Distributed Linear Heterogeneous Reconfiguration of Cubic Modular Robots via Simultaneous Tunneling and Permutation

Mostly in natural disaster situations, for example an earthquake, we will face a situation where people get trapped and unable to be found as soon as possible due to the unpredictable terrain. Hence, robot is being seen as scouts that able to adapt and perceive, and usually snake type robot is able to move throughout rubble and small confines. Then, the idea of using modular self-reconfigurable (MSR) robots based on CEBOT in 1988 spark an interest to researchers to fit the search and rescue purpose. Besides that, the idea of controlling robots without manual control but by using “thinking” have fascinated researchers and lead to the development of interfaces between human and machines. In 1970, a Brain Computer Interface (BCI) system has been establish and the BCI system usually is based on the Electroencephalogram (EEG) which is the electrical potentials generated in which the information generated by user and independent of any muscular activities. The implementations of both technologies to each other will frontier for a new alternatives which improves self-reconfigurable modular robot in term of control strategy. As a preliminary framework, a simulation is needed to determine both systems capabilities, and it can be achieved by interfacing the robot simulator, OpenVIBE and Virtual Experimentation Platform (V-REP) with the Python programming language. This study presentation will focus on how to control the modular robot in V-REP environment by using Python language which can be used for interfacing with BCI system created in OpenVIBE software and the simulated robot configuration. Each joint handles of modular robot based on V-REP hierarchy being streamed by Python language. There are several methods for establishment of communication between OpenVIBE and other applications. The method purpose in this paper will utilizing Lab Streaming Layer (LSL) and Python script as mediator. The outcome that is expected to be obtained for this study will be the success of communication establish to control virtual modular robot based on data from OpenVIBE. The future work based on this study will involving the BCI system designed using OpenVIBE and implementation to real modular robot might be applied.

The paper presents a solution to the problem of information interaction between embedded computing devices in the implementation of distributed control in the information-measuring and control system (IMCS) of robots with modular architecture. Distributed control is realized by designing each module as a device with its own IMCS containing all the components necessary to perform its functionality, including computing devices. As a consequence of such a functional completion of the modules, the computations needed to control the robot as a single mechatronic system are parallelized. As a result, the requirements to the power of computing devices of modules’ IMCS are significantly reduced, as it is possible to use inexpensive microcontrollers and single-board computers – embedded computing devices. The network organization of the IMCS structure of the robot is proposed, which allowed the transfer of the reconfigurability property of the network to the structure of the modular robot. Analysis of various network topologies has shown that the topology of the star type has several advantages over the topology of the bus type for use in heterogeneous modular robots. It is shown that the use of the Robot Operating System (ROS) for the implementation of information interaction between embedded computing devices is either impossible or significantly hampered. A specification is proposed for the creation of appropriate programming interfaces and a language for inter-module communication, which enable the inclusion of third-party modules in the plug and play mode. The specification is based on the principles of ROS, but allows one to implement software on embedded computing devices. On the basis of Pareto's multi-criteria optimization, recommendations were obtained for selecting the appropriate hardware and software. The efficiency of the proposed solution was proved in the course of experiments on an installation whose composition is close to the working conditions of the IMCS of a heterogeneous modular robot. The experiments showed that the joint operation of the software and hardware parts meets all the specified requirements and is applicable for the transmission of messages of the executive level with a frequency of up to 100 Hz under any load on the network.

Self-reconfigurable, modular robots are distributed mechatronic devices that can change their physical shape; modules are programmed individually but must coordinate across the robot. Programming modular robots is difficult due to the complexity of programming a distributed embedded system with a dynamically evolving topology. We are currently experimenting with programming-language abstractions to help overcome these difficulties. This tutorial describes a few such experiments using Scheme to control simulated modular robots.

In this paper, a novel robotic system called modular transformer (M-TRAN) is proposed. M-TRAN is a distributed, self-reconfigurable system composed of homogeneous robotic modules. The system can change its configuration by changing each module's position and connection. Each module is equipped with an onboard microprocessor, actuators, intermodule communication/power transmission devices and intermodule connection mechanisms. The special design of M-TRAN module realizes both reliable and quick self-reconfiguration and versatile robotic motion. For instance, M-TRAN is able to metamorphose into robotic configurations such as a legged machine and hereby generate coordinated walking motion without any human intervention. An actual system with ten modules was built and basic operations of self-reconfiguration and motion generation were examined through experiments. A series of software programs has also been developed to drive M-TRAN hardware, including a simulator of M-TRAN kinematics, a user interface to design appropriate configurations and motion sequences for given tasks, and an automatic motion planner for a regular cluster of M-TRAN modules. These software programs are integrated into the M-TRAN system supervised by a host computer. Several demonstrations have proven its capability as a self-reconfigurable robot.

Distributed robotic systems can benefit from automatic controller design and online adaptation by reinforcement learning (RL), but often suffer from the limitations of partial observability. In this paper, we address the twin problems of limited local experience and locally observed but not necessarily telling reward signals encountered in such systems.We combine direct search in policy space with an agreement algorithm to efficiently exchange local rewards and experience among agents. We demonstrate improved learning ability on the locomotion problem for self-reconfiguring modular robots in simulation, and show that a fully distributed implementation can learn good policies just as fast as the centralized implementation. Our results suggest that prior work on centralized RL algorithms for modular robots may be made effective in practice through the application of agreement algorithms. This approach could be fruitful in many cooperative situations, whenever robots need to learn similar behaviors, but have access only to local information.

The ability of reconfiguration makes modular robots have the ability of adaptable, low-cost, self-healing and fault-tolerant. It can also be applied to a variety of mission situations. In this manuscript, a robot platform which relied on the module library was designed, based on the screw theory and module theory. Then, the configuration design method of the modular robot was proposed. And the different configurations of modular robot system have been built, including industrial mechanical arms, the mobile platform, six-legged robot and 3D exoskeleton manipulator. Finally, the simulation and verification of one system among them have been made, using the analyses of screw kinematics and polynomial planning. The results of experiments demonstrate the feasibility and superiority of this modular system.

This paper presents a hybrid strategy for controlling a chain type modular robot to achieve a better interaction with the environment based on the combination of Central Pattern Generators (CPG) and Hormone inspired control. Locomotion movements of robot chains are generated by the local interaction of CPG running inside each module. Hormone messages are used to propagate sensory feedback information to the CPG thus providing a way to define general motor primitives regardless of the specific role of a module and the configuration of the robotic structure. An example set of motor primitives is defined using the hybrid approach and tested in a simulated environment. Our results showed that the integration of the motor primitives using the hybrid strategy allows the robot to travel through an obstacle-filled uneven terrain.

A heterogeneous modular robotic design for fast response to a diversity of tasks

Large-scale Multi-View Clustering (LMVC) is a hot research problem in the fields of signal processing and machine learning, and many anchor-based multi-view subspace clustering algorithms are proposed in recent years. However, most existing methods usually concentrate on the issue of reducing the time cost and ignore the exploration of the complementary information during the clustering process. To this end, we propose a Fast Essential Subspace Representation Learning (FESRL) method for large-scale multi-view subspace clustering. Specifically, FESRL introduces the orthogonal transformation to investigate both the complementary and consensus information across multiple views. The essential subspace representation can be learned in a linear time cost. Experiments conducted on several benchmark datasets illustrate the competitiveness of the proposed method.

The purpose of this article is to develop a model to explain performance in decision-making groups characterized by high diversity in composition. It begins with a brief discussion on the nature and effects of diversity. Previous research on group performance is then reviewed with the general conclusion that diverse groups perform less well than homogeneous ones do. This conclusion is challenged by closely examining a small group of studies specifically researching the effects of diversity, and it is shown that diversity can enhance a group's performance if it is integrated. Communication is proposed as an integrating mechanism, and a theory of communication in terms of preconditions is described. This theory is then used to develop propositions concerning the relationships among diversity, integration, and performance in decision-making groups. Implications for research and practice are discussed.

In situ Raman and FTIR spectra complemented by in situ Raman/18O isotope labelling are exploited for deciphering the structural properties and configurations of the (ReOx)n phase dispersed on monoclinic ZrO2 at temperatures of 120-400 °C under oxidative dehydration conditions and coverages in the range of 0.71-3.7 Re nm-2. The dispersed (ReOx)n phase is heterogeneous, consisting of three distinct structural units: (a) Species-I with mono-oxo termination ORe(-O-Zr)m (ReO mode at 993-1005 cm-1); (b) Species-IIa with di-oxo termination (O)2Re(-O-Zr)m-1 (symmetric stretching mode at 987-998 cm-1); and (c) Species-IIb with di-oxo termination (O)2Re(-O-Zr)u (symmetric stretching mode at 982-991 cm-1); all terminal stretching modes undergo blue shifts with increasing coverage. With increasing temperature, a reversible temperature-dependent Species-IIa ↔ Species-I transformation is evidenced. At low coverages, below 1 Re nm-2, isolated species prevail; at 400 °C the mono-oxo ORe(-O-Zr)m Species-I is the majority species, the di-oxo Species-IIa occurs in significant proportion and di-oxo Species-IIb is in the minority. At coverage ≥1.3 Re nm-2, at 400 °C the di-oxo Species-IIa prevails clearly over mono-oxo Species-I. Below 80 °C and at a low coverage of 0.71 Re nm-2, the occurrence of a fourth structural unit, Species-III taking on a tri-oxo configuration (symmetric stretching mode at 974 cm-1) is evidenced. All temperature-dependent structural and configurational transformations are fully reversible and interpreted by mechanisms at the molecular level.

Abstract. In a sequencing problem with linear time cost, Suijs (1996) proved that it is possible to achieve first best. By first best we mean that one can find mechanisms that satisfy efficiency of decision, dominant strategy incentive compatibility and budget balancedness. In this paper we show that among a more general and natural class of sequencing problems, sequencing problems with linear cost is the only class for which first best can be achieved.

Independent exponential capture times are assumed for each of N prey. The payoff is the number of prey caught less a linear time cost. The optimal stopping time and value are obtained. When N is known an adaptive statistical procedure is proposed for which the expected payoff differs from the value by at most one-half plus a term which tends to zero (of order N –α, a < 1) as N → ∞.

Cellular automata complexity trade-offs

Many parties are involved in a construction project, so in deciding a method of implementing the box girder erection many criteria are taken into consideration. Consequently, decision making is not easy for decision makers. A simple, frequently-used, and popular method for decision making is Fuzzy-Analytical Hierarchy Process (F-AHP) which is designed to overcome the problem of multi criteria decision making (MCDM) in the subjective assessment process. This study aims to obtain the correct method of implementing the box girder erection to be used. Based on previous research, the criteria for determining box girder erection method are the criteria for job risk, work quality, implementation time, implementation process, work safety, and work costs. The alternatives compared are the tandem crane method and the launching gantry method. The data in this study were collected through questionnaires distributed to the expert parties involved in Jakarta - Cikampek II Elevated Toll Road Project. F-AHP analysis is based on the weighting of quantitative criteria as a result of normalized calculations and qualitative criteria from the results of the respondents questionnaires which were then made pairwise comparisons assisted by Microsoft Excel software. The results of the analysis show that the occupational safety criteria are the most influential criteria with a weight of 0.454, then followed by job risk criteria (0.169), implementation time (0.119), work quality (0.114), implementation process (0.084), and work costs (0.061). The most appropriate method used in the work of the box girder erection at Jakarta - Cikampek II Elevated Toll Road Project is a launching gantry method with a value of 0.597, while the tandem crane method has a value of 0.403.