Swarm Robotics

This week we will explore swarm robotics. Learn how smaller, less capable robots can work together in large numbers to obtain complex goals.

Mechanisms of Cooperation in Cancer Nanomedicine: Towards Systems Nanotechnology

Sabine Hauert et. al

Abstract - Nanoparticles are designed to selectively deliver therapeutics and diagnostics to tumors. Their size, shape, charge, material, coating and cargo, determine their individual functionalities. A systems approach could help predict the behavior of trillions of nanoparticles interacting in complex tumor environments. Engineering these nanosystems may lead to biomimetic strategies where interactions between nanoparticles and their environment give rise to cooperative behaviors typically seen in natural self-organized systems. Examples include nanoparticles that communicate the location of a tumor to amplify tumor homing, or self-assemble and disassemble to optimize nanoparticle transport. The challenge is to discover which nanoparticle designs lead to a desired systems behavior. To this end, novel nanomaterials, deep biological understanding, and computational tools are emerging as the next frontier.

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Programmable Self-Disassembly for Shape Formation in Large-Scale Robot Collectives

Melvin Gauci et. al

Abstract - We present a method for a large-scale robot collective to autonomously form a wide range of user-specified shapes. In contrast to most existing work, our method uses a subtractive approach rather than an additive one, and is the first such method to be demonstrated on robots that operate in continuous space. An initial dense, stationary configuration of robots distributively forms a coordinate system, and each robot decides if it is part of the desired shape. Non-shape robots then remove themselves from the configuration using a single external light source as a motion guide. The subtractive approach allows for a higher degree of motion parallelism than additive approaches; it is also tolerant of much lower-precision motion. Experiments with 725 Kilobot robots allow us to compare our method against an additive one that was previously evaluated on the same platform. The subtractive method leads to higher reliability and an order-of-magnitude improvement in shape formation speed.

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Swarm Robotics Search & Rescue: A Novel Artificial Intelligence-inspired Optimization Approach

M. Bakhshipour

Abstract - In this paper, a novel heuristic algorithm is proposed to solve continuous non-linear optimization problems. The presented algorithm is a collective global search inspired by the swarm artificial intelligent of coordinated robots. Cooperative recognition and sensing by a swarm of mobile robots have been fundamental inspirations for development of Swarm Robotics Search & Rescue (SRSR). Swarm robotics is an approach with the aim of coordinating multi-robot systems which consist of numbers of mostly uniform simple physical robots. The ultimate aim is to emerge an eligible cooperative behavior either from interactions of autonomous robots with the environment or their mutual interactions between each other. In this algorithm, robots which represent initial solutions in SRSR terminology have a sense of environment to detect victim in a search & rescue mission at a disaster site. In fact, victim’s location refers to global best solution in SRSR algorithm. The individual with the highest rank in the swarm is called master and remaining robots will play role of slaves. However, this leadership and master position can be transitioned from one robot to another one during mission. Having the supervision of master robot accompanied with abilities of slave robots for sensing the environment, this collaborative search assists the swarm to rapidly find the location of victim and subsequently a successful mission. In order to validate effectiveness and optimality of proposed algorithm, it has been applied on several standard benchmark functions and a practical electric power system problem in several real size cases. Finally, simulation results have been compared with those of some well-known algorithms. Comparison of results demonstrates superiority of presented algorithm in terms of quality solutions and convergence speed.

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Assessing the Effect of Self-Assembly Ports in Evolutionary Swarm Robotics

Kazi Shah Nawaz Ripon

Abstract - Self-assembly in swarm robotics is essential for a group of robots in achieving a common goal that is not possible to achieve by a single robot. Self-assembly also provides several advantages to swarm robotics. Some of these include versatility, scalability, re-configurability, cost-effectiveness, extended reliability, and capability for emergent phenomena. This work investigates the effect of self-assembly in evolutionary swarm robotics. Because of the lack of research literature within this paradigm, there are few comparisons of the different implementations of self-assembly mechanisms. This paper reports the influence of connection port configuration on evolutionary self-assembling swarm robots. The port configuration consists of the number and the relative positioning of the connection ports on each of the robot. Experimental results suggest that configuration of the connection ports can significantly impact the emergence of self-assembly in evolutionary swarm robotics.

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Projects to Work on

Build Your Own Swarm

Introduction

Now that you have had the opportunity to explore swarms in robotics in several different scenarios and scales, it is time for you to build your own "robot" swarm. Of course, you are not expected to build a fleet of robots due to costs, but you can get creative and build a swarm using household items as well!

What to build

The goal of this project is to build swarm-like behaviors however you like! Perhaps you are interested in building a swarm that attaches itself to a food source. Maybe you are interested in building a swarm that self-organizes into different types of formations (lines, circles, squares, etc.). The choice is up to you; so get creative.

How to build

How you choose to build your swarm is entirely up to you, but be creative.

Some ideas for building materials of physical swarms:

• If you want to make something electronic, items like Raspberry Pis, Beaglebones, and Arduinos are good starting points but may be a bit pricey. Also look for similar products that may be cheaper (i.e. derivatives of these types of products). You will likely need a method for these agents to communicate, for this, you may want to investigate wifi, bluetooth, RFID and other methods. If you need to program them, there is a language called BUZZ that may be interesting to you.
• If you want to make a swarm out of more common materials, items like beans, rice, pasta, marbles, etc. may be good choices. For the actuation, you could put them in a large box and shake or apply an external force to move them around a bit. Remember, you do not want to connect the objects directly, but rather have a "natural" assembly take place. You could also try a small amount of fluid on top of a speaker and seeing how it self organizes.

Some ideas for building simulated swarms:

If you are interested in creating computer simulations of swarms, there are a variety of simulators you can try. Below is a list of some common simulators used for modeling swarms:

• ARGOS
• Roborobo
• StarLogo and SWARM
• DDLab
• Or create your own using any programming language and/or tools you like!