Self-deformable modular robot inspired by cellular structure

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.Includes bibliographical references (leaves 15-16).In this paper, we present a modular robot design inspired by the creation of complex structures and functions in biology via deformation. Our design is based on the Tensegrity model of cellular structure, where active filaments within the cell contract and expand to control individual cell shape, and sheets of such cells undergo large-scale shape change through the cooperative action of connected cells. Such deformations play a role in many processes: early embryo shape change, heart and intestine function, and in lamprey locomotion. Modular robotic systems that replicate the basic deformable multicellular structure have the potential to quickly generate large-scale shape change and create time-varying shapes to achieve different global functions. We present a design and initial hardware implementation of this model. Our design includes four different modular components: (1) actuating links, (2) passive (compressive) links, (3) elastic surface membranes, and (4) universal connecting interfaces. In both hardware implementation and simulation, we show several self-deformable structures that can be generated from these four components, including the deformable surface, expandable cube, terrain-adaptive bridge from [1] and some examples inspired by biology. We argue that self-deformation is more appropriate for dynamic and sensing-adaptive shape change in a certain class of tasks.by Kristina M. Haller.S.B

The implications of embodiment for behavior and cognition: animal and robotic case studies

In this paper, we will argue that if we want to understand the function of the brain (or the control in the case of robots), we must understand how the brain is embedded into the physical system, and how the organism interacts with the real world. While embodiment has often been used in its trivial meaning, i.e. 'intelligence requires a body', the concept has deeper and more important implications, concerned with the relation between physical and information (neural, control) processes. A number of case studies are presented to illustrate the concept. These involve animals and robots and are concentrated around locomotion, grasping, and visual perception. A theoretical scheme that can be used to embed the diverse case studies will be presented. Finally, we will establish a link between the low-level sensory-motor processes and cognition. We will present an embodied view on categorization, and propose the concepts of 'body schema' and 'forward models' as a natural extension of the embodied approach toward first representations.Comment: Book chapter in W. Tschacher & C. Bergomi, ed., 'The Implications of Embodiment: Cognition and Communication', Exeter: Imprint Academic, pp. 31-5

Constructing living buildings: a review of relevant technologies for a novel application of biohybrid robotics

Biohybrid robotics takes an engineering approach to the expansion and exploitation of biological behaviours for application to automated tasks. Here, we identify the construction of living buildings and infrastructure as a high-potential application domain for biohybrid robotics, and review technological advances relevant to its future development. Construction, civil infrastructure maintenance and building occupancy in the last decades have comprised a major portion of economic production, energy consumption and carbon emissions. Integrating biological organisms into automated construction tasks and permanent building components therefore has high potential for impact. Live materials can provide several advantages over standard synthetic construction materials, including self-repair of damage, increase rather than degradation of structural performance over time, resilience to corrosive environments, support of biodiversity, and mitigation of urban heat islands. Here, we review relevant technologies, which are currently disparate. They span robotics, self-organizing systems, artificial life, construction automation, structural engineering, architecture, bioengineering, biomaterials, and molecular and cellular biology. In these disciplines, developments relevant to biohybrid construction and living buildings are in the early stages, and typically are not exchanged between disciplines. We, therefore, consider this review useful to the future development of biohybrid engineering for this highly interdisciplinary application.publishe

MULTIAGENT SYSTEMS IN MODULAR ROBOTICS

The article describes the use of a multi-agent system in modular robotics. Multi-agent systems originated as an extension of the field of distributed artificial intelligence which allows understanding the individual modules as independent agents. By adopting this concept, design direction, which gives the robot a new quality, which is based on the possible effective reconfigure its kinematic and functional structure, thereby taking advantage of the original robot modules generate new variants of the robot with the required new parameters and behavior

Configuration Recognition, Communication Fault Tolerance and Self-reassembly for the CKBot

We present and experimentally verify novel methods for increasing the generality of control, autonomy and reliability for modular robotic systems. In particular, we demonstrate configuration recognition, distributed communication fault tolerance, and the organization and control of self-reassembly with the Connector Kinetic roBot (CKBot). The primary contribution of this work is the presentation and experimental verification of these innovative methods that are general and applicable to other modular robotic systems. We describe our CKBot system and compare it to other similar, state-of-the-art modular robotic systems. Our description and comparison highlights various design developments, features, and notable achievements of these systems. We present work on isomorphic configuration recognition with CKBot. Here, we utilize basic principles from graph theory to create and implement an algorithm on CKBot that automatically recognizes modular robot configurations. In particular, we describe how comparing graph spectra of configuration matrices can be used to find a permutation matrix that maps a given configuration to a known one. If a configuration is matched to one in a library of stored gaits, a permutation mapping is applied and the corresponding coordinated control for locomotion is executed. An implementation of the matching algorithm with small configurations of CKBot configurations that can be rearranged during runtime is presented. We also present work on a distributed fault-tolerance algorithm used to control CKBot configurations. Here, we use a triple modular redundancy approach for CKBot units to collectively vote on observations and execute commands in the presence of infrared (IR) communication failures. In our implementation, we broadcast infrared signals to modules which collaboratively vote on a majority course of action. Various gait selections for a seven module caterpillar and sixteen module quadruped with faulty subsets of IR receivers have been verified to demonstrate the algorithm\u27s robustness. Lastly, we present work on the communication hierarchy and control state machine for the Self-reassembly After Explosion (SAE) robot. Here, we discuss the interaction and integration of the various sensory inputs and control outputs implemented for camera-guided self-reassembly with CKBot. This section describes the overall communication system and reassembly sequence planning after a group of CKBot clusters is kicked apart

AutoFac: The Perpetual Robot Machine

Robotics currently lacks fully autonomous capabilities, especially where task knowledge is incomplete and optimal robotic solutions cannot be pre-engineered. The intersection of evolutionary robotics, artificial life and embodied artificial intelligence presents a promising paradigm for generating multitask problem-solvers suitable for adapting over extended periods in unexplored, remote and hazardous environments. To address the automation of evolving robotic systems, we propose fully autonomous, embodied artificial-life factories and laboratories, situated in various environments as multi-task problem-solvers. Such integrated factories and laboratories would be adaptive solution designers, producing fit-for-purpose physical robots with accelerated artificial evolution that experiment to continually discover new tasks. Such tasks would be stepping-stones towards accomplishing given mission objectives over extended periods (days to decades). Rather than being purely speculative, prerequisite technologies to realize such factories have been experimentally demonstrated. Currently, vast scientific and enterprise opportunities await in applications such as asteroid mining, terraforming, space and deep sea exploration, though no suitable solution exists. The proposed embodied artificial-life factories and laboratories, termed: AutoFac, use robot production equipment run by artificial evolution controllers to collect and synthesize environmental information (from robotic sensory systems). Such information is merged with current needs and mission objectives to create new robot embodiment and task definitions that are environmentally adapted and balance task-oriented behavior with exploration. AutoFac is thus generalist (deployable in many environments) but continually produces specialist solutions within such environments — a perpetual robot machine