Bio-inspired automation technology – limitless possibilities

Bio-inspired automation technology – limitless possibilities

The ingenuity of Nature has always intrigued scientists and has inspired generations of inventors to understand how natural processes work and to apply that learning to come up with innovative bio-inspired solutions.  We thought we would, in this blog, talk about some of the work that has been going on and the “bio” inspiration driving that research.

THE ANTS

A project developed at the MIT Artificial Intelligence Laboratory, the aim is to develop a community of cubic-inch micro-robots, which should form a structured robotic community and incorporate social behaivor in this community.  The robot is equipped with 5 different sensors including IR, food, tilt, bump and light.  The inspiration came from the natural Ant colonies.  From a technical perspective, it was developed to accommodate ‘n’ number of hardware in such a small volume (1 cu.in.).  The microprocessor was just 8-bit running at 2MHz with EEPROM, equivalent to the first IBM PC.  The important point to consider is that, it not only runs its own code, but in parallel is communicating with its environment and other robots as well, which creates complications.

SWARMs

The main goal of the project is to develop a framework and methodology for the analysis of swarming behavior from biology and the synthesis of bio-inspired swarming behavior for engineered systems.  The idea was developed by Prof. Vijay Kumar from the University of Pennsylvania, to answer some of the questions related to bio-inspired swarms: Can large numbers of autonomous vehicles, work in a group to carry out a prescribed mission with or without a leader? Can they change their roles working in some hostile environment?

The inspiration for idea was to develop the high end algorithms, control laws and hardware to perform specified tasks as well as switching decisions by communicating with other group members. For example, Control was developed based on Hydrodynamics models (where swarm is assumed as an incompressible fluid, which is again interdisciplinary), and algorithm for task allocation without communication..

DIVISION OF LABOR

Another similar project is underway at the Laboratory of Intelligent systems at EPFL, Switzerland.  The project focuses on the evolutionary dynamics of fixed and adaptive mechanisms from both an engineering and a biological perspective.  The aim is to reveal the complexities arising from multiple agent interactions, development of distributed control algorithms and comparing with the engineering explainations for the colonial traits observed in ants, bees etc.

Amid research, they developed a framework based on artificial neural networks for modeling task allocation which includes workers’ behavioral flexibility to stimulus and colony response to varying stimuli. The bio-inspired models create a new perspective to the task completion in teams by agent swapping.  Similarly, in other domains of team work, bio-inspired theories help in the invention of new models.

The above examples are presented to emphasize the fact that there are lots of theories still untouched in nature which can be applied to any domain.

There are numerous examples in nature where things have structural flexibility like leaves, skin etc. Along similar lines, researchers have developed soft actuators/sensors which are fabricated on a flexible sheet at the Wyss Laboratory in Harvard.  One of the uses of actuator/sensor is to calculate the stretching of material on which it is mounted.  Another example is in the improvement in communication protocols for communication between machines working collectively.  New mathematical models are developed for spatial relationship to indentify the relative position in the dynamic systems. Similarly, a new class of algorithms, inspired by swarm intelligence, is currently being developed that can potentially solve numerous problems in communication networks like increasing network size, rapidly changing topology, and complexity.

As mentioned earlier, there is no end to learning from nature … and the quest will go on.

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