Abstract—This paper presents a biologically inspired approach to two basic problems in modular self-reconfigurable robots: adaptive communication in self-reconfigurable and dynamic networks, and 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 selfreconfiguration. 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 scaleable 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. Index Terms — Self-reconfigurable robots, self-reconfigurable systems, adaptive communication, dynamic networks, distributed

Previous work on self-reconfiguring modular robots has concentrated primarily on hardware and reconfiguration algorithms for particular systems. In this paper, we introduce a new type of generic locomotion algorithm for self-reconfigurable robots. The algorithms presented here 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 di#erent systems with correct locomotion algorithms.

The ability of self-reconfigurable robots to solve a variety of robot tasks comes in part from their use of a large number of modules. E#ective use of these systems requires parallel actuation and planning, both for e#ciency and independence from a central controller. This paper presents the PacMan algorithm, a technique for distributed actuation and planning. This algorithm was developed for systems with unit-compressible modules, such as the crystalline robot. We also describe some analytical properties of the PacMan planning and actuation, and discuss simulation and hardware experiments. 1

Abstract — Here we introduce one simulated and two physical three-dimensional stochastic modular robot systems, all capable of self-assembly and self-reconfiguration. We assume that individual units can only draw power when attached to the growing structure, and have no means of actuation. Instead they are subject to random motion induced by the surrounding medium when unattached. We present a simulation environment with a flexible scripting language that allows for parallel and serial selfassembly and self-reconfiguration processes. We explore factors that govern the rate of assembly and reconfiguration, and show that self-reconfiguration can be exploited to accelerate the assembly of a particular shape, as compared with static self-assembly. We then demonstrate the ability of two different physical three-dimensional stochastic modular robot systems to self-reconfigure in a fluid. The second physical implementation is only composed of technologies that could be scaled down to achieve stochastic self-assembly and self-reconfiguration at the microscale. I.

Chain modular robots form systems with many degrees of freedom which are capable of being reconfigured to form arbitrary chain-based topologies. This reconfiguration requires the detaching of modules from one point in the system and re-attaching at another. The internal errors in the system (especially with large numbers of modules) are such that accurate movement of chain ends, required for the attaching of modules, can be extremely difficult. A three phase docking process is described that utilizes both openand closed-loop techniques. This process has been shown to work with an early version. Issues raised during this testing have been addressed in a later version. Discussion of these issues, their solutions and preliminary results of the testing the latest version are given. Index Terms—PolyBot, robot, chain, reconfigurable I.

The problemwe address is the distributed reconfiguration of a planar metamorphic robotic system composed of any number of hexagonal modules. After presenting a framework for classifying motion planning algorithms for metamorphic robotic systems, we describe distributed algorithms for reconfiguring a straight chain of hexagonal modules to any intersecting straight chain configuration. We prove our algorithms are correct, and show that they are either optimal or asymptotically optimal in the number of moves and asymptotically optimal in the time required for parallel reconfiguration.

This article illustrates the methods and results of two sets of experiments in which a group of mobile robots, called s-bots, are required to physically connect to each other, that is, to self-assemble, to cope with environmental conditions that prevent them from carrying out their task individually. The first set of experiments is a pioneering study on the utility of self-assembling robots to address relatively complex scenarios, such as cooperative object transport. The results of our work suggest that the s-bots possess hardware characteristics which facilitate the design of control mechanisms for autonomous self-assembly. The control architecture we developed proved particularly successful in guiding the robots engaged in the cooperative transport task. However, the results also showed that some features of the robots ’ controllers had a disruptive effect on their performances. The second set of experiments is an attempt to enhance the adaptiveness of our multi-robot system. In particular, we aim to synthesise an integrated (i.e., not-modular) decisionmaking mechanism which allows the s-bot to autonomously decide whether or not environmental contingencies require self-assembly. The results show that it is possible to synthesize, by using evolutionary computation techniques, artificial neural networks that integrate both the mechanisms for sensory-motor coordination and for decision making required by the robots in the context of self-assembly. This work was supported by the SWARM-BOTS project, funded by the Future and Emerging Technologies

In this paper we present algorithms for planning the motion of robotic Molecules on a substrate of other Molecules. Our approach is to divide self-reconfiguration planning into three levels: trajectory planning, configuration planning, and task-level planning. This paper focuses on algorithms for trajectory planning, moving a single Molecule from a start location to a goal location, and configuration planning, moving a set of Molecules from a starting configuration to a goal configuration. We also present our scaffold planning approach in which the interior of a structure contains three-dimensional tunnels. This allows Molecules to move within a structure as well as on the surface, simplifying Molecule motion planning as well as increasing parallelism. In addition, we present a new gripper-type connection mechanism for the Molecule which does not require power to maintain connections.

Prey retrieval, also known as foraging, is a widely used test application in collective robotics. The task consists in searching for objects spread in the environment and in bringing them to a specific place called nest. Scientific issues usually concern efficient exploration, mapping, communication among agents, task coordination and allocation, and conflict resolution. In particular, interferences among robots reduce the efficiency of the group in performing the task. Several works in the literature investigate how the control system of each robot or some form of middle/long range communication can reduce the interferences. In this work, we show that a simple adaptation mechanism, inspired by ants' behaviour and based only on information locally available to each robot, is effective in increasing the group efficiency. The same adaptation mechanism is also responsible for self-organised task allocation in the group.

Abstract — In this paper, we introduce a robotic implementation of the theory of graph grammars[12], which we use to model and direct self-organization in a formal, predictable and provably-correct fashion. The robots, which we call programmable parts, float passively on an air table and bind to each other upon random collisions. Once attached, they execute local rules that determine how their internal states change and whether they should remain bound. We demonstrate through experiments how they can self-organize into a global structure by executing a common graph grammar in a completely distributed fashion. The system also presents a challenge to the grammatical method (and to distributed systems approaches in general) due to the stochastic nature of its dynamics. We conclude by discussing these challenges and our initial approach to addressing them. I.