Cognitive Robotics Lectures and Labs - Revision history

Dvernon: Redirected page to Cognitive Robotics Lecture Plan

2016-12-21T12:19:41Z

Redirected page to Cognitive Robotics Lecture Plan

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Dvernon at 12:10, 21 December 2016

2016-12-21T12:10:53Z

Dvernon at 12:02, 21 December 2016

2016-12-21T12:02:47Z

Dvernon at 11:48, 21 December 2016

2016-12-21T11:48:56Z

Dvernon at 11:42, 21 December 2016

2016-12-21T11:42:02Z

Dvernon at 11:40, 21 December 2016

2016-12-21T11:40:56Z

Dvernon at 11:31, 21 December 2016

2016-12-21T11:31:49Z

Dvernon at 11:30, 21 December 2016

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Dvernon at 13:08, 7 November 2016

2016-11-07T13:08:42Z

Dvernon at 09:19, 7 November 2016

2016-11-07T09:19:37Z

@@ Line 81: / Line 81: @@
 |Anki Cozmo SDK, OpenCV
 |Python tutorial. Cozmo SDK API. OpenCV Python tutorial.
-|Cozmo locomotion (e.g. program Cozmo to drive along a pre-determined route and perform face detection)
+|Cozmo landmark recognition
 |- style="vertical-align: top;"
 | 5
@@ Line 90: / Line 90: @@
 |Anki Cozmo SDK, OpenCV
 |Python tutorial. Cozmo SDK API. OpenCV Python tutorial.
-|Cozmo locomotion (e.g. program Cozmo to follow a cube at a fixed distance; when it stops moving, pick it up)
+|Cozmo object recognition
 |- style="vertical-align: top;"
 | 5
@@ Line 96: / Line 96: @@
 |Mobile robots IV
 |Graph search path planning. Potential field path planning. Navigation. Obstacle avoidance. Object search.
+|Anki Cozmo mobile robot
+|Anki Cozmo SDK, OpenCV
+|Python tutorial. Cozmo SDK API. OpenCV Python tutorial.
 |Cozmo navigation
 |- style="vertical-align: top;"
@@ Line 158: / Line 158: @@
 | 17
 |Cognitive architectures I
-|Role and requirements; cognitive architecture schemas; example cognitive architectures including Soar, ACT-R, Clarion, LIDA, and ISAC.
+|Role and requirements; cognitive architecture schemas; example cognitive architectures including Soar, ACT-R, Clarion, LIDA, and ISAC. The Standard Model.
+|
+|
@@ Line 167: / Line 167: @@
 | 18
 |Cognitive architectures II
-|CRAM: Cognitive Robot Abstract Machine.CRAM Plan Language (CPL). KnowRob knowledge processing and reasoning
+|CRAM: Cognitive Robot Abstract Machine. CRAM Plan Language (CPL). KnowRob knowledge processing and reasoning
+|
 |CRAM
 |Beetz et al. (2010)
-|Exercises on CRAM test programs
+|CRAM test programs
 |- style="vertical-align: top;"
 | 10
@@ Line 180: / Line 180: @@
 |MaxHebb library
 |Harmon and Harmon (1997)
-|Exercise on Hebbian learning
+|Hebbian learning
 |- style="vertical-align: top;"
 | 10
@@ Line 189: / Line 189: @@
 |Anki Cozmo SDK, PSL library
 |Sun and Giles (2001). Billing et al. (2011, 2016).
-|Exercises on PSL test programs
+|PSL test programs
 |- style="vertical-align: top;"
 | 11
@@ Line 198: / Line 198: @@
 |Anki Cozmo SDK
 |Vernon (2014), Chapters 6 & 9. |Lungarella et al. (2003). Asada et al. (2009). Cangelosi and Schlesinger (2015), Chapters 1 & 2.
-|Exercises on PSL test programs
+|PSL test programs
 |- style="vertical-align: top;"
 | 11
@@ Line 216: / Line 216: @@
 |Anki Cozmo SDK,  CINDY library, OpenCV
 |Vernon (2014), Chapter 7.
-|Implement episodic memory on Cozmo
+|Implementation of episodic memory on Cozmo
 |- style="vertical-align: top;"
 | 12
@@ Line 249: / Line 249: @@
 |Social interaction I
 |Joint action. Joint attention. Shared intention. Shared goals. Perspective taking. Theory of mind.
-|Orabec Astra RGBD sensor
+|Orabec Astra RGB-D sensor
 |Ubuntu 14.04, ROS, Imperial College London Perspective Taking library
 |Vernon (2014), Chapter 9.
@@ Line 258: / Line 258: @@
 |Social interaction II
 |Action and intention recognition. Learning from demonstration. Humanoid robotics.
-|Orabec Astra RGBD sensor
+|Kinect RGB-D sensor
 |PSL library
 |Billard et al. (2008). Argall (2009).

@@ Line 60: / Line 60: @@
 |Robot&nbsp; vision V
 |Visual attention. Plane pop-out. RANSAC. Differential geometry. Surface normals and Gaussian sphere. Point clouds. 3D descriptors.
-|Kinect RGBD sensor
+|Kinect RGB-D sensor
 |Vienna University of Technology RGB-D Segmentation Library and V4R Library
 |Szeliski (2010), Sections 12.4. Point Cloud Library tutorial.

@@ Line 27: / Line 27: @@
 | OpenCV
 | Kragic and Vincze (2010). Szeliski (2010), Sections 1.1, 1.2, 2.3, 3.2, 4.2. Vernon (1991), Sections 2.1, 2.1
-|Exercises on image acquisition and image processing using OpenCV
+|Image acquisition and image processing using OpenCV
 |- style="vertical-align: top;"
 | 2
@@ Line 36: / Line 36: @@
 | OpenCV
 | 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.
-| Exercises on Hough transforms and colour segmentation using OpenCV
+| Hough transforms and colour segmentation using OpenCV
 |- style="vertical-align: top;"
 | 2
@@ Line 45: / Line 45: @@
 | OpenCV, Vienna University of Technology BLORT Library
 | Szeliski (2010), Sections 4.1.2, 4.1.3, 4.1.4, 4.1.5, 14.1.1.
-| Exercises on face detection and object recognition using OpenCV
+| Face detection and object recognition using OpenCV
 |- style="vertical-align: top;"
 | 3
@@ Line 54: / Line 54: @@
 |OpenCV
 |Szeliski (2010), Sections 2.1, 11.1, 11.2, 11.3. Vernon (1991), Section 8.6, 9.4.2.
-|Exercise on camera calibration
+|Camera calibration
 |- style="vertical-align: top;"
 | 3
@@ Line 63: / Line 63: @@
 |Vienna University of Technology RGB-D Segmentation Library and V4R Library
 |Szeliski (2010), Sections 12.4. Point Cloud Library tutorial.
-|Exercises analysing point cloud data from RGB-D camera
+|Analysis of point cloud data from RGB-D camera
 |- style="vertical-align: top;"
 | 4
@@ Line 70: / Line 70: @@
 |Differential drive locomotion. Forward and inverse kinematics. Holonomic and non-holonomic constraints.  Cozmo mobile robot.
 |Anki Cozmo mobile robot
-|Anki Cozmo SDK
+|Anki Cozmo SDK, OpenCV
 |Python tutorial. Cozmo SDK API. OpenCV Python tutorial.
-|Exercises on Cozmo locomotion (e.g. program Cozmo to drive along a pre-determined route and perform face detection)
+|Cozmo locomotion (e.g. program Cozmo to drive along a pre-determined route and perform face detection)
 |- style="vertical-align: top;"
 | 4
@@ Line 79: / Line 79: @@
 |Map representation. Probabilistic map-based localization. Landmark-based localization.
 |Anki Cozmo mobile robot
-|Anki Cozmo SDK
+|Anki Cozmo SDK, OpenCV
 |Python tutorial. Cozmo SDK API. OpenCV Python tutorial.
-|Exercises on Cozmo locomotion (e.g. program Cozmo to drive along a pre-determined route and perform face detection)
+|Cozmo locomotion (e.g. program Cozmo to drive along a pre-determined route and perform face detection)
 |- style="vertical-align: top;"
 | 5
@@ Line 88: / Line 88: @@
 |SLAM: simultaneous localization and mapping. Extended Kalman Filter (EKF) SLAM. Visual SLAM. Particle filter SLAM.
 |Anki Cozmo mobile robot
-|Anki Cozmo SDK
+|Anki Cozmo SDK, OpenCV
 |Python tutorial. Cozmo SDK API. OpenCV Python tutorial.
-|Exercises on Cozmo locomotion (e.g. program Cozmo to follow a cube at a fixed distance; when it stops moving, pick it up and bring it home)
+|Cozmo locomotion (e.g. program Cozmo to follow a cube at a fixed distance; when it stops moving, pick it up)
 |- style="vertical-align: top;"
 | 5
 | 10
 |Mobile robots IV
-| Graph search path planning. Potential field path planning. Navigation. Obstacle avoidance. Object search.
+|Graph search path planning. Potential field path planning. Navigation. Obstacle avoidance. Object search.
-|Orabec Astra RGBD sensor
-|Ubuntu 14.04, ROS, Gazebo, Java 7
-|ROS tutorials. Protege4Pizzas10Minutes tutorial.Manchester OWL tutorial.
-|ROS TurtleBot view planning simulation
+|Cozmo navigation
 |- style="vertical-align: top;"
 | 6
@@ Line 108: / Line 108: @@
 |Arduino sketch programs for Lynxmotion
 |Paul (1981), Chapters 1 & 2.
-|Exercises to move end-effector along various paths in joint space
+|Move end-effector along various paths in joint space
 |- style="vertical-align: top;"
 | 6
@@ Line 117: / Line 117: @@
 |Arduino sketch programs for Lynxmotion
 |Paul (1981), Chapter 3.
-|Exercises to move end-effector along various paths in Cartesian frame of reference
+|Move end-effector along various paths in Cartesian frame of reference
 |- style="vertical-align: top;"
 | 7
@@ Line 126: / Line 126: @@
 |Arduino sketch programs for Lynxmotion
 |Vernon (1991), Sections 8.1-8.4.
-|Exercise to compute the pose of a light cube
+|Compute the pose of a light cube
 |- style="vertical-align: top;"
 | 7
@@ Line 135: / Line 135: @@
 |Arduino sketch programs for Lynxmotion
 |Vernon (1991), Sections 8.1-8.4
-|Exercises to implement a program to move light cube from one position/pose to another position/pose
+|Implement a program to move light cube from one position/pose to another position/pose
 |- style="vertical-align: top;"
 | 8

@@ Line 31: / Line 31: @@
 | 2
 | 3
-| Robot vision II
+| Robot&nbsp; vision II
 | Segmentation. Hough transform: line, circle, and generalized transform; extension to codeword features. Colour-based segmentation.
 | USB camera

@@ Line 22: / Line 22: @@
 | 1
 | 2
-| Robot vision I
+| Robot&nbsp; vision I
 | Optics, sensors, and image formation. Image acquisition. Image filtering. Edge detection.
-| Orabec Astra RGBD sensor
+| USB camera
 | OpenCV
 | Kragic and Vincze (2010). Szeliski (2010), Sections 1.1, 1.2, 2.3, 3.2, 4.2. Vernon (1991), Sections 2.1, 2.1
@@ Line 33: / Line 33: @@
 | Robot vision II
 | Segmentation. Hough transform: line, circle, and generalized transform; extension to codeword features. Colour-based segmentation.
-| Orabec Astra RGBD sensor
+| USB camera
 | OpenCV
 | 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.
@@ Line 40: / Line 40: @@
 | 2
 | 4
-| Robot vision III
+| Robot&nbsp; vision III
 | Object recognition. Interest point operators. Gradient orientation histogram - SIFT descriptor. Colour histogram intersection. Haar features, boosting, face detection.
-| Orabec Astra RGBD sensor
+| USB camera
 | OpenCV, Vienna University of Technology BLORT Library
 | Szeliski (2010), Sections 4.1.2, 4.1.3, 4.1.4, 4.1.5, 14.1.1.
@@ Line 49: / Line 49: @@
 | 3
 | 5
-|Robot vision IV
+|Robot&nbsp; vision IV
 |Homogeneous coordinates and transformations. Perspective transformation. Camera model and inverse perspective transformation. Stereo vision. Epipolar geometry. Structured light & RGB-D cameras.
-|Orabec Astra RGBD sensor
+|USB camera
 |OpenCV
 |Szeliski (2010), Sections 2.1, 11.1, 11.2, 11.3. Vernon (1991), Section 8.6, 9.4.2.
@@ Line 58: / Line 58: @@
 | 3
 | 6
-|Robot vision V
+|Robot&nbsp; vision V
 |Visual attention. Plane pop-out. RANSAC. Differential geometry. Surface normals and Gaussian sphere. Point clouds. 3D descriptors.
-|Orabec Astra RGBD sensor
+|Kinect RGBD sensor
 |Vienna University of Technology RGB-D Segmentation Library and V4R Library
 |Szeliski (2010), Sections 12.4. Point Cloud Library tutorial.
@@ Line 90: / Line 90: @@
 |Anki Cozmo SDK
 |Python tutorial. Cozmo SDK API. OpenCV Python tutorial.
-|Exercises on Cozmo locomotion (e.g. program Cozmo to follow a cube at a fixed distance; wnen it stops moving, pick it up and bring it home)
+|Exercises on Cozmo locomotion (e.g. program Cozmo to follow a cube at a fixed distance; when it stops moving, pick it up and bring it home)
 |- style="vertical-align: top;"
 | 5
@@ Line 139: / Line 139: @@
 | 8
 | 15
+|
-|Russell and Norvig (2010), Chapter 6. Dechter (2003), Chapter 1.
-|Exercises on Meta-CSP
 |- style="vertical-align: top;"
 | 8
 | 16
-|Constraint-based reasoning for robotics II
-|Planning and navigation with multiple mobile robots
+|
 |- style="vertical-align: top;"
 | 9

@@ Line 9: / Line 9: @@
 ! Required&nbsp;software
 ! Pre-class&nbsp;reading
-! Lab&nbsp;exercises
+! Homework&nbsp;exercises
 |- style="vertical-align: top;"
 | 1

@@ Line 230: / Line 230: @@
 | 25
 |Internal simulation II
 |HAMMER cognitive architecture
 |Boost, Imperial College London HAMMER library
 |Demiris and Khadhouri (2006). Sarabia et al. (2011).

@@ Line 263: / Line 263: @@
 |}
 </small>
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