View source for Cognitive Robotics Lecture Plan

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