1. Algorithms for Sensor-Based Robotics: Introduction and Background
Computer Science 436/636
Greg Hager
Simon Leonard
3/16/2020
CS 436/636, G.D. Hager

2. https://cirl.lcsr.jhu.edu/sensorbasedrobotics
Admin
Instructors: Greg Hager, Simon Leonard, Chris Paxton
Tuesday/Thursday: 15h-16h15
Lecture slides are posted on the web page and will be updated after each lecture
The current online slides are from last year
Office hours
Simon: By appointment
Greg: By appointment
Chris: TBD
3/16/2020
CS 436/636, G.D. Hager

3. Admin
Newsgroup:
Blackboard
Piazza
Last year both were used interchangeably (and that’s not a good thing)
So let’s decide which one:
3/16/2020
CS 436/636, G.D. Hager

4. Robotics at JHU
One of the top 10 universities for robotics in the US 
Arguably the leader medical robotics  
Laboratory for Computational Sensing and Robotics (LCSR)
Built in 2007
Interdisciplinary: CS, ME, EE
11 research labs (medical robotics, underwater robotics, drones, space robotics,…)
3/16/2020
CS 436/636, G.D. Hager

5. Robotics at JHU Courses: Robot Systems Programming (ME 530.707)
Lots of ROS, lots of programming (Whitcomb)
Robot Devices, Kinematics, Dynamics, and Control (ME )
Lots of mathematics modeling (Cowan)
Algorithms for Sensor-Based Robotics (CS /636) (Hager, Leonard)
Algorithms: path planning, mapping, localization
Intro to Computer-Integrated Surgery (CS )
Introduction to CIS
Computer-Integrated Surgery I (CS /645) (Taylor)
Computer-Integrated Surgery II (CS /646) (Taylor)
Projects
3/16/2020
CS 436/636, G.D. Hager

6. Robotics BotJunkie WIRED Discovering for Life Boston Dynamics
Two broad categories (
Industrial Robots
Service Robots
BotJunkie
WIRED
Discovering for Life
Boston Dynamics

7. Industrial Robots
Industrial robot as defined by ISO 8373: (
“An automatically controlled, reprogrammable, multipurpose manipulator programmable in three or more axes, which may be either fixed in place or mobile for use in industrial automation applications.”
Reprogrammable: whose programmed motions or auxiliary functions may be changed without physical alterations;
Multipurpose: capable of being adapted to a different application with physical alterations;
Physical alterations: alteration of the mechanical structure or control system except for changes of programming cassettes, ROMs, etc.
3/16/2020
CS 436/636, G.D. Hager

8. Industrial Robots www.ifr.org 178,132 units sold in 2013 (www.ifr.org)
Automotive, chemical, rubber & plastics, food industries
Total worldwide operational units at the end of 2013 was in the range of 1,333,000 to 1,600,000
US$9.5 billion in sales (market value for robot systems is US$29 billion).

9. Service Robots
Pretty much everything else that is not an “industrial robot”
ISO-8373:
A robot is an actuated mechanism programmable in two or more axes with a degree of autonomy, moving within its environment, to perform intended tasks. Autonomy in this context means the ability to perform intended tasks based on current state and sensing, without human intervention.
A service robot is a robot that performs useful tasks for humans or equipment excluding industrial automation application. Note: The classification of a robot into industrial robot or service robot is done according to its intended application.
Personal service robot is a service robot used for a non-commercial task. Examples are domestic servant robot, automated wheelchair, personal mobility assist robot, and pet exercising robot.
Professional service robot is a service robot used for a commercial task. Examples are cleaning robot for public places, delivery robot in offices.

10. Service Robots
21,000 professional service robots units sold in 2013 (
US$3.57 in sales in 2013
About 63,500 units sold between 1996 and 2008, but about 100,000 units were sold since.
Military (45% of service robots), drones (12%), ground vehicles (4%)
Farming: Milking robots (24%), mobile barn cleaner (Roomba for barns) and robotic fencer (4%)
Field robots (28%): mining, underwater, forest
Medical robots (6%)
Most valuable service robots with an average price of US$1.5 million
4 million personal service robot units sold in 2013
Vacuum cleaners, lawn mowers
Assisted living (physical disabilities, elders)

11. This Course: Two Key Problems
Motion Planning: Given a mechanism, a known environment, and a known start and goal, compute a set of inputs (e.g. a joint trajectory) that moves the robot from start to goal without collision.
Localization and Mapping: Given no a priori knowledge, use information from sensing and motion to simultaneously compute a model of the environment (a map) and robot location within the environment.
WIRED
CNN

12. What is Motion Planning?
Determining where to go
...more than a search (or it is a geometric search)
3/16/2020
CS 436/636, G.D. Hager

13. Basic Path Planning Path Planner
Problem Statement: Compute a continuous sequence of collision-free robot configurations connecting the initial and goal configurations
2D EXAMPLE:
Path
Planner
Geometry of environment
Geometry and kinematics of robot
Initial and goal configurations
Collision-free
path

14. Localization and Mapping
What is the world around me (mapping/geometry)
sense from various positions
integrate measurements to produce map
assumes perfect knowledge of position
Where am I in the world
sense
relate sensor readings to a world model
compute location relative to model
assumes a perfect world model
Together, these are SLAM (Simultaneous Localization and Mapping)
Can you localize yourself without a map?
Can you create a map if you cannot localize yourself?
Can you localize yourself and create a map at the same time?

15. Can we assume? Perfect sensors? Perfect control? Perfect thinking?
What information
Uncertainty
Perfect control?
What controls?
Perfect thinking?
Knowledge of the world? Complete?
Processing the world? Everything?
3/16/2020
CS 436/636, G.D. Hager

16. Probabilistic Methods/Drug Design
Asada Nauyo
robotics.standord.edu

17. Think About Dynamics Too!
Following a path and avoiding obstacles is one thing
Given other constraints (i.e. maximum acceleration, maximum torque), is there a path that maximizes ____?
Throwing a fast ball vs
Scissors jump vs Fosbury flop

18. Think About Dynamics, Too!
Visually controlled juggling
3R manipulator
3-5 full frames / bounce
used half-frames
estimated single-frame motion
obstacle avoidance ?!
Al Rizzi, Noah Cowan, Rob Burridge, & Dan Koditschek
3/16/2020
CS 436/636, G.D. Hager

19. SLAM
Suppose you wake up in the desert and you need to find your way around --- how do you do it?
A Chicken and Egg problem?
3/16/2020
CS 436/636, G.D. Hager

20. 3/16/2020
CS 436/636, G.D. Hager

21. 3/16/2020
CS 436/636, G.D. Hager

22. 3/16/2020
CS 436/636, G.D. Hager

23. 3/16/2020
CS 436/636, G.D. Hager

24. 3/16/2020
CS 436/636, G.D. Hager

25. 3/16/2020
CS 436/636, G.D. Hager

26. This Course: We will focus on two robotics problems:
Robot Motion Planning: How do I get from A to B in an environment
Robot Localization and Mapping: What is the structure of space, and where am I in it.
We will primarily focus on algorithms, their analysis, and their implementation (when possible) from real sensor data
We will focus on the *static* planning problem
the world does not change
our own momentum does not matter
Most of our work will be in simulation although some of you will be able to apply it to real robots
3/16/2020
CS 436/636, G.D. Hager

27. Book http://motionplanning.com
Principles of Robot Motion: Theory, Algorithms, and Implementations
H. Choset, K. M. Lynch, S. Hutchinson, G. Kantor, W. Burgard, L. E. Kavraki and S. Thrun,
MIT Press, Boston, 2005.
3/16/2020
CS 436/636, G.D. Hager

28. Other Books
Planning Algorithms Steven Lavalle, Cambridge University Prress, 2006
Free download:       
Robot Motion Planning,
Jean-Claude Latombe, Kluwer, 1991.
An Introduction to AI/Robotics
Robin Murphy
MIT Press, 2006
A Mathematical Introduction to Robotic Manipulation
Murray, Li, Sastry
Probabilistic Robotics
S. Thrun, W. Burgard, D. Fox
MIT Press, 2006
3/16/2020
CS 436/636, G.D. Hager

29. This Course:
Text: Principles of Robot Motion: Theory, Algorithms, and Implementation, Choset et. al, 2005
Chap 1: Introduction
Chap 3: Kinematics and Configuration Space
Chap 4: Potential Field Methods
Collision Detection
Chap 5: Roadmaps
Chap 6: Cell decompositions
EXAM
Chap 7: Sampling-Based Motion Planning
Chap 8: Kalman-Filter based Localization
Chap 9: Bayesian Methods for Localization
3/16/2020
CS 436/636, G.D. Hager

30. Assignments First assignment is paper/pencil Others are coding
Using Robot Operating System (ROS)
You will need access to a Linux computer with Ubuntu (dual boot, virtual machine, etc.)
Some dual boot computers are available in Wyman 157
Working remotely will not work well given that the assignments require graphical software
If you have a laptop/desktop I highly recommend installing Linux on it
We will host a session on how to do this if you need help
We will do the best support we can but if it doesn’t work you will need to use the computers in 157
ROS packages will be provided and you will edit lines of code and fill in placeholders (methods, functions, etc.)
3/16/2020
CS 436/636, G.D. Hager

31. MoveIt!
MoveIt! is a software for mobile manipulation, incorporating the latest advances in motion planning, manipulation, 3D perception, kinematics, control and navigation.
3/16/2020
CS 436/636, G.D. Hager