1. Mobile Robotics

3. Fundamental Idea: Robot Pose 2D world (floor plan) 3 DOF Very simple model—the difficulty is in autonomy

4. Major Issues with Autonomy Movement Inaccuracy Sensor Inaccuracy Environmental Uncertainty

5. Problem One: Localization Given: World map Robot’s initial pose Sensor updates Find: Robot’s pose as it moves

6. How do we Solve Localization? Represent beliefs as a probability density Markov assumption Pose distribution at time t conditioned on: pose dist. at time t-1 movement at time t-1 sensor readings at time t Discretize the density by sampling

7. Localization Foundation At every time step t: UPDATE each sample’s new location based on movement RESAMPLE the pose distribution based on sensor readings

8. Algorithms Markov localization (simplest) Kalman filters (historically most popular) Monte Carlo localization / particle filters Same: Sampled probability distribution Basic update-resample loop Different: Sampling techniques Movement assumptions

9. Localization’s Sidekick: Globalization Credit to Dieter Fox for this demo One step further: “kidnapped robot problem” Localization without knowledge of start location

10. Problem Two: Mapping Given: Robot Sensors Find: Map of the environment (and implicitly, the robot’s location as it moves)

11. Simultaneous Localization And Mapping (SLAM) If we have a map: We can localize! If we can localize: We can make a map!

12. Circular Error Problem If we have a map: We can localize! If we can localize: We can make a map! NOT THAT SIMPLE!

13. How do we Solve SLAM? Incorporate location/map uncertainties into a single model Optimize robot’s exploratory path Use geometry (especially indoors) Major hurdle: correlation problem Credit to Sebastian Thrun for this demo

14. For the Interested Good overview papers by Sebastian Thrun: “Probabilistic Algorithms in Robotics”, 2000 “Robotic Mapping: A Survey”, 2002 Stanford course: cs225B Build a Markov Localization engine Run it on Amigobots to play soccer

15. Up Next… Mobile robot example: Underwater robots Localization is only useful if we’re mobile… …so how do these robots move? Emergent Behaviors Mobile robots more powerful in groups… …but localization is expensive… …so what can we do without localization?