Regular Meeting Minutes

April 5, 2008, 10:30AM

1. Welcome

2. Presentation

- Introduction to Bayesian Particle Filters

3. Announcements

- BotFest ‘08

4. Update on Open AHRMS

5. Show and Tell

** Introduction to Bayesian
Particle Filters – **Professor
Barton C. Massey,

Authors E-mail - bart@cs.pdx.edu

Authors Website - http://web.cecs.pdx.edu/~bart/

http://wiki.cs.pdx.edu/forge/bmpf.html

1. What's the problem?

Why do we need to know state of Robot? Platform Control, Accurate Navigation

One Solution - Bayesian Particle Filtering (BPF)

A method of Sensor Fusion – Robot State Space tracking

BPF is the HOT NEW Alternative to Kalman Filtering – Last 10-15 years

2. Approaches

a) Deal with sensor unreliability by adding redundant sensors -

b) Kalman - linear normal distribution estimation of maximum probability position

Linear algebra - lots of high level math required

Improvements - EKF, UKF

c) Bayesian Particle Filtering - Computational intensive

3. Bayesian Particle Filtering - How does it work?

__BPF Inputs__

State of vehicle - s

g: dead reckoning

h: measurement function

Need to deal with multiple probabilities from Dead Reckoning and sensor measurement. In order to find robot location you must maximize the product of all state probabilities. Sounds Simple, Right? à Space is large

Basic Process for BPF:

0) Create copies of vehicle state, Si. Set all probabilities to 1 (Wi = 1)

1) Propagate each state copy, Si, forward one time of sample.

2) Calculate the probability of each state (Si) given the sensor reading (h) and probability, Wi.

3) Pick and Si to use right now based on maximum probability product, Wi[max]

4) Resample Si. Use a weighted random selection of states to continue duplication and propagation.

5) Repeat for next time sample.

Wi' = h(Si)*Wi [normalize]

Bayesian Particle Filter is a method of simulated evolution. BPF is a useful machine learning technique.

Drawback - Computationally intensive - Floating Point can be a plus

BotFest '08 Indoor Competition – May 17^{th} at the

http://www.portlandrobotics.org/botfest08.php?link_id=26

BotFest ’08 Outdoor Competition – May 25^{th} at the

http://www.portlandrobotics.org/botfest08.php?link_id=26

http://www.portlandrobotics.org/PARTS_Outdoor_Challenge.html

New PARTS Website – New Content Management System

http://www.portlandrobotics.org

**OpenAHRMS Update**

OpenAHRMS is the Open Source project to develop an Attitude and Heading Reference and Measurement System for Personnel Robotics. Hardware layout is nearing completion. The current design will provide USB connectivity to Host controller.

http://wiki.cs.pdx.edu/openahrms/

http://svcs.cs.pdx.edu/mailman/listinfo/openahrms