A Prehensile Tail?!
(Telluride Neuromorphic Workshop, July 2004)
Ever thought that a prehensile tail would be useful? The potential applications span from enhanced physical agility to social expression to a simple “helping hand”. A longtime dream of mine has been to construct a robotic tail controlled by signals from electromyography (EMG) using skin-surface electrodes. EMG-based control of prosthetic limbs has a long history and is being developed for future teleoperated robotic actuators for use in space and other hazardous environments. Because EMG measures muscle activation, the signal represents the force that the muscle is exerting on the body and the environment.
At this summer’s Telluride Neuromorphic
Engineering Workshop, a team of enthusiastic participants decided to attempt a
proof-of-concept project, demonstrating a simple two-channel (four-state) tail
control. Our project consisted of three
components: EMG signal detection, signal
processing/command recognition, and the motorized tail. Our team consisted of: Pamela Abshire (Univ.
EMG signals measured on the skin surface
over an active muscle can be as large as a few millivolts in amplitude, with
frequencies mainly between 20-400 Hz. They are typically measured with two skin
electrodes placed along the length of the muscle and a high input-impedance differential
amplifier. A low-impedance ground
electrode is placed on the body surface away from the muscle to control the
common-mode voltage for the amplifier. Most
clinical (commercial) systems use standardized wet electrodes (Ag/AgCl), each
with an adhesive patch to hold the electrode and conductive gel securely
against the skin surface. While we
successfully designed and tested our own amplifiers, we ultimately used two
commercial amplifiers that had better noise characteristics and could be connected
directly onto the electrode patches.
Figure 1 shows example signal data from a forearm muscle being rapidly
twitched. A gain of about 1000 was used
here. In our final version, two sets of
electrodes were placed vertically over the lower back muscles (Erector spinae
muscle group) about 1.5 inches from the spine.
Following analog amplification, we
sampled the waveform using a multi-channel Measurement Computing™ Universal
Serial Bus (USB) Analog to Digital converter (ADC) at 500 samples/sec in 100ms
blocks. This USB device included digital
outputs as well. A laptop computer
running MATLAB was used to control data acquisition and provide software
control. The waveforms were subsequently
rectified and lowpass filtered and compared against a level threshold. We now had two digital channels that
indicated when the left, right, or both back muscles were contracting.
To test
the feasibility of controlling a robotic device using the EMG signals, we built
a prototype robotic tail. The core of the tail consisted of a light flexible
steel cable that was easily bent yet resisted compression. The steel cable was
fitted with eight circular flanges through which three parallel strings
(Spectra Cable 0.030in) were threaded through holes on the edges. Applying tension to one string effectively
bends the assembly as the effective length of this string reduces while the
length of the steel cable remains constant forming an arc. The three tensional strings were separated by
120 degrees along the circumference of the guide to control the two degrees of
freedom on the tail. Tension was applied
to each string using the shaft of a Solarbotics™ motor as a winch mechanism.
The motors and the steel cable are both mounted to a base plate which serves as
the base of the tail. The default gear ratio was reduced by removing a
gear-stage to facilitate passive back-driving of the motor.
The three motors were driven by one of three possible EMG commands: a left muscle contraction drove the left motor to pull, a right muscle contraction drove the right motor to pull, and co-contraction of the back muscles drove the third (downward) motor to pull. The three motors are connected in a “star” configuration with a common node in the center. When one motor is driven in the pulling direction, the current flows through the motor towards the center of the star and flows outward through the two other motors in the releasing direction. The pulling motor bends the tail and the other motors weakly release their strings. This system, while clever, suffered from both weak motor strength and frictional imbalances producing either too much tension or looseness.
The final system (see Figure 3) was
“portable”, consisting of a laptop, USB-based ADC, batteries, and a tangle of
wires. The tail mechanism was mounted on
a commercial lower-back support product.
The tail would wag naturally while walking, due to the alternating
muscle activations with each step.
Leaning forward or deliberate stomach-muscle contractions produced back
muscle co-contractions that pulled the tail straight down.
The lack of proprioceptive or visual feedback made tail control somewhat
confusing.
This project initiated many new ideas
about the use of many more electrodes and utilizing signal separation
techniques to resolve the signals of muscle subsets that are currently blurred
together on a single set of electrodes.
The signal-to-noise ratio of the back muscle measurements were quite
high which allowed a close look at the complex muscle activations that underlie
balance and posture in humans.
Movie: Testing the tail with Masi's arm (5.0 MB AVI file)
Movie: Testing on the bench (2.6MB AVI file)
Movie: Testing on Timmer's back (3.6 MB AVI file)
Movie: Going for a walk in the Workshop lab (8.9 MB AVI file)
Another interesting EMG-driven tail
project can be found at: http://www.wolftronix.com/biotail/biotail.html