1. ROBOT LOCALISATION & MAPPING: NAVIGATION Ken Birbeck

2. Introduction  Talk about  Navigation  Path finding What is path finding How robots are able to find a path  My background  Initial to do list  Final deliverable

3. Navigation  Navigation is the process in which the robot looks at data about its surroundings, determines where the desired targets are located and then using this data, determines a safe path to a target from its current location.  Thus navigation has 2 main phases  Planning  Motion.

4. Planning the path to follow  Path finding  The process through which a path to travel is determined  Relatively easy for humans but not so easy for robots  Examples of path finding algorithms  A-star  D-star

5. A-star path finding  Divides a map into sections/nodes  Plans a least-cost path based on a distance plus cost heuristic function.  Sum of 2 functions Path cost function Admissible heuristic estimate of the distance to the desired location.

6. D-star path finding  D-star pseudo code:  Makes assumptions about unknown parts of the environment  Finds the shortest path from the robots location to a given location based on those assumptions  Detects obstacles and updates the map  Calculates a new shortest path

7. Background  My background – worked on the lynx robot as part of robotic systems last year  Developed simple navigation programs:  Wall follower program  Imprinting program

8. Project start to do list  Adaptation of programs from last year to a proximity alert program using IR sensors  Produce a simple exploring algorithm  Produce a path finding algorithm  Determining a path to a know location of a target  Determine the location of a target and then a path to it

9. Final Deliverable  Final deliverables:  lynx robot to autonomously map and navigate an indoor area.  If time permits expanded to navigating a outside area and 3D mapping.

10. Questions?  Thank you for your time.  Any questions?