No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Automatic Leg Regeneration for Robot Mobility Recovery
... Robots described in this literature can complete their desired tasks despite sudden changes to their mechanical structures such as broken appendages, damaged sensors, and limb loss. These past adaptations to physical damage have involved a change in: 1) the physical morphology [13]- [17]; 2) the gait generated 1 [18]- [52]; or 3) both the physical structure and gait employed [53]- [56]. In this paper, we narrow our scope to join the second body of literature, research that addresses creating alternate gaits for legged robots in response to limb damage. ...
A vast number of applications for legged robots entail tasks in complex, dynamic environments. But these environments put legged robots at high risk for limb damage. This paper presents an empirical study of fault tolerant dynamic gaits designed for a quadrupedal robot suffering from a single, known ``missing'' limb. Preliminary data suggests that the featured gait controller successfully anchors a previously developed planar monopedal hopping template in the three-legged spatial machine. This compositional approach offers a useful and generalizable guide to the development of a wider range of tripedal recovery gaits for damaged quadrupedal machines.
Microbots can revolutionize various fields of science and technology with applications that require access to confined environments. These microbots could allow engine inspections without disassembly, repair satellite computer boards, assess pollution in confined spaces, and perform surgical procedures in hard-to-reach areas in the human body. However, manufacturing, power supplies, and control of microbots for real-world applications are still significant challenges. More investigations are necessary to develop functional microbots that collect essential information from uncertain environments or disaster areas, in which microbots can manipulate objects and modify the environment. Herein, we present the recent advances in bioinspired walking microrobots, including their design, manufacturing process, and control. In addition, comparisons of the main parameters of various microbots and their potential applications are incorporated. Also, we report the potential challenges of the bioinspired walking microrobots regarding their autonomy systems, manipulation capabilities, reconfigurable systems, and collaborative work. This review can help understand the performance and manufacturing processes of future bioinspired microbots that may access complex terrains or hazardous environments.
Tool manufacture and use are observed not only in humans but also in other animals such as mammals, birds and insects. Manufactured tools are used for biomechanical functions such as effective control of fluids and small solid objects and extension of reaching. These tools are passive and used with gravity and the animal users' own energy. From the perspective of evolutionary biology, manufactured tools are extended phenotypes of the genes of the animal and exhibit phenotypic plasticity. This incurs energetic cost of manufacture as compared to the case with a fixed tool. This paper studies mechanics and energetics aspects of tool manufacture and use in non-human beings. Firstly, it investigates possible mechanical mechanisms of the use of passive manufactured tools. Secondly, it formulates the energetic cost of manufacture and analyses when phenotypic plasticity benefits an animal tool maker and user. We take a synthetic approach and use a controlled physical model, i.e. a robot arm. The robot is capable of additively manufacturing scoop and gripper structures from thermoplastic adhesives to pick and place fluid and solid objects, mimicking primates and birds manufacturing tools for a similar function. We evaluate the effectiveness of tool use in pick-and-place and explain the mechanism for gripper tools picking up solid objects with a solid-mechanics model. We propose a way to formulate the energetic cost of tool manufacture that includes modes of addition and reshaping, and use it to analyse the case of scoop tools. Experiment results show that with a single motor trajectory, the robot was able to effectively pick and place water, rice grains, a pebble and a plastic box with a scoop tool or gripper tools that were manufactured by itself. They also show that by changing the dimension of scoop tools, the energetic cost of tool manufacture and use could be reduced. The work should also be interesting for engineers to design adaptive machines.
The control of robot swarming in a distributed manner is a difficult problem because global behaviors must emerge as a result of many local actions. This paper uses a bio-inspired control method called the Digital Hormone Model (DHM) to control the tasking and executing of robot swarms based on local communication, signal propagation, and stochastic reactions. The DHM model is probabilistic, dynamic, fault-tolerant, computationally efficient, and can be easily tasked to change global behavior. Different from most existing distributed control and learning mechanisms, DHM considers the topological structure of the organization, supports dynamic reconfiguration and self-organization, and requires no globally unique identifiers for individual robots. The paper describes the DHM and presents the experimental results on simulating biological observations in the forming of feathers, and simulating wireless communicated swarm behavior at a large scale for attacking target, forming sensor networks, self-repairing, and avoiding pitfalls in mission execution.
Self-assembly of active, robotic agents, rather than of passive agents such as molecules, is an emerging research field that is attracting increasing attention. Active self-assembly techniques are especially attractive at very small spatial scales, where alternative construction methods are unavailable or have severe limitations. Building nanostructures by using swarms of very simple nanorobots is a promising approach for manufacturing nanoscale devices and systems.
The method described in this paper allows a group of simple, physically identical, identically programmed and reactive (i.e., stateless) agents to construct and repair polygonal approximations to arbitrary structures in the plane. The distributed algorithms presented here are tolerant of robot failures and of externally-induced disturbances. The structures are self-healing, and self-replicating in a weak sense. Their components can be re-used once the structures are no longer needed. A specification of vertices at relative positions, and the edges between them, is translated by a compiler into reactive rules for assembly agents. These rules lead to the construction and repair of the specified shape. Simulation results are presented, which validate the proposed algorithms.
Self-reconfigurable robots are built from modules, which are autonomously able to change the way they are connected, thus changing the overall shape of the robot. This self-reconfiguration process is difficult to control, because it involves the distributed coordination of large numbers of identical modules connected in time-varying ways. We present an approach where a desired shape is grown based on a scalable representation of the desired configuration, which is automatically generated from a 3D CAD model. The size of the configuration is adjusted continually to match the number of modules in the system. This has the advantage that if modules are removed or added, the system automatically adjusts its scale and thus self-repair is obtained as a side effect. This capability is achieved by distributed, local rules for module movement that are independent of the goal configuration. We compare the scale independent approach to one where the desired configuration is grown directly at a fixed scale. We find that the features of the scale independent approach come at the expense of an increased number of moves, messages, and time steps taken to reconfigure.
Cognitive developmental robotics (CDR) aims to provide new understanding of how human's higher cognitive functions develop by means of a synthetic approach that developmentally constructs cognitive functions. The core idea of CDR is ldquophysical embodimentrdquo that enables information structuring through interactions with the environment, including other agents. The idea is shaped based on the hypothesized development model of human cognitive functions from body representation to social behavior. Along with the model, studies of CDR and related works are introduced, and discussion on the model and future issues are argued.
This paper introduces a new challenge problem: designing robotic systems to recover after disassembly from high-energy events and a first implemented solution of a simplified problem. It uses vision-based localization for self- reassembly. The control architecture for the various states of the robot, from fully-assembled to the modes for sequential docking, are explained and inter-module communication details for the robotic system are described.
Developmental robotics is also known as epigenetic robotics. We propose in this paper that there is one substantial difference between developmental robotics and epigenetic robotics, since epigenetic robotics concentrates primarily on modeling the development of cognitive elements of living systems in robotic systems, such as language, emotion, and social skills, while developmental robotics should also cover the modeling of neural and morphological development in single- and multirobot systems. With the recent rapid advances in evolutionary developmental biology and systems biology, increasing genetic and cellular principles underlying biological morphogenesis have been revealed. These principles are helpful not only in understanding biological development, but also in designing self-organizing, self-reconfigurable, and self-repairable engineered systems. In this paper, we propose morphogenetic robotics, an emerging new field in developmental robotics, is an important part of developmental robotics in addition to epigenetic robotics. By morphogenetic robotics, we mean a class of methodologies in robotics for designing self-organizing, self-reconfigurable, and self-repairable single- or multirobot systems, using genetic and cellular mechanisms governing biological morphogenesis. We categorize these methodologies into three areas, namely, morphogenetic swarm robotic systems, morphogenetic modular robots, and morphogenetic body and brain design for robots. Examples are provided for each of the three areas to illustrate the main ideas underlying the morphogenetic approaches to robotics.
A self-assembling and self-repairing mechanical system is experimentally studied to demonstrate its effectiveness. We developed a 2-D model of autonomous me- chanical unit capable of dynamic reconfiguration and inter-unit communication. Self-assembly and self-repair experiments have been carried out using a distributed algorithm developed under the constraints of the system's homogeneity and locality of information exchange. In experiments, more than ten units successfully config- ured themselves and recovered from a fault. Besides the research of the 2-D model, a model of 3-D system and its self-assembly algorithm are also developed.
Research in man-made systems capable of self-diagnosis and self- repair is becoming increasingly relevant in a range of scenarios in which in situ repair/diagnosis by a human operator is infeasi- ble within an appropriate time frame. In this paper, we present an approach to the multi-robot team diagnosis problem that utilizes gradient-based training of multivariate Gaussian distributions. We then evaluate this approach using a testbed involving modular mo- bile robots, each assembled from four electromechanically separable modules. The diagnosis algorithm is trained on data obtained from two sources: (1) a computer model of the system dynamics and (2) experimental runs of the physical prototypes. Tests were then per- formed in which a fault was introduced in one robot in the testbed and the diagnostic algorithm was queried. The results show that the state predicted by the diagnostic algorithm performed well in iden- tifying the fault state in the case when the model was trained using the experimental data. Limited convergence was also demonstrated using training data from an imperfect dynamic model and low data sampling frequencies. KEY WORDS—diagnosis, fault diagnosis, self diagnosis, team diagnosis, robot team repair, mobile robot, robotics, multi-robot system, modular robot, gradient-based training, particle filters.
We present a set of tools and a process, making use of inexpensive and environmentally friendly materials, that enable the rapid realization of fully functional large scale prototypes of folded mobile millirobots. By mimicking the smart composite microstructure (SCM) process at a 2-10X scale using posterboard, and commonly available polymer films, we can realize a prototype design in a matter of minutes compared with days for a complicated SCM design at the small scale. The time savings enable a significantly shorter design cycle by allowing for immediate discovery of design flaws and introduction of design improvements prior to beginning construction at the small scale. In addition, the technology eases the difficulty of visualizing and creating folded 3D structures from 2D parts. We use the example of a fully functional hexapedal crawling robot design to illustrate the process and to verify a scaling law which we propose.
A distributed formation control method is proposed for a modular
mechanical system. We have developed a totally decentralized system
composed of many homogeneous mechanical units which are designed to
change their connective configuration using only local information. The
control method proposed in this paper enables the systems to re-organize
themselves so that various configurations can be formed in a robust way.
Computer simulations and experiments are carried out to show its
effectiveness
Self-repair robots are modular robots that have the capability of detecting and recovering from failures. Typically, such robots are unit-modular and carry a number of redundant modules on their bodies. Self-repair consists of detecting the failure of a module, ejecting the bad module and replacing it with one of the extra modules. In this paper we show how self-repair can be accomplished by self-reconfiguring Crystalline robots. We describe the Crystalline robots, which consist of modules that can aggregate together to form distributed robot systems and are actuated by expanding and contracting each unit. This actuation mechanism permits automated shape metamorphosis. We also describe an algorithm that uses this actuation mechanism for self-repair.
Robotic systems are increasingly being used in hazardous environments and remote locations to safely extend human reach. However, these systems can be faced with unexpected events or system faults. Currently, the standard paradigm is to either leave a damaged robot in the field, or to rely on human invention for repair or retrieval. Therefore, a need exists for systems that offer long-term robustness in the face of such failures. In this paper, we present the Hexagonal Distributed Modular Robot (Hex-DMR) II System which is comprised of a team of several autonomous mobile robots capable of performing repair procedures on individual robots in the team. Hex-DMR II represents a potential solution to the longstanding problem of fragility in robotic systems in remote environments. First, we introduce the design elements of the second-generation system and contrast them to its first-generation counterpart. Then we describe the modular team members that result and summarize the repair process. Finally, we experimentally demonstrate the functionality of our system by performing two autonomous procedures necessary for repair.
We present a set of tools and a process, making use of inexpensive and environmentally friendly materials, that enable the rapid realization of fully functional large scale prototypes of folded mobile millirobots. By mimicking the smart composite microstructure (SCM) process at a 2–10X scale using posterboard, and commonly available polymer films, we can realize a prototype design in a matter of minutes compared with days for a complicated SCM design at the small scale. The time savings enable a significantly shorter design cycle by allowing for immediate discovery of design flaws and introduction of design improvements prior to beginning construction at the small scale. In addition, the technology eases the difficulty of visualizing and creating folded 3D structures from 2D parts. We use the example of a fully functional hexapedal crawling robot design to illustrate the process and to verify a scaling law which we propose.
The capability of extending body structures is one of the most significant challenges in the robotics research and it has been partially explored in self-reconfigurable robotics. By using such a capability, a robot is able to adaptively change its structure from, for example, a wheel like body shape to a legged one to deal with complexity in the environment. Despite their expectations, the existing mechanisms for extending body structures are still highly complex and the flexibility in self-reconfiguration is still very limited. In order to account for the problems, this paper investigates a novel approach to robotic body extension by employing an unconventional material called Hot Melt Adhesives (HMAs). Because of its thermo-plastic and thermo-adhesive characteristics, this material can be used for additive fabrication based on a simple robotic manipulator while the established structures can be integrated into the robot's own body to accomplish a task which could not have been achieved otherwise. This paper first investigates the HMA material properties and its handling techniques, then evaluates performances of the proposed robotic body extension approach through a case study of a “water scooping” task.
The ATRON self-reconfigurable robot consists of simple interconnected modules. Modules move relative to other modules and as a result change the shape of the robot. The ATRON modules are difficult to control because of complex motion constraints on the modules. Motion constraints are reduced by using meta-modules composed of three modules. A meta-module may emerge from unstructured groups of modules if three modules are connected in the right configuration. The meta-module then moves on a surface of modules and stop at another position. To attract moving meta-modules and thereby to specify the shape-changing task of the robot we use attraction-points. In this work we evolve a distributed artificial neural network controller for the modules. The controller is identical on every module and controls when a meta-module emerges, how it move and when it stops. In simulation we demonstrate how this control strategy allows the ATRON robot to shape-change to support an unstable roof, build a bridge across a gap and to self-repair a broken bone. We conclude that the control strategy is able to shape-change and self-repair the ATRON robot independent on whether it consists of dozens, hundreds or thousands of modules
We describe a decentralized algorithm for coordinating a swarm of identically-programmed mobile agents to spatially self-aggregate into arbitrary shapes using only local interactions. Our approach, called SHAPEBUGS, generates a consensus coordinate system by agents continually performing local trilaterations, and achieves shape formation by simultaneously allowing agents to disperse within the defined 2D shape using a gas expansion model. This approach has several novel features (1) agents can easily aggregate into arbitrary user-specified shapes, using a formation process that is independent of the number of agents (2) the system automatically adapts to influx and death of agents, as well as accidental displacement. We show that the consensus coordinate system is robust and provides reasonable accuracy in the face of significant sensor and movement error.
Shape adaptation through soft-matter extended phenotype enhances robots’ functionality
- wang
Hormone-inspired self-organization and distributed control of robotic swarms
- W.-M Shen
- P Will
- A Galstyan