ROBOT LOCALISATION & MAPPING: NAVIGATION Ken Birbeck
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
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.
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
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.
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
Background My background – worked on the lynx robot as part of robotic systems last year Developed simple navigation programs: Wall follower program Imprinting program
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
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.
Questions? Thank you for your time. Any questions?