Modular robot system architecture

In this thesis we present the design and implementation of a novel self-reconfiguring modular (SR-MR) robotic system: Roombots. We are aiming at three main applications with Roombots; locomotion through self-reconfiguration in the regular cubic 3D-lattice on structured surfaces, locomotion in non-structured environments applying central pattern generators (CPG) as the locomotion controller, and self-assembly and reconfiguration of static objects of the day-to-day environment, such as furniture. Robot assemblies from self-reconfigurable modular robots have the ability to adapt to a given task and working environment by altering their shape through a series of reconfiguration moves, and attachments and detachments between the modules. We are interested in self-reconfiguring modular robots for their shape-changing capabilities, and their distributed characteristics. We envision the following applications for Roombots: First, self-reconfiguration in a structured 3D lattice, i.e. a floor and walls equipped with connectors. Embedded connectors can provide pivot points for locomotion of SR-MR assemblies, and docking and recharging places for our adaptive furniture pieces. Second, our proposed concept for locomotion control of modular robots on non-structured ground are central pattern generators. Third, we would like to build adaptive and versatile furniture from modular robots and light-weight elements. In the following we are able to count more than 60 modular robotic systems, developed over the last two decades. However we were unable to identify an existing system which could provide us with all desired kinematic and geometric capabilities. This led us to design and implement a novel self-reconfiguring modular robotic system: Roombots. To tackle the module design we attempt to identify both meaningful design parameters from existing modular robots, and essential features for our applications. The combination of both leads to the kinematic and geometric description of the Roombots modules, and eventually to its implementation. In order to be able to assemble furniture from our Roombots units in the future, we need a reconfiguration framework which supports the specific requirements of Roombots. Metamodules made of two units attached in-series are attracted and guided by a virtual force-field, they use broadcast signals, look-up tables of collision clouds and simple assumptions about their near environment to reach their seeding positions, which are currently hand coded. For the task of locomotion in non-structured environments we propose a framework for learning to move with modular robots using central pattern generators and online optimization. The distributed implementation of CPGs offers an ideal substrate for producing locomotion patterns and for online learning, and an optimization framework for fast learning.

Modular robot systems towards the execution of cooperative tasks in large facilities

This article discusses the advantages of a modular robot that can reassemble itself for different tasks. Modular robots are composed of multiple, linked modules. Although individual modules can move on their own, the greatest advantage of modular systems is their structural reconfigurability. Modules can be combined and assembled to form configurations for specific tasks and then reassembled to suit other tasks. Modular robotic systems are also very well suited for dynamic and unpredictable application areas such as search and rescue operations. Modular robots can be reconfigured to suit various situations. Quite a number of modular robotic system prototypes have been developed and studied in the past, each containing unique geometries and capabilities. In some systems, a module only has one degree of freedom. In order to exhibit practical functionality, multiple interconnected modules are required. Other modular robotic systems use more complicated modules with two or three degrees of freedom. However, in most of these systems, a single module is incapable of certain fundamental locomotive behaviors, such as turning.

This paper presents a design method and experiments for whole-body locomotion by a modular robot. There are two types of locomotion for modular robots: a repeating self-reconfiguration and whole-body motion such as walking or crawling. For whole-body locomotion, designing a control method is more difficult than for ordinary robots because a modular robotic system can form various configurations, each of which has many degrees of freedom. This study proposes a unified framework for automatically designing an efficient locomotion controller suitable for any module configuration. The method utilizes neural oscillators (central pattern generators, CPGs), each of which works as a distributed joint controller of each module, and a genetic algorithm to optimize the CPG network. We verified the method by software simulations and hardware experiments, in which our modular robotic system, named M-TRAN II, performed stable and effective locomotion in various configurations.

A self-repairing approach for the M-Lattice modular robotic system using digital hormone model

A system has been developed to interactively assemble modular and reconfigurable robotic systems in a computer animation environment. The modular robot is based on a set of one, two and three degree of freedom joint modules and generic links. These modules may be assembled into a large class of robotic systems that include serial, parallel, mobile and hybrid configurations. A model of the configured robotic system is immediately available for use in a wide variety of robotics research areas, including: obstacle avoidance, redundant inverse kinematics, dynamic simulations, mobile platforms and world model databases.

Modular robotic systems have been investigated to change the appearance and functions by controlling robotic modules. These reconfigurable modular systems are developed for the interactions between the external environment including humans. Capabilities of compliant interactions are as helpful as those of self-reconfiguration for the modular systems in adapting to the environments. This paper presents a novel concept of a modular robot that has the abilities of compliant actuation and self-reconfiguration to form compliant structures. The authors develop the initial prototype of the modular robots, named Module-W (M-W). Empirical results with the prototype suggest that M-W has the potential to form compliant structures.

Block Type Modular Robot: Mom's Friend

This paper presents an automatic coupling mechanism with mechanical overload protection for use in modular robotic systems. The genderless coupling incorporates a novel safety mechanism that disengages two modules at a predefined torque threshold. Several key design aspects allow the minimalist coupling to contain all functionalities within a compact cylindrical space. A detailed analytical model of the overload protection mechanism is validated by testing two materials and fabrication methods. We further present a functional prototype of the coupling with a demonstration of two modular robots driving toward one another, automatically connecting and disconnecting, detecting the connection, communicating in the process, and sensing the angle between them. The coupling as well as the embedded technologies and mechanisms present essential steps toward enabling fully self-reconfigurable robots combining modular and origami features, while advancing the process of introducing modularity into a wide range of robotic systems.

Operations in extreme and hostile environments, such as offshore oil and gas production, nuclear decommissioning, nuclear facility maintenance, deep mining, space exploration, and subsea applications, require the execution of sophisticated tasks. In nuclear environments, robotic systems have advanced significantly over the past years but still suffer from task failures caused by informational and physical uncertainty of the highly unstructured nature of the environment and exasperated by the time constraints imposed by high radiation levels. Herein, a survey is presented of current robotic systems that can operate in such extreme environments and offer a novel approach to solving the challenges they impose, encapsulated by the mission statement of providing structure in unstructured environments and exemplified by a new self‐assembling modular robotic system, the Connect‐R.

A modular robot has a distributed mechanical composition which can make various configurations and also make locomotion in a wide variety of configurations. Modular robots are thought to be useful in extreme or unknown environments by adaptively changing their shape and locomotion patterns. As for locomotion, two types can be used; one is whole-body fixed-configuration locomotion and the other is locomotion by self-reconfiguration. In this paper we deal with the former type of locomotion which is realized by coordinated joint actuation. So far, proposed control methods for whole-body locomotion by modular robots have been based on predefined locomotion sequences. However, locomotion based on predefined sequences cannot adapt to changing terrain conditions such as uphill, downhill, slippery and sticky grounds. To solve such problems, we propose a distributed control mechanism using a CPG controller which enables adaptive locomotion by modular robots. Besides the real-time CPG control we introduce a decentralized control mechanism for detecting the situation that the robot is stuck and initiating transformation to another shape for recovering the situation. The results of various hardware experiments by 4-legged structure prove the feasibility of the method for adaptive locomotion and transformation by our M-TRAN II modules.

Requirements necessary to integrate intelligent computer aided design systems in future KAE/CAM systems aimed at supporting concurrent engineering and the handling of product data, propounding extensions and new developments of system architecture, data structures and functionality. Indispensable among these are an integrated and flexible formalization of the knowledge base and a modular system architecture which can be easily modified to suit current demands. Within our developed framework we propose a homogeneous representation of declarative, procedural, and control knowledge based on a conditional attributed rewriting system (CARW). Design, reasoning and computation are carried out in domains of typed attributed entities, which are replenished with reflective capabilities. Due to the rule-based approach, a high degree of flexibility and modularity can be achieved, while perpetuating the system’s overall control in the form of a CARW manager. The objective of this study is to investigate how far our approach satisfies the requirements under consideration. Of major interest are — within the given scope — consistency aspects among attributed entities of different domains and the use of reflective techniques to support status evaluation of design features, their operators as well as design strategies.

The automated documentation of work steps is a requirement of many modern manufacturing processes. Especially when it comes to important procedures such as safety critical screw connections or weld seams, the correct and complete execution of certain manufacturing steps needs to be properly supervised, e.g., by capturing video snippets of the worker to be checked in hindsight. Without proper technical and organizational safeguards, such documentation data carries the potential for covert performance monitoring to the disadvantage of employees. Naïve documentation architectures interfere with data protection requirements, and thus cannot expect acceptance of employees. In this paper we outline use cases for automated documentation and describe an exemplary system architecture of a workflow recognition and documentation system. We derive privacy protection goals that we address with a suitable security architecture based on hybrid encryption, secret-sharing among multiple parties and remote attestation of the system to prevent manipulation. We finally contribute an outlook towards problems and possible solutions with regards to information that can leak through accessible metadata and with regard to more modular system architectures, where more sophisticated remote attestation approaches are needed to ensure the integrity of distributed components.

This paper presents an industry-unique approach and improved model-based engineering practices for software reliant aircraft systems aligned with the Future Airborne Capability Environment (FACE™) open system technical reference architecture. A lifecycle toolset is described which fuses systems and software modeling and simulation (M&S) capabilities, modular open system architectures (MOSA), and device and sensor integration techniques into a single package to enable rapid design, development, verification, certification, and deployment of interoperable, platform portable, embedded mission-critical safety-critical avionic systems. TES' MBSE lifecycle toolset, AWESUM™, supports system architecture and virtual integration (SAVI) of cyber-physical system (CPS) assets, and evaluation of these platform assets through simulated mission rehearsals in a network-centric collaborative virtual environment. The result is improved systems product. The toolset has been demonstrated to several aviation-focused communities including the American Helicopter Society International (AHS), the Association of Old Crows (AOC), the FACE Consortium, and the US Army's Aviation and Missile Research Development and Engineering Center (AMRDEC), with favorable response. TES demonstrated a virtual simulation of realistically modeled and simulated multiple dissimilar aircraft platform systems conducting network centric operations (NCO). With the goal of improving flight-safety and enhancing the situational awareness (SA) of the battle-space, virtual missions were executed showing the inter-operations of cyber-physical system (CPS) assets and capabilities from reusable FACE-aligned applications. The simulated battle-space was composed of device-configured simulated flight models of both manned and unmanned rotorcraft platforms operating within a virtual environment of real-world terrain data. The environment included simulated threats and obstacles used to stimulate platform devices that report detections and produce alerts for own-ship flight mishap avoidance. These detections were then packaged into communications messages (VMF) and shared off-platform via NCO to the common operating picture (COP) to enhance the SA operations of the battle space flight group. After a decade of development and use supporting US Army military common software programs for the PM-AME and AMRDEC, TES is now making its industry-unique approach and model-based airworthy systems/software lifecycle product line available to industry. The MBSE lifecycle toolset product suite, referred to as AWESUM™ for AirWorthy Engineering Systems Unified Modeling, is a comprehensive model-based environment aligned to DO-178C, DO-331, AC 20-148, AR 7062, and FACE™. The AWESUM™ tool suite is currently supporting the US Army's Joint Common Architecture project, a model-based avionics architecture for the Joint Multi-Role family of future vertical lift platforms, and two other FACE-aligned US Army Aviation programs within the military communications and aircraft survivability domains. This is TES-SAVi's first publication and presentation to the IEEE. While we have applied our capabilities to the Military Aviation domain, these capabilities can be effectively applied to Aerospace and other domains.

There is a high demand for system reliability in the field of avionics. With the increase in system complexity, it is becoming increasingly difficult to analyze the reliability of integrated avionics systems. This paper summarizes the commonly used reliability analysis methods of avionics systems. Specifically, the dynamic Bayesian network method is used to conduct the reliability analysis of the general integrated modular avionics system architecture. According to the results of reliability and inference analysis, the system architecture design is improved to enhance reliability and reduce system cost. The results indicate that dynamic Bayesian networks can evaluate the reliability of complex avionics systems over time and guide the optimal design of the system.