EDHMoR: Evolutionary designer of heterogeneous modular robots

This paper is devoted to the problem of automatically designing feasible and manufacturable robots made up of heterogeneous modules. Specifically, the coevolution of morphology and control in robots is analyzed and a particular strategy to address this problem is contemplated. To this end, the main issues of this approach such as encoding, evaluation or transfer to reality are studied through the use of heterogeneous modular structures with distributed control. We also propose a constructive evolutionary algorithm based on tree-like representations of the morphology that can intrinsically provide for a type of generative evolutionary approach. The algorithm introduces some new elements to smooth the search space and make finding solutions much easier. The evaluation of the individuals is carried out in simulations and then transferred to real robots assembled from the modules considered. To this end, the extension of the principles proposed by classical authors in traditional evolutionary robotics to brain–body evolution regarding how simulations should be set up so that robust behaviors that can be transferred to reality are obtained is considered here. All these issues are analyzed by means of an evolutionary design system called EDHMoR (Evolutionary Designer of Heterogeneous Modular Robots) that contains all the elements involved in this process. To show practical evidences of the conclusions that have been extracted with this work, two benchmark problems in modular robotics are considered and EDHMoR is tested over them. The first one is focused on solving a linear robot motion mission and the second one on a static task of the robot that does not require displacements.     

High-level motion planning for CPG-driven modular robots

Modular robots may become candidates for search and rescue operations or even for future space missions, as they can change their structure to adapt to terrain conditions and to better fulfill a given task. A core problem in such missions is the ability to visit distant places in rough terrain. Traditionally, the motion of modular robots is modeled using locomotion generators that can provide various gaits, e.g. crawling or walking. However, pure locomotion generation cannot ensure that desired places in a complex environment with obstacles will in fact be reached. These cases require several locomotion generators providing motion primitives that are switched using a planning process that takes the obstacles into account. In this paper, we present a novel motion planning method for modular robots equipped with elementary motion primitives. The utilization of primitives significantly reduces the complexity of the motion planning which enables plans to be created for robots of arbitrary shapes. The primitives used here do not need to cope with environmental changes, which can therefore be realized using simple locomotion generators that are scalable, i.e., the primitives can provide motion for robots with many modules. As the motion primitives are realized using locomotion generators, no reconfiguration is required and the proposed approach can thus be used even for modular robots without self-reconfiguration capabilities. The performance of the proposed algorithm has been experimentally verified in various environments, in physical simulations and also in hardware experiments.     

可重构模块机器人分散容错控制

针对可重构模块机器人的执行器故障,提出一种基于自适应模糊系统的分散被动容错控制方法.该方法不需要机器人动力学模型与模块之间的信息交换,模块控制器分别采用间接和直接自适应方法设计,自适应参数的更新律基于Lyapunov稳定性理论设计,保证了系统的稳定性和H∞跟踪性能.数值仿真结果表明了所提出方法的有效性.     

能力风暴智能机器人无线通信系统的研究

提出了实现能力风暴智能机器人之间无线通信的一种方法,介绍了能力风暴智能机器人平台及无线收发模块的功能,分析了用无线收发模块实现机器人之间无线通信的原理和设计要点.该无线通信系统脱离了计算机的控制,机器人可自行收发数据,实验结果表明:在有效范围内机器人之间能进行快速有效的通信.     

Design of a miniature switchable connection system for stochastic modular robots

This paper presents the design and implementation of a MIniature SwitchAble (MISA) connection system for stochastic modular robots. The MISA connector consists of attaching, aligning, locking, detaching and holding mechanisms. The connection function can be switched on and off by controlling shape memory alloy (SMA) actuators. Furthermore, it possess functions of self-attachment and self-alignment through magnetic interaction under random collision condition. The design details and prototype construction are presented. The preliminary experiments and results demonstrate feasibility and performance of this miniature connector. The potential application is to integrate it into modular microrobots.     

The design of a representation and analysis method for modular self-reconfigurable robots

For Modular Self-Reconfigurable (MSR) robots to successfully reconfigure themselves, the control system must have the robot's topological structure before, during and after the reconfiguration process. Therefore, the module's docking status such as the docking orientation and the availability of docking ports must be ascertained before self-configuration takes place. This paper presents a representation method, based on labelled planar graphs and incidence matrices to represent the topologic structure of a group of connected modules. Essential information such as the orientations of the docked joints and docking ports are obtained from the labelled graph for reconfiguration. An innovative Hardware Orientation Detecting System (HODS) is proposed for detecting the orientation between two docking ports, which can be applied to all multi-orientation docking systems. An analytical method is also presented to determine whether a structure has enough degrees-of-freedom to perform self-reconfiguration.     

Design of a modular assembly of four-footed robots with multiple functions

Modern industries use many types of robots. In addition to general robotic arms, bipedal, tripedal, and quadrupedal robots, which were originally developed as toys, are gradually being used for multiple applications in manufacturing processes. This research begins with establishing the platform for four-footed robots with multiple functions, high sensitivity, and modular assembly and this is how a fundamental model of the industrial robots is constructed. Under additional loads, the four feet of the quadrupedal robot reinforce its carrying ability and reliability compared to bipedal or tripedal robots, which helps it to carry more objects and enhances functionality. Based on different requirements and demands from the manufacturing processes, the highly sensitive four-footed robot provides an expandable interface to add different sensing components. In addition, when combined with a wireless communication module or independent 1.2 GHz radio frequency CCD wireless image transmission system, the user can control the robot remotely and instantly. The design helps the four-footed robot to expand its applications. By assembling and disassembling modules and changing the sensing components, the highly sensitive four-footed robot can be used for different tasks. Moreover, the remote control function of the robot will increase interaction with human beings, so it can become highly become involved in people's lives. The platform of the four-footed robot will become a design reference for the commercialization of different industrial robots, and it will provide the design of industrial robots with more options and useful applications.     

Roombots: A hardware perspective on 3D self-reconfiguration and locomotion with a homogeneous modular robot

In this work we provide hands-on experience on designing and testing a self-reconfiguring modular robotic system, Roombots (RB), to be used among others for adaptive furniture. In the long term, we envision that RB can be used to create sets of furniture, such as stools, chairs and tables that can move in their environment and that change shape and functionality during the day. In this article, we present the first, incremental results towards that long term vision. We demonstrate locomotion and reconfiguration of single and metamodule RB over 3D surfaces, in a structured environment equipped with embedded connection ports. RB assemblies can move around in non-structured environments, by using rotational or wheel-like locomotion. We show a proof of concept for transferring a Roombots metamodule (two in-series coupled RB modules) from the non-structured environment back into the structured grid, by aligning the RB metamodule in an entrapment mechanism. Finally, we analyze the remaining challenges to master the full Roombots scenario, and discuss the impact on future Roombots hardware.     

Multiagent control of self-reconfigurable robots

We demonstrate how multiagent systems provide useful control techniques for modular self-reconfigurable (metamorphic) robots. Such robots consist of many modules that can move relative to each other, thereby changing the overall shape of the robot to suit different tasks. Multiagent control is particularly well-suited for tasks involving uncertain and changing environments. We illustrate this approach through simulation experiments of Proteo, a metamorphic robot system currently under development.     

Multimode locomotion via SuperBot reconfigurable robots

One of the most challenging issues for a self-sustaining robotic system is how to use its limited resources to accomplish a large variety of tasks. The scope of such tasks could include transportation, exploration, construction, inspection, maintenance,in-situ resource utilization, and support for astronauts. This paper proposes a modular and reconfigurable solution for this challenge by allowing a robot to support multiple modes of locomotion and select the appropriate mode for the task at hand. This solution relies on robots that are made of reconfigurable modules. Each locomotion mode consists of a set of characteristics for the environment type, speed, turning-ability, energy-efficiency, and recoverability from failures. This paper demonstrates a solution using the SuperBot robot that combines advantages from M-TRAN, CONRO, ATRON, and other chain-based and lattice-based robots. At the present, a single real SuperBot module can move, turn, sidewind, maneuver, and travel on batteries up to 500 m on carpet in an office environment. In physics-based simulation, SuperBot modules can perform multimodal locomotions such as snake, caterpillar, insect, spider, rolling track, H-walker, etc. It can move at speeds of up to 1.0 m/s on flat terrain using less than 6 W per module, and climb slopes of no less 40 degrees. Harris Chi Ho Chiu is a PhD Student in Computer Science at the University of Southern California and a research assistant in Polymorphic Robotics Laboratory of Information Science Institute. He received his Master in Computer Science from the University of Southern California and his Bachelor of Engineering from the University of Hong Kong. His research interests include intelligent automated systems, modular self-reconfigurable systems, artificial intelligence, and machine learning. Michael Rubenstein is currently a PhD student at the Polymorphic Robotics Laboratory, working on the CONRO and Superbot self-reconfigurable robotic systems. He has received his bachelors in Electrical Engineering from Purdue University, and his masters in Electrical Engineering from the University of Southern California, and is currently working towards his PhD in Computer Science from the University of Southern California. His interests include modular self-reconfigurable systems, autonomous robots, self-healing systems, and self-replicating systems. Jagadesh B Venkatesh is a member of the Polymorphic Robotics Laboratory at the Information Sciences Institute. He is currently a Master’s candidate in the Product Development Engineering program at the University of Southern California. He received his MS in Computer Science with specialization in Intelligent Robotics, also at the University of Southern California in 2005. His current interest is the commercialization of robotic technologies, specifically in the consumer robotics sector.     

一种引入通信的多移动机器人编队方法*

提出以视觉跟踪为基础并引入通信进行多机器人的编队控制方法,根据需要编写了一种新的通信协议,采用闭环l-Φ实现编队算法.这种多机器人编队控制避免了视觉系统的局限,能够更好地在复杂未知环境中协作完成任务,解决了编队控制的无反馈和实时性不高的问题,使得机器人能够准确迅速地进行跟踪和通信编队,一起顺利达到目标点.试验结果证明了该方法的有效性.     

Enhancing multi-hop communication over multi-radio multi-channel wireless mesh networks: A cross-layer approach

The multi-channel multi-radio technology represents a straightforward approach to expand the capacity of wireless mesh networks (WMNs) in broadband wireless access scenarios. However, the effective leveraging of this technology in WMNs requires (i) enhanced MAC protocols, to coordinate the access to multiple channels with a limited number of radio interfaces, and (ii) efficient channel allocation schemes, to mitigate the impact of co-channel interference. The design of channel assignment schemes and MAC protocols is strictly interrelated, so that joint design should be considered to optimize the mesh network performance. In this paper, a channel assignment and fast MAC architecture (CAFMA) is proposed, which exploits the benefits provided by the multi-channel multi-radio technology to (i) enhance the performance of multi-hop communications, (ii) maximize the resource utilization, and (iii) support differentiation of traffic classes with different quality of service (QoS) requirements. CAFMA is designed with a cross-layer approach and includes (1) a novel MAC scheme, which provides multi-channel coordination and fast data relaying over multi-hop topologies, and (2) a distributed channel allocation scheme, which works in cooperation with the routing protocol. Simulation results confirm the effectiveness of CAFMA when compared with other single-layer and cross-layer solutions for multi-radio multi-channel WMNs.     

Graph-based optimal reconfiguration planning for self-reconfigurable robots

The goal of optimal reconfiguration planning (ORP) is to find a shortest reconfiguration sequence to transform a modular and reconfigurable robot from an arbitrary configuration into another. This paper investigates this challenging problem for chain-type robots based on graph representations and presents a series of theoretical results: (1) a formal proof that this is an NP-complete problem, (2) a reconfiguration planning algorithm called MDCOP which generates the optimal graph-based reconfiguration plan, and (3) another algorithm called GreedyCM which can find a near-optimal solution in polynomial time. Experimental and statistical results demonstrate that the solutions found by GreedyCM are indeed near-optimal and the approach is computationally feasible for large-scale robots.     

Channel assignment in heterogeneous multi-radio multi-channel wireless networks: A game theoretic approach

Channel assignment is a challenging issue for multi-radio multi-channel wireless networks, especially in a competing environment. This paper investigates channel assignment for selfish nodes in a heterogeneous scenario, in which nodes may have different QoS requirements and thus compete for different channels with unequal bandwidth. The interaction among nodes is formulated as a non-cooperative Multi-radio Channel Assignment Game (MCAG), where Nash Equilibrium (NE) corresponds to a stable channel assignment outcome from which no individual node has the incentive to deviate. The NEs in MCAG are characterized in this paper. Since multiple NEs may exist in this game, it is natural to choose the NE that maximizes the network utility, i.e., the sum of node utilities. It is shown that the optimal NE outcome can be derived by solving an integer non-linear programming problem. Based on some observations on the radio number distribution of NE, we propose a two-stage optimization algorithm to achieve an optimal channel assignment. Finally, computer simulations validate the effectiveness of the proposed algorithm.     

ModRED: Hardware design and reconfiguration planning for a high dexterity modular self-reconfigurable robot for extra-terrestrial exploration

This paper presents a homogeneous modular robot system design based on four per-module degrees of freedom (DOF), including a prismatic DOF to increase the versatility of its reconfiguration and locomotion capabilities. The ModRED (Modular Robot for Exploration and Discovery) modules are developed with rotary-plate genderless single sided docking mechanisms (RoGenSiD) that allow chain-type configurations and lead towards hybrid-type configurations. Various locomotion gaits are simulated through the Webots robot simulator and implemented in the real ModRED system. This work also addresses the problem of dynamic reconfiguration in a modular self-reconfigurable robot (MSR). The self-reconfiguration problem is modeled as an instance of the graph-based coalition formation problem. We formulate the problem as a linear program that finds the “best” partition or coalition structure among a set of ModRED modules. The technique is verified experimentally for a variety of settings on an accurately simulated model of the ModRED robot within the Webots robot simulator. Our experimental results show that our technique can find the best partition with a reasonably low computational overhead.     

基于微粒群优化的有限通信多机器人气味寻源

考虑机器人间的通信受限约束,将机器人抽象为微粒,提出基于微粒群优化的多机器人气味寻源方法.首先,采用结合斥力函数的策略,引导机器人快速搜索烟羽;然后,基于无线信号对数距离损耗模型,估计机器人间的通讯范围,据此形成微粒群的动态拓扑结构,并确定微粒的全局极值;最后,将传感器的采样/恢复时间融入微粒更新公式,以跟踪烟羽.将所提出方法应用于3个不同场景的气味寻源,实验结果验证了该方法的有效性.     

Reconfigurable swarm robots produce self-assembling and self-repairing organisms

Reconfigurable robots are set to become a vital factor in the theoretical development and practical utilization of robotics. The core problem in this scientific area is steady information transfer between a swarm and its organisms and vice versa. To this end, we present a basic theoretical framework that stipulates the interoperation between the two modes. We evaluate our proposed framework by constructing 100 mobile microrobots of three different types that initiate the processes of self-reconfigurability and self-repair. The autonomous decision to self-aggregate to an organism mainly derives from the necessity to overcome existing obstructive environmental conditions, e.g. ramps or clefts. The methodological dichotomy that we have chosen to evaluate our concept was to pursue in parallel an approach based on embodied distributed cognition and an evolutionary path mainly based on artificial genomes and reproduction. In this paper, we evaluate these two different approaches in two distinct grand challenges and present the main results.     

A distributed and morphology-independent strategy for adaptive locomotion in self-reconfigurable modular robots

In this paper, we present a distributed reinforcement learning strategy for morphology-independent life-long gait learning for modular robots. All modules run identical controllers that locally and independently optimize their action selection based on the robot’s velocity as a global, shared reward signal. We evaluate the strategy experimentally mainly on simulated, but also on physical, modular robots. We find that the strategy: (i) for six of seven configurations (3–12 modules) converge in 96% of the trials to the best known action-based gaits within 15 min, on average, (ii) can be transferred to physical robots with a comparable performance, (iii) can be applied to learn simple gait control tables for both M-TRAN and ATRON robots, (iv) enables an 8-module robot to adapt to faults and changes in its morphology, and (v) can learn gaits for up to 60 module robots but a divergence effect becomes substantial from 20–30 modules. These experiments demonstrate the advantages of a distributed learning strategy for modular robots, such as simplicity in implementation, low resource requirements, morphology independence, reconfigurability, and fault tolerance.     

Robust formation tracking control of mobile robots via one-to-one time-varying communication

We solve the formation tracking control problem for mobile robots via linear control, under the assumption that each agent communicates only with one ‘leader’ robot and with one follower, hence forming a spanning-tree topology. We assume that the communication may be interrupted on intervals of time. As in the classical tracking control problem for non-holonomic systems, the swarm is driven by a fictitious robot which moves about freely and which is a leader to one robot only. Our control approach is decentralised and the control laws are linear with time-varying gains; in particular, this accounts for the case when position measurements may be lost over intervals of time. For both velocity-controlled and force-controlled systems, we establish uniform global exponential stability, hence consensus formation tracking, for the error system under a condition of persistency of excitation on the reference angular velocity of the virtual leader and on the control gains.