1. Advanced Topics in Robotics CS 790 (X)
Lecture 1
Instructor: Monica Nicolescu

2. General Information Instructor: Dr. Monica Nicolescu Class webpage:
Office hours: Wednesday 10am-noon, 1-2pm
Room: SEM 239
Class webpage:
Time and place
Tuesday, Thursday: 1:00-2:15pm WRB 4051
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3. What will we Learn? Cover fundamental aspects of robotics
Control architectures
Sensing and perception
Advanced robotics techniques
Robot learning by demonstration
Navigation and mapping
Multiple robot systems: coordination and cooperation
Human-robot interaction
Biologically inspired robotics
Hands-on experience
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4. Readings and Presentations
Two papers (on average) discussed at each lecture
Each paper is presented by a student
For some lectures we will have one background reading
Presentation guidelines (papers)
At most 30 minutes
Briefly summarize the paper
Discuss the paper, its strengths, weaknesses, any points needing clarification
Addressing any questions the other students may have
Presentation guidelines (background reading)
At most 45 minutes
Area challenges, existing approaches, case studies
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5. Readings and Paper Reports
For each paper, all students must submit, at the beginning of the class a brief report of the paper
Report format (typed)
Student’s name
Title and authors of the paper
A short paragraph summarizing the contributions of the paper
A critique of the paper that addresses the strengths and weaknesses of the paper
Summary of background reading if applicable
Area challenges, existing approaches, case studies
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6. Project Individual project on topics covered in class
Project topics: an implementation of either:
a single robot system (involving complex behavior and demonstrated on a physical robot) or
a multi-robot system (involving cooperation/ communication/ coordination between robots and demonstrated in simulation or on a physical robot)
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7. Project/Lab Testbeds
The Robot Operating System (
ROS provides libraries and tools to create robot applications
ROS provides hardware abstraction, device drivers, libraries, visualizers, message-passing, package management
Stage is a ROS-compatible high-fidelity indoor multi-robot simulation testbed
Allows for direct porting to ROS-compatible physical robots
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8. Project/Lab Testbeds 11 ActivMedia Pioneer 3 DX
sonar sensors, laser, PTZ camera, onboard computer
One Player-compatible ActivMedia Pioneer 1 AT robot
7 sonar sensors and requires the use of a laptop (not provided)
10 Robosapien robots
On-board CPU
10 Create robots
1.2 GHz CPU
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9. Project/Lab Testbeds NAO humanoid robot Baxter humanoid robot
PR2 humanoid robot
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10. Project Report Should include the following: Title, author Abstract
Introduction and motivation
Review of relevant literature
Problem definition: project goals, assumptions, constraints, and evaluation criteria
Details of proposed approach
Results and objective experimental evaluation
Discussion (strengths and weaknesses) and conclusion
References
Appendix (relevant code or algorithms)
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11. Class Policy Grading Late submissions Attendance Paper reports: 20%
Paper presentations: 20%
Participation in class discussions: 20%
Final project: 40%
Late submissions
No late submissions will be accepted
Attendance
Full participation in class discussions and labs
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12. Important Dates/Milestones
February 17
Project topic proposal and presentation (5 slides)
One page that outlines the specific goals, contribution, implementation platform and the proposed approach
April 14
Project status presentations (3-5 slides)
5 minute in-class presentation
Partial report that describes the current status of the project
Abstract, introduction and motivation, relevant literature review, problem definition (goals, constraints, etc.), what has been done, what is still to be done
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13. Important Dates/Milestones
May 12
Project final presentations 
Project final demonstrations
Project final reports due
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14. Optional Textbooks Basic topics Advanced topics Broad topics
The Robotics Primer, Author: Maja Mataric'
Advanced topics
Behavior-Based Robotics, 2001 Author: Ron Arkin
Available at the library
Broad topics
Springer Handbook of Robotics, 2008
Siciliano, Bruno; Khatib, Oussama, editors
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15. Where do Robots Come From?
The term robot comes from “robota” (subordinate work)
Karel Capek’s 1921 play RUR (Rossum’s Universal Robots)
Robotics grew out of the fields of control theory, cybernetics and AI
1940s: first explorations of the connection between human intelligence and machines, around the time of cybernetics
1960s: early robots are built, benefitting from two technologies: numerical control machines for precise manufacturing, and teleoperators for remote radioactive material handling
Robotics = the science and technology of robots
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16. A Brief History of Robotics
1970s: industrial robots, became essential components in the automation of flexible manufacturing systems, due to development of integrated circuits, digital computers and miniaturized components
General industry: metal products, the chemical, the electronics and the food industries
Early AI had a strong impact on how it evolved (1950s-1970s), emphasizing reasoning and abstraction, removal from direct situatedness and embodiment
1980s: robotics was defined as the science which studies the intelligent connection between perception and action
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17. A Brief History of Robotics
1990s: the need to use robots in hazardous environments (field robotics), or to enhance the human operator ability (human augmentation), or to improving the quality of life (service robotics).
2000: from industrial robotics to challenges of the human world (human-centered and life-like robotics)
Need for a higher degree of autonomy!
Wide range of applications
biomechanics, haptics, neurosciences, virtual simulation, animation, surgery, and sensor networks
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18. What is in a Robot? Sensors Effectors and actuators
Used for locomotion and manipulation
Controllers for the above systems
Coordinating information from sensors with commands for the robot’s actuators
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19. Challenges of Robot Control
Perception
Limited, noisy sensors, diversity of sensors
Actuation
Limited capabilities of robot effectors
Thinking
Time consuming, different time scales for response, real-time demands, everything happens concurrently and asynchronously
Environments
Dynamic, impose fast reaction times
Lots of architectures exists
No single architecture is best for all applications
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20. Robot Architectures
Robot control is the means by which the sensing and action of a robot are coordinated
Robot architectures
Structure: how the system is divided into subsystems and how they interact
Style: computational concepts
Common feature of architectures
Modular decomposition of systems into simpler, independent pieces  increase reliability and decrease complexity
Software tools
Help development in a particular architectural style (specialized languages, communication libraries)
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21. Spectrum of robot control
From “Behavior-Based Robotics” by R. Arkin, MIT Press, 1998
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22. Robot control approaches
Reactive Control
Don’t think, (re)act.
Deliberative (Planner-based) Control
Think hard, act later.
Hybrid Control
Think and act separately & concurrently.
Behavior-Based Control (BBC)
Think the way you act.
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23. W. Grey Walter’s Tortoise
Machina Speculatrix” (1953)
1 photocell, 1 bump sensor, 1 motor, 3 wheels, 1 battery
Behaviors:
seek light
head toward moderate light
back from bright light
turn and push
recharge battery
Uses reactive control, with behavior prioritization
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24. Shakey At Stanford Research Institute (late 1960s)
A deliberative system
Visual navigation in a very special world
STRIPS planner
Vision and contact sensors
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25. The Art of Robot Architectures
What tasks will the robot perform?
Short term, long term, user-initiated, robot initiated
What actions are necessary to perform the tasks?
Representation, coordination, speed
What data is necessary to perform the tasks?
How to get it, what sensors are needed, how to represent it, how to update it
What computational capabilities does the robot have?
What data will be used, on-board/off-board
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26. The Art of Robot Architectures
Who are the robot’s users?
How to command the robot, feedback, interaction, information exchange
How will the robot be evaluated?
Success criteria, failure modes
Will the architecture be used for more than one set of tasks?
More than one robot, more than one team of developers
Sensing and acting are the hard parts (not the planning) and take the most of the development time
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27. Sensing Force and tactile Inertial sensors, GPS, odometry
Normal pressure, skin deformation
Inertial sensors, GPS, odometry
model a robot’s motion or pose
(position and orientation) relative
to an external frame of reference
Sonar sensing
Obstacle avoidance, mapping
object recognition
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28. Sensing How to we put it all together? Range sensors 3D vision
Obtain 3D structure
for navigation
3D vision
How to we put it all together?
Usually need a fusion architecture
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29. Robot Types - Manipulators
Kinematic redundancy: more degrees of freedom than necessary to solve the task
7-DOF Mitsubishi PA10
8-DOF Scienzia Machinale
Snake design
Robotics Research Corporation
NASA dexterous manipulator
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30. Robot Types - Hands
Mechanical constraints: placement of motors and sensors
Utah/MIT robot hand
Stanford/JPL hand
UB hand 3
NASA robonaut
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31. Robot Types – Legged Robots
Inspired from biological systems: insects, mammals
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32. Robot Types - Wheeled
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33. Robot Types - Hybrid Leg – wheel Leg – arm Wall-climbing
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34. Robot Types – Humanoid Robots
Biped robots
Humanoid torso
Hopping robots
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35. Robots: Alternative Terms
UAV
unmanned aerial vehicle
UGV (rover)
unmanned ground vehicle
UUV
unmanned undersea vehicle
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36. Key Concepts Situatedness Embodiment
Agents are strongly affected by the environment and deal with its immediate demands (not its abstract models) directly
Embodiment
Agents have bodies, are strongly constrained by those bodies, and experience the world through those bodies, which have a dynamic with the environment
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37. Key Concepts (cont.) Situated intelligence
is an observed property, not necessarily internal to the agent or to a reasoning engine; instead it results from the dynamics of interaction of the agent and environment
and behavior are the result of many interactions within the system and w/ the environment, no central source or attribution is possible
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38. Background Readings
M. Matarić: Chapters 1, 3
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