PolyBot - Modular, self-reconfigurable robots
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PolyBot - Modular, self-reconfigurable robots

Modular, self-reconfigurable robots show the promise of great versatility, robustness and low cost. Polybot is a modular, self-reconfigurable system that is being used to explore the hardware reality of a robot with a large number of interchangeable modules. Three generations of Polybot have been built over the last three years which include ever increasing levels of functionality and integration. Polybot has shown versatility, by demonstrating locomotion over a variety of terrain and manipulating a variety of objects.
Polybot is the first robot to demonstrate sequentially two topologically distinct locomotion modes by self-reconfiguration. Polybot has raised issues regarding software scalability and hardware dependency and as the design evolves the issues of low cost and robustness are being addressed while exploring the potential of modular, self-reconfigurable robots
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PolyBot: A Modular Reconfigurable Robot
Modular, self-reconfigurable robots show the promise of great versatility, robustness and low

cost.This is a robot with a a large number of interchangeable modules. It can move on variety of

terrain and manipulating a variety of objects.

Modular robotic systems are those systems that are
composed of modules that can be disconnected and
reconnected in different arrangements to form a new configuration with new functionalities. Modular

self-reconfigurable robot systems can also reconfigure their own modules.

Three Promises of N-modular Systems :
- Versatility :
They can form a large variety of shapes with large
numbers of degrees of freedom (DOF).Example of additional motion capabilities include rolling type for
efficiency and speed over flat terrain, earthworm type to
slither through obstacles, and over large steps and finally a
spider form to stride over uncertain hilly terrain.

-Reliability :
The system has the ability to repair itself as they are self reconfigurable. As the number of modules

increases, the
redundancy also increases.Error correction strategies:
The first is to use the redundancy of a
system and global feedback. The second
strategy is sometimes called self-repair

- Low Cost :
The cost savings are indirect and may require
computation over the life cycle of several systems to

PolyBot :
PolyBot is a modular reconfigurable robot system
composed of two types of modules, one called a segment
and one called a node.The node module is rigid with no
internal DOF and 6 connection ports. The segment module has 1 DOF
and 2 connection ports.

For details, refer this report:
http://www2.parc.com/spl/project and implimentations/modrobots/publications/pdf/HDSISymp2001Duff.pdf
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29-08-2010, 11:09 AM


A robot designed for a single purpose can perform some specific task well but poorly on some other task especially in a different environment. One recent trend in robotic architectures has been a focus on behavior based or reactive systems. Here, robots with the ability to change their shape could be of great value. When a task or terrain varies, reconfigurable robots can change their shape to get the job done. Robots which can perform such shape shifting are known as Modular reconfigurable robots. They are built up from a number of modules since a module cannot do much by itself but when connected together they can do highly complicated tasks.

.doc   MODULAR_ROBOTICS.doc (Size: 153.5 KB / Downloads: 98)


A robot designed for a single purpose can perform some specific task well but poorly on some other task especially in a different environment. One recent trend in robotic architectures has been a focus on behavior-based or reactive systems. Here, robots with the ability to change their shape could be of great value, since they could adapt to constantly varying tasks and environments.

When a task or terrain varies, reconfigurable robots can change their shape to get the job done. Robots, which can perform such shape shifting, are known as Modular reconfigurable robots. Modular reconfigurable robots are built up from tens to hundreds, and potentially millions, of modules. The module cannot do much by itself, but when you connect many of them together you get a system that can do complicated things. The first approach to this was done at Xerox Palo Alto Research Center (PARC) in California. PolyBot developed by PARC is a chain reconfiguration robot. It has gone through many variations with three basic generations.











Robots out on the factory floor pretty much know what is coming. Constrained as they are by programming and geometry, their world is just an assembly line. But for robots operating outdoors, away from civilization, both mission and geography are unpredictable. When a task or terrain varies, reconfigurable robots can change their shape to get the job done. Here, robots with the ability to change their shape could be of great value, since they could adapt to constantly varying tasks and environments. Modular reconfigurable robots”experimental systems made by interconnecting multiple, sample, similar units”can perform such shape shifting.

Imagine a robot made up of a chain of simple hinge joints. It could shape itself into a loop and move by rolling like a self-propelled tank tread; then break open the loop to form a serpentine configuration and slither under or over obstacles; and then rearrange its modules to morph into a multilegged spider, able to stride over rocks and bumpy terrain. These systems can reconfigure themselves automatically, with on help from outside, to tackle whatever tasks and terrain they encounter.


Modular reconfigurable robots are built up from tens to hundreds, and potentially millions, of modules. Such robots are called n-modular systems (where n is the number of module types). An n-modular system holds out three promises.

Versatility (different shapes)

Its versatility stems from the many ways in which modules can be connected. For a typical system with hundreds of modules, there are usually millions of possible configurations, which can be applied to many diverse tasks.

Robustness (Self-repair and redundancy)

Robustness is born of the redundancy and small number of module types. The units diagnose themselves and each other and compensate for, replace, or reconfigure themselves around any that are malfunctioning. But the overall number of modules is a factor: the more of them there are the more likely it is that some may fail. Clearly, if just a few modules fail, others may be able to compensate for them. The main advantage of redundancy is that when one or more modules malfunction, overall function degrades gracefully, instead of failing catastrophically. Naturally, such a robotic system must have a control strategy for dealing with partial failures. Ultimately, the system should be able to repair itself by shedding crippled units.

Cost (economies of scale?)

The promise of low cost may be the most difficult to realize. Being few in type, the modules can be mass produced, and as economies of scale come into play, the cost of each one can be reduced. That may really depend on how small they can get. At their current scale of 5 cm on a side, our modules consist of many parts and fasteners that must be assembled, some by hand, but as their size diminishes; batch fabrication becomes practical, even necessary. However, even if the cost of each module is reduced to just US$1, a complete system might require one million modules. Still, even that $1 million price tag might be worth it, Especailly if one modular robot can adapt to a Variety to difficult tasks.

Modular reconfigurable robots have a number of other advantages.

1. They support multiple modalities of locomotion and manipulation.
2. These robots are more fault tolerant than their fixed structure counterparts.
3. They can be used in tasks requiring self-assembly.
4. They provide a means for physically modeling 3D-data.


A modular reconfigurable robot Ëœarchitectureâ„¢ refers to the software and hardware framework for controlling the robot


Modular reconfigurable robot systems employ physical mechanisms allowing modules to dynamically and automatically configure and reconfigure themselves into more complex forms. They are made up of sensors (cameras range finding device etc) , actuators (controllers, imaging for robotics) and wireless communication (RF modems). Designers can use neural networks and genetic algorithms to enable the robot to cope with complicated tasks.

The basic module to be as small and simple as possible in terms of physical size and numbers of components, linkages and functions, because the smaller the module, the greater the range of shapes that can be built form it. The modules should also be able to function independently of one another. Simplicity is also a key consideration in designing the inter-module connection mechanism. Because the modules make and break connections frequently, the connection should be simple and reliably independent of human intervention.

Other important design issues include communication between modules, actuator power, and the method used to supply electrical power to the system. A good connection mechanism can also be used to transmit messages between modules. In a 3D system, modules must be able to move their won weight against the force of gravity. If the modules supply their own power using batteries, their weight and size increase, thus requiring more power to move them around. One possibility is to use the connection mechanism to simultaneously transmit power to all modules.

Several research groups proposed unit-reconfigurable robot systems, which are actuated by rotating a module relative to the rest of the robot or expanding and/or contracting a module.

Mainly the work was focused on the principle of mechanical simplicity, or the simplest design with the fewest components to accomplish the job. Modular reconfigurable robots are characterized as either homogeneous (all modules are identical) or heterogeneous (modules are different).

A reconfiguring system is unit modular if it is homogeneous. Guided by these results, they develop two unit modular systems: the Molecule robot and the Crystal robot. The main goal of the former is self-reconfiguration in 3D. The molecule robot consists of multiple units called Ëœmoleculesâ„¢ each consisting of two atoms linked by a rigid connection called a bond. Each atom has five inter-molecule connection points and two degrees of freedom. One degree of freedom allows the atom to rotate 180 degrees relatives to its bond connection and the other one allows to rotate relative to the entire molecule.

The later uses a novel actuation mechanism, called scaling, that allow an individual module to double in size by expanding or halve its size by contracting, thus providing more robust motion than the previous rotation-based actuation systems. They are dynamic structures. They move using sequence of reconfigurations to implement locomotion and undergo shape metamorphosis.


The algorithmic challenges involved in achieving self reconfiguring robotic systems in a distributed fashion concern the metamorphosis of a given structure into a desired structure and how to use self-reconfiguration to implement multiple locomotion and manipulation gaits. These issues can be formulated as motion planning problems. The key observation for automated planning is that most self-reconfiguring systems consist of identical modules. Several groups proposed architecture - dependent planners. This work can be divided into two categories of approaches: centralized and decentralized. The former is easier to analyze for performance guarantees but is not scalable for large robots. The latter supports parallelism but is generally more difficult to analyze.

Distributed planning for Crystal Robots

One possible approach is an algorithm called PACMAN distributed control developed for unit compressible systems like Crystal robots. An overall desired shape is given to the robotâ„¢s modules, each of which then determines whether or not it needs to move using only local information. If motion is necessary, each module initiates a path search through its fellow modules using only local information at each step. A data structure called pellets is used to mark the path a module should follow. After a path is found it is instantiated by marking each atom through which the path travels. Because of the Crystalâ„¢s unique action principle, a single physical module does not follow the entire path. Rather, it exchanges identities with other modules along the path, so it appears to follow the entire path while actually moving only locally. The reconfiguration involves two main steps. First, a path is planned for each module in a distributed fashion. The result is a set of pellets distributed through the atoms of the robots. Once the pellets are in place, the actuation happens asynchronously, as each atom looks for pellets and eats them without adhering to a strict schedule. This strategy means that although the intermediate structure of the crystal is undetermined, the final structure is as specified. The active module exchanges identities with other modules along the path, eventually resulting in a module appearing at a location specified in the goal statement. It allows for many paths to be planned and executed simultaneously through the robot.


The robots that can change shape can be classified in terms of how they do so. They are built for chain, lattice, or mobile reconfiguration.

The chain kind make themselves over by attaching and detaching chains of modules to and from themselves, with each chain always attached to the rest of the modules at once or more points. Nothing ever moves off on its own. The chains may be used as arms for manipulating objects, legs for locomoting. Xerox Palo Alto Research Center (PARC) is focusing on this class, which it has found to be the most versatile. A chain robot has already demonstrated locomotion by rolling like a tank tread, climbing stairs, slithering like a snake, climbing like a caterpillar, and walking like a spider.

Lattice robots change shape by moving into positions on a virtual grid, or lattice. They are like a pawn moving on a chessboard, except this board has three dimensions. As with chain robots, all the modules remain attached to the robot. Planning and control issues become less complex when the modules may move only to neighboring positions within a lattice instead of to any arbitrary position. The robot need only deal with what is occupying the limited number of neighboring positions in the lattice: for example, four positions for a module that moves on a flat square grid. With its less demanding programming, this class currently has the most research groups working on it.

Mobile self-reconfiguring robots changes shape by having modules detach themselves form the main body and move independently. They then link up at new locations to form new configurations. This type of reconfiguration is less explored than the other two because the difficulty of reconfiguration tends to outweigh the gain in functionality.



It is a chain reconfiguration robot developed at Xerox PARC. PolyBot, which has been made of as many as hundred modules, has demonstrated several abilities including locomotion, climbing, manipulation and self-reconfiguration.


The precursor to PolyBot. This is developed at Stanford University for locomotion.


Each face of the cube can expand or retract and connect or disconnect from-neighboring modules.

Dissecting PolyBot [The Chain Reconfiguration Robot]

PolyBot is made up of many repeated modules. Each module is virtually a robot in and of itself having a computer, a motor, sensors and the ability to attach to other modules. In some cases, power is supplied off board and passed from module to module. These modules attach together to form chains, which can be used like an arm or a leg or a finger depending on the task at hand.


PolyBot has gone through many variations with three basic generations.

Generation I

The modules are built up form simple hobby RC servos, power and computation are supplied off-board. The modules are manually screwed together, so they do not self-reconfigure.

Generation I version 4 (glv4)

This module was made to be a testbed for adding sensors and for testing the functionality of various configurations. Although it is not self-recongurable, it is very easy to manually reconfigure with a simple push and a twist.

Generation II

This generation of PolyBot includes onboard computing (Power PC 555) as well as the ability to reconfigure automatically via shape memory alloy actuated latches. The two used most at PARC are known as G2 and Glv4.

Of which the more powerful one, G2, is made of just two types of cube-shaped modules: a segment that has a hinge-joint between two hermaphroditic connection plates, and a node, which does not move but has six connection plates. Most of the functions depend on the hinged segment, which produces the robotâ„¢s movement, whereas the nodeâ„¢s job is to provided branches to other chains of segments. In theory, with enough nodes and segments, PolyBot could approximate any shape.

Structurally, each segment is roughly the size of a cube about 5 cm on a side and has one motor that rotates the hinge. The two connection plates on either side of the hinge joint to other modules, electrically as well as physically. On every connection plate there are four electrical connectors, each with four contacts; and through the connectors electric power and communications pass from module to module. The communications network uses the CAN protocol (for controller area network), which is a popular automotive serial network standard.

For physically docking and undocking, every connection plate also houses a latch. At its heart the latch is a wire made of a shape memory alloy, a nickel-titanium combination that alternates between two shapes when alternated between two temperatures. In this case, resistive heating is used. When current is run through the wire, the latch opens and releases its hold on a neighboring module. Stopping the current allows the latch to close by a return spring.

Embedded in each PolyBot segment and node is a 32-bit Motorola Power PC 555 processor (MPC555) along with 1MB of external RAM. Granted, the MPC555 is a rather powerful processor to have on every module, and its full processing power is not get utilized. However the goal of this research is a large, multipurpose, fully autonomous robot, which may require the complete use of these processor and memory.

The G2 has two kinds of sensors: position sensors, to determine the angle between the two connection plates, and proximity sensors. The first are Hall effect sensors, which measure voltage induced by magnetic flux to determine the motorâ„¢s angle with a resolution of 0.45 degrees. These also serve for commutation and are built into the segmentâ„¢s 30-W brush less DC motors, which can generate 4.5 Newton-meters of torque. The proximity sensors are infrared detectors and emitters mounted on the connection plates. They serve primarily to aid in docking two modules. They are used to sense and indicate the presence of an object within a specified distance without any physical contact. The detailed diagram of PolyBot segment is shown.



The first prototypes of the Generation III (G3) have been constructed as of December 2001. A short run of 200 modules is in progress. The module are very similar to G2 using the same processor but has the following exception.

Approximately ½ weight and volume of G2
Lover Power than G2
More sensors than G2


Modular reconfigurable robots are being used for different applications. They are particularly useful in industries where the environment is hostile to human beings, Some major applications are
Urban search.
Rescue in buildings badly damaged by an earthquake or bomb.
Nuclear power and fuel cycle.
Waste management.
Remote manufacturing and processing.
Medical Application.


The first two generations of PolyBot have shown some of the versatility possible with these systems, most notable the use of self reconfiguration to adapt to change in the environment or the task. New versions of PolyBot and other modular robots are being constructed to explore other issues.

For example, the next PolyBot generation, G3, will grapple with robustness and self-repair as aspects of reliability, for G3 will have over 100 modules, an order of magnitude more than any other modular robot so far. G3â„¢s goal is to move autonomously, shift lightweight objects blocking its path and reshape itself while moving though a pile of rubble as part of search- and- rescue task.

To cope with some of the issue that will arise with G3 and more sophisticated robots, PARC engineers plan to look to biology to see how nature solves the same problems of complex control, self-repair, and efficiency. In future there will be possibility that ordinary objects can be morphed into another one. For example a lamppost would be able to reorganize themselves on demand into other objects, say, a bench or barricade.


Modular reconfigurable robots are able to adapt to the operating environment and required functionality by changing shapes. They consist of a set of identical robotic modules that can autonomously and dynamically change the aggregate geometric structure to suit different locomotion, manipulation and sensing tasks. However, creating robots with reconfiguration capabilities is a serious challenge on being met through new designs for reconfigurable systems and new ideas about algorithmic planning and control that confer autonomous reconfigurability.

However, developers have a way to go before they can engineer modular reconfigurable robot systems that can be embedded into the physical world and respond in real time to requests for self-assembly. Because these robots systems will constitute long-lived distributed systems, all the supporting hardware and software will have to be robust, long lasting, fault tolerant, scalable and self healing. The hardware will have to rely on simple and robust actuation. The units will have to be powered for long period of time. Adding and removing units into the systems will have to be incremental, in that these changes should affect the overall system only locally. When units brake, the system should be able to repair itself without altering overall global functionality. The units will have to be network with reliable wireless ad-hoc communication infrastructure. And control will have to be highly parallel, scalable and distributed


[1]. IEEE SPECTRUM, February 2002.
[2]. Commissions of the ACM, March 2002/vol45
[3]. http://www.spectrum.ieee.org

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Modular self-reconfiguring robotic systems or self-reconfigurable modular robots are autonomous kinematic machines with variable morphology. Beyond conventional actuation, sensing and control typically found in fixed-morphology robots, self-reconfiguring robots are also able to deliberately change their own shape by rearranging the connectivity of their parts, in order to adapt to new circumstances, perform new tasks, or recover from damage.
For example, a robot made of such components could assume a worm-like shape to move through a narrow pipe, reassemble into something with spider-like legs to cross uneven terrain, then form a third arbitrary object (like a ball or wheel that can spin itself) to move quickly over a fairly flat terrain; it can also be used for making "fixed" objects, such as walls, shelters, or buildings.
Previous work on self-reconfiguring modular robots has concentrated primarily on hardware and reconfiguration algorithms for particular systems. We introduce a type of generic locomotion algorithm for self-reconfigurable robots. The algorithms presented are inspired by cellular automata, using geometric rules to control module actions. The actuation model used is a general one, presuming that modules can generally move over the surface of a group of modules. These algorithms can then be instantiated on to a variety of particular systems. Correctness proofs of the rule sets are also given for the generic geometry, with the intent that this analysis can carry over to the instantiated algorithms to provide different systems with correct locomotion algorithms.
Modular robots are usually composed of multiple building blocks of a relatively small repertoire, with uniform docking interfaces that allow transfer of mechanical forces and moments, electrical power and communication throughout the robot.
The modular building blocks usually consist of some primary structural actuated unit, and potentially additional specialized units such as grippers, feet, wheels, cameras, payload and energy storage and generation.
Real-World Applications:

One application that highlights
the advantages of self-reconfigurable
systems is long-term space missions.
These require long-term
Self-sustaining robotic ecology
that can handle unforeseen situations and may require self repair. Self-reconfigurable systems have the ability to handle tasks that are not known a priori especially compared to fixed configuration systems. In addition, space missions are highly volume and mass constrained. Sending a robot system that can reconfigure to achieve many tasks is better than sending many robots that each can do one task.
Another example of an application has been coined “telepario” by CMU professors Todd Mowry and Seth Goldstein. What the researchers propose to make are moving, physical, three-dimensional replicas of people or objects, so lifelike that human senses would accept them as real. This would eliminate the need for cumbersome virtual reality gear and overcome the viewing angle limitations of modern 3D approaches. The replicas would mimic the shape and appearance of a person or object being imaged in real time, and as the originals moved, so would their replicas. One aspect of this application is that the main development thrust is geometric representation rather than applying forces to the environment as in a typical robotic manipulation task. This project and implimentation is widely known as claytronics or programmable matter.
Presents a biologically inspired approach to two basic problems in modular self-reconfigurable robots: adaptive communication in self-reconfigurable and dynamic networks, and distributed collaboration between the physically coupled modules to accomplish global effects such as locomotion and reconfiguration. Inspired by the biological concept of hormone, the paper develops the adaptive communication (AC) protocol that enables modules continuously to discover changes in their local topology, and the adaptive distributed control (ADC) protocol that allows modules to use hormone-like messages in collaborating their actions to accomplish locomotion and self-reconfiguration. These protocols are implemented and evaluated, and experiments in the CONRO self-reconfigurable robot and in a Newtonian simulation environment have shown that the protocols are robust and scalable when configurations change dynamically and unexpectedly, and they can support online reconfiguration, module-level behavior shifting, and locomotion. The paper also discusses the implication of the hormone-inspired approach for distributed multiple robots and self-reconfigurable systems in general.
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hey can you pls send me the report on polybots.I would like to give a seminar and presentation in my college on the topic. thank you
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to get information about the topic PolyBot full report ppt and related topic refer the link bellow



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