Portland Area Robotics Society

Regular Meeting Minutes

Nov 4, 2006, 10:30AM



1.      Presentations:

a.       Touching Imaginary Things %G–%@ Hakan Gurocak

b.      Making sense of Sensor Data %G–%@ Peter Skeggs

2.      PDXBot Alert %G–%@ Roger Ray

3.      Table-top Line Maze challenge %G–%@ Monty Goodson

4.      News & Reports

a.       Show-and-tell






Touching Imaginary Things

1.     Hakan Gurocak

Director, School of Engineering and Computer Science, WSU, Vancouver

Robotics research:
Precision assembly and walking robotics
Human-like decision making

2.     Magnetorheological Fluid Brake for a Force Feedback Glove for Virtual Environments

Research Goal: To develop a force feedback glove that can be worn by a user interacting with a virtual environment.

The glove would constrain the users fingers from penetrating into a virtual object.

The current system incorporates virtual reality goggles, and a glove with 22 sensors.

The glove has breaks on the joints of the fingers to constrain motion. This simulates contact with objects.

Other force feedback devices:

        Cybergrasp/CyberForce by Immersion Corp.

        Rutgers Master by Rutgers University

        Phantom by SensAble Technologies.

Magnetorheological (MR) fluid is a liquid with particles suspended in it. In its normal state it has the consistency of motor oil, but in the presence of a magnetic field, it has a thicker consistency similar to peanut butter.

The MR fluid is used in the breaks on the joints of the gloves fingers. By varying the magnetic field in the breaks, the

The human hand can produce a sustainable torque of about 200N-mm at the finger tip joints, and 620N-mm at the finger root joints. The glove needs to resist about 20-30% of this force for an effective tactile response.

The brake contains concentric cylinders with MR fluid located in a small gap between. The change in shear stress of the fluid produces an output torque. An electric coil produces the magnetic field to change the MR stiffness.

To test the glove, users were asked to hold a virtual object without visual feedback. The user first performs the task with audio feedback, then with the force-feedback glove activated. The MR feedback significantly improved user performance in this task. In another experiment, users were easily able to tell the difference in stiffness with the glove.


We need volunteers and organizers to help with planning of PDXBot. We need help running events, and spcialists. Please contact Roger Ray if you have any interest in helping out.

Making sense of sensor data

1.     Pete Skeggs, Noetic, Nu-Botics

Hardware interfaces

Firmware and applications

Robot Products: WheelWatcher, WheelCommander

2.     Sensor filtering.

The art of using sensors is to filter the noise out of the data.

Often, analog filters are applied to filter out noise. This often requires an understanding of the frequency characteristics of the data and the noise. For example, if the noise has a higher frequency than the data, then a low-pass filter can help to reject the noise. A simple low-pass filter can be implemented with a resistor and a capacitor %G–%@ an RC filter.

The same kind of filter can be implemented in microcontroller software. Implementing a filter in software has the advantage of being reprogrammable.

There are two kinds of digital filters %G–%@ Finite Impulse Response (FIR) and Infinite Impulse Response (IIR). A FIR filter will reject momentary spikes of input in a short time. An IIR filter will retain some component of the spike for a long time.

A simple FIR filter is an average of the past two samples:
Cn = (Rn + Rn-1) / 2.

More elaborate FIR filters can be significantly more difficult to calculate.

An IIR filter can provide better control over the cut-off frequency. A simple single-pole IIR filter includes the current input and the previous output:
Cn = k * Rn + l * C n-1

Cn = (k*Rn + (m-k)C n-1 )/m

There are standard formulas for calculating the k and m coefficients in this equation.


There are also hardware digital filters. For example, see the Linear Technology LTC1569-7

For more information, Pete recommends the book Robot Programming by Joe Jones.


Line Maze Competition

The competition this month is design a robot to turn at the third intersection on a line-maze map. The robot should detect and ignore the first two turns on the map, and take the third one, regardless of its direction. Further details were posted to the PARTS mail list.
Next month, we will add a more complex challenge. The robot must detect the goal marker and dead-ends.


Show-and-Tell and News

For next month, Roger Ray requested all members to bring in current AND older projects for an extended show-and-tell session.


JCM InVentures is producing a new kit for a Sumo robot, the SAMrI. See www.jcminventures.com. The kit provides downloadable software and a graphical programming interface for simple customization.