Coverage Efficiency in Autonomous Robots With Emphasis on Simultaneous

Localization and Mapping

Mo Lu

Computer Systems Lab 2009-2010 Final Version

Introduction•Coverage Efficiency is a key point in programming autonomous systems•Project approaches CE using SLAM•Using SLAM, a autonomous system will be able to map and process an environment to minimize resource use in runtime

Background

• Modern commercial autonomous lawnmowers and inefficiency

• Random cuts and turns• Dummy sensing

• Problems of runtime v. coverage

SLAM Theory

• Scan for obstacles via laser scanner or similar device

• Update scans until entire map can be created, ie: all boundaries and obstacles connect

• Create obstacle and boundary map using scan outputs

• Analyze map via recursive run-through to determine most efficient path

• Run optimal path on subsequent runthroughs

Serious Business: Project Work

• Matrix-based environment simulation– Environment is pre-created, obstacles, boundaries

and size have been set• Robot keeps track of location• Pings in 180 degree field of vision• Returned data forms obstacle map• Map is cross checked with environment for accuracy• Results indicate that the scanning and mapping code

works with various obstacles

Setup

Simulation Results

Simulation Runtimes (3 Continuous Obstacles, Randomly Placed)

0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5

0

5

10

15

20

25

Runtimes Given Mapsize

6x6

Test #

Ru

ntim

e (

s)

Discussion Cont.

• Adapted parts of the simulation code for use with the laser scanner

• Specifically, that means the scanning parts of the code, since the robot is not self-propelling

yet• Manual movement of the scanner is being

used in lieu of motors• Can scan part of a constructed environment

given hand rotations

Setup

Scanner in Action

Scanner in Action

Laser Rangefinder Results

Results Cont.

Robot

Conclusions and Future Applications

• Scanning works, with a given flat elevation• Adapt simulation for terrain types (unmowable v.

mowable grounds, different elevations)• More runtime analysis

• Need to address more realistic conditions-Power sources

-Complex polygonal navigation• Integrate program with robot, so testing on

movement, mapping, and keeping coordinates can be done