Hi, I was thinking of posting the text bellow as a commentary on a robotics page I might add to my website. But before I do this I would like to get some feedback to make sure the content is sound. Or in other wards I want to make sure my first impressions of BEAM technology are correct despite my limited reading on the subject and having not focused my studies on electronics. I will leave out the location of the website for now because it has been years since I have done anything to it. If the post is too long feel free to just read one section and make comments with regard to that section only.
John's Robotics Page
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-------------------Who am I and Why Create a Robotics Page.-----------
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I have two undergraduate degrees. One degree is in physics and the other degree is in electrical engineering. I am currently studying my masters in control system. My thesis is about parameter estimation using a quasi linear Kalman filter. I choose physics because I wanted to understand how things work. I choose electrical engineering because I wanted a job where I could create things. I considered the electrical control aspects to be the most crucial knowledge I needed to obtain these goals. I originally thought I would go into robotics until I discovered the elegant mathematics involved in control systems and signal processing. My discovery of two fields revitalized my interest in robotics. The two fields are BEAM robotics and genetic algorithms.
My attraction to beam robotics was its simplicity. I realized that I could create a walking robot from only two motors and very few transistors. It is likely that I will be able to find all of the parts I need from old electronic junk. Genetic algorithms closely relates to my research interest in the sense that a genetic algorithm could be used as an estimation algorithm. However, a more ambitious goal of a genetic algorithm is to evolve behaviour that may be construed as intelligent.
Regardless of these claims I realize that I can easily create simple robots by following simple BEAM designs. By analyzing these designs I can get new I ideas about controls. I can review the electronics I have learned and extend my knowledge of electronics. From these fist steps I can go two roots, I can learn more about AI techniques by applying genetic algorithms and simulations to improve upon these simple designs, or I can add two the simple BEAM design higher level controls and functionality such as microprocessors that would not normally be considered BEAM technology. Regardless, I get to enhance important skills well talking a break from my main areas or research.
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----------------Demystifying BEAM technology------------------
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Some proponents of BEAM technology believe that their design approach will evolve machine behaviour that resembles lower level organisms. Although, evolution approaches could be used to evolve intelligent like behaviour it is not clear what complexity is required to achieve this behaviour. Nor is it clear that a BEAM architecture would be an intelligent architecture. This ambiguity comes from two questions: the ambiguity of what electronics are considered BEAM robotics; and the a lack of knowledge of the required architecture for artificial intelligence. Regardless, the strength of genetic algorithms is it can find solutions outside of conventional design approaches. Consequently genetic algorithms produce what may be thought of as more creative solutions to problems then people often produce.
The less we understand about how beam robotics works the easer the technology becomes to mystify. The control of a BEAM robot is accomplished by pulses that are transmitted around a ring and coupled to other rings, actuators and sensors. The pulse travels from one node to another.
In BEAM technology each node is called a nerve and the group of nerves forms what is called a nervous net. Typically the nerves are nonlinearly band pass filters. In the design used in [1] a capacitor blocks the DC current at the input, the output of the capacitor is a node of a resistor to ground and an inverter to the output. When the input changes from low to high the voltage one the other side of the capacitor goes from low to high because the voltage across the capacitor cannot change incautiously. This causes the output of the inverter to switch from high to low. The capacitor will then drain charge through the resistor until the voltage across the resistor is bellow some threshold value and then the inverter will switch from low to high.
If you connect four of these nerves in a ring then there are two possible modes. In one mode, one pulse travels around the ring and in another mode two pulses travel around the ring. In [1] this simple four nerve, nervous net is used to control a two motor walking BEAMbot.
This very simple BEAMbot moves forward by shifting its weight with the back legs, then pulling the BEAMbot forward with the front legs. Only one motor is used for the front legs and one motor is used for the back legs. The front motor is connected to nodes one and four in the ring and the back motor is connected to nodes two and three. Thus with very few motors and very few transistors a very simple walking robot was created.
Two very important observations should be made. The first is that all that was needed to provide the same level of control was an oscillator and an inverter. Thus the BEAM bias towards a ring of "nerves" was not the simplest design. Moreover, in [1] to reverse the direction of the BEAMbot required changing the initial conditions of the circuit. A simpler way to change the direction of the BEAMbot would be to switch the terminals of the rear motor.
We conclude that there is nothing special about this single ring nervous net. It is merely a two mode oscillator. This does not mean networks of nervous nets couldn't perform useful computational functions, however, it is not obvious that such an architecture would be the simplest architecture that would accomplish the same function. Higher level approaches must be developed by understanding and planning or by optimization. The first step of optimization is to weight the objective of various behaviours and applying an optimization algorithm such as genetic algorithms.
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--------------------------Implicit Control---------------------
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Another false assumption made by proponents of BEAM technology is that the control of the BEAMbot is accomplished by pulses. There are two problems with such an assumption. The first problem is that aside from the synchronization benefits of networks of nervous nets, the motor is essentially controlled in open loop.
There is nothing special about an open loop controller. In many cases an open loop controller will provide satisfactory performance. Moreover, although this design contains no position feedback to the electrical subsystem, there is mechanical feedback to help control the position of the legs.
For instance when the rear motor pushes the right back leg against the ground the rear motor does not even turn because it does not have enough torque to counter act the torque produced by the reaction the left front leg. Thus mechanical feed back is used to control the position of the back motor. Similarly the front legs cannot turn past the body, thus by mechanical (position saturation)\(collision feedback) the robots motions is constrained. It is not obvious from the design out of the range of possible forward directions if straight forward is preferred or if sometime the robot circles to the right and other times the robot circles to the left in sort of a random fashion.
Thus like any control system feedback is applied to correct error on the output. If the feedback was obtained by using a potentiometer to determine the position of the legs it is not clear if the technology would be considered BEAM technology. Moreover if the ring of nervous nets was replaced by a single oscillators and an inverter, with using position feedback to the electrical subsystem, the design may still be simpler then the BEAM design but it probably wound not be considered a beam design. This raises the question is BEAM, a technology, a philosophy or an ideology. Is there anything special or different about BEAM technology or is just a buzzword used to create interest.
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--------------------Synchronization In Nervous Nets---------------
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I have read that coupled rings of nervous nets are self-synchronizing. This raises two questions, what do we want to synchronize with this architecture and are nervous nets the best architecture to accomplish this goal. Consider the control of a mechanical spider. The spider may move forward by moving front left legs 1 and 3 backward well moving right legs 2 and 4 backwards. Again this kind of motion is just a simple periodic motion. It is not obvious that the spider couldn't be controlled by a single oscillator and inverter running the motors in open loop and using mechanical feedback to limit the range of motion. However, if it was desirable to synchronize the movement of the legs a simpler scheme may be to just use a single voltage controlled oscillator instead of a separate loop for each leg. If the leg is too far ahead the voltage applied to the VCL would be reduced if the leg is too far back the voltage is increased. Such an approach is very similar to a pahse locked loop. Moreover a phase locked loop is not considered BEAM technology.
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------------------------Alternative Ring Topologies--------------
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Even the ring topology is not a sacrosanct technology. GPS satellites used feedback between several shift registers to provide a pseudo random sequence. Thus a shift register could be used to form the ring. The shift register has the advantage that a four bit shift register has four modes of operation well the four nerve ring in [1] can only support two modes. Another advantage of a shift register is the speed at which it shifts data can easily be changed by changing the clock signal. Moreover a flop flow can be constructed from only four logic gates. And each of those logic gates has only a small number of transistors. Alternatively a flip flop could replace one of the nodes in the nervous nets to help regulate the speed and provide away to clock in a new signal to the ring nervous net. Another alternative ring topology is a transmission line. A transmission line can be simulated with inductors in series and capacitors in shunt. The advantage of a transmission line is it is completely analog and there are more possible periodic modes that could be formed around a transmission line. A flipflop could be used to close the loop around a transmission line.
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-----------------Periodic motion and Walking Control------------
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Walking is essentially a periodic motion of the mussels. BEAM technology causes periodic signals to be created by propagation around rings. It is clear that by combining periodic signals complex trajectories can be described. Essentially this is just a generalization of the Fourier series. It is also clear that rings can be combined to create signals of longer period. For instance if we multiply one point from one ring with one point from the other ring, the resulting signal has a period that is the sum of the period of each ring. Other ways of combining ring include coupling and various forms of feedback. If the connections between nerves could be dynamically controlled a large number of signals could be described with less information then might be required if the entire time sequence was stored. Thus rings of nervous nets could be use to compress complex motions.
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---------------------------Conclusion---------------------------
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BEAM technology has a number of advantageous. It is simple and it is effective. It provides a good starting point for someone wishing to create simple robots as a hobby. Because there are numerous ways to propagate a signal in a ring, it should be easy to find the necessary components from junk electronics. However, BEAM technology is not magic, it doesn't always provide the simplest solution and in clearly doesn't provide the highest performance control. Moreover, when the complexity of a robot design increase it becomes less clear if the resulting product used beam technology. Thus some points should be remembered. Complex periodic motions can be created by combining loop nervous nets or shift registers. Often open loop electrical control with mechanical feedback is a sufficient to meet the performance requirements of a multiple leg-walking robot. Three methods that can be used to provide synchronization in walking robots are; coupling between loop nervous nets, mechanical limiting and phase locked loops. There is no need to categorize these techniques with the term BEAM robotics. Finally development of higher level robots should proceed with both the use of optimization techniques such as genetic algorithms and human planning.
[1] Susanne Still, Mark W. Tilden*,Controller for a four legged walking machine ETH Zuerich, Institute of Neuroinformatics, Gloriastr.32, CH-8006 Zuerich, Switzerland Biophysics Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA