory and Prospection
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|Declarative vs. procedural memory. Semantic memory. Episodic memory
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|Anki Cozmo mobile robot
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|Anki Cozmo SDK,  CINDY library, OpenCV
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|Vernon (2014), Chapter 7.
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|Implementation of episodic memory on Cozmo
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|- style="vertical-align: top;"
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| 12
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| 24
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|Internal simulation I
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|Forward and inverse models, internal simulation hypothesis, internal simulation with PSL
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|Anki Cozmo mobile robot
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|Anki Cozmo SDK, PSL library
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|Vernon (2014), Chapter 8. Billing et al. (2016).
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|Exercises on PSL test programs
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|- style="vertical-align: top;"
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| 13
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| 25
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|Internal simulation II
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|HAMMER cognitive architecture
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|Boost, Imperial College London HAMMER library
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|Demiris and Khadhouri (2006). Sarabia et al. (2011).
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|Exercise on HAMMER tutorial using the ICL library
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|- style="vertical-align: top;"
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| 13
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| 26
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|Visual attention
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|Visual attention. Spatial attention vs. selective attention. Saliency functions. Selective Tuning.  Overt attention. Inhibition of return. Habituation. Top-down attention.
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|Anki Cozmo mobile robot
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|Anki Cozmo SDK, CINDY library
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|Borji and Itti (2013).
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|Implement visual attention on Cozmo
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|- style="vertical-align: top;"
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| 14
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| 27
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|Social interaction I
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|Joint action. Joint attention. Shared intention. Shared goals. Perspective taking. Theory of mind.
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|Orabec Astra RGB-D sensor
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|Ubuntu 14.04, ROS, Imperial College London Perspective Taking library
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|Vernon (2014), Chapter 9.
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|Exercise on perspective taking using the ICL library
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|- style="vertical-align: top;"
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| 14
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| 28
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|Social interaction II
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|Action and intention recognition. Learning from demonstration. Humanoid robotics.
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|Kinect RGB-D sensor
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|PSL library
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|Billard et al. (2008). Argall (2009).
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|Exercise on learning from demonstration using the PSL library
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|}
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</small>
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Back to [[Cognitive Robotics]]
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Latest revision as of 08:19, 21 December 2016