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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.robot.2006.02.014 Byline: Miriam Fend, Simon Bovet, Rolf Pfeifer Abstract: Many different animal species rely on whiskers for a variety of tasks. Among the most basic are obstacle avoidance and wall-following. We show that fast and reliable evaluation of distances can be greatly improved by an appropriate sensory morphology that matches the physical space of the agent. To investigate morphologies and material properties of whiskers, we conduct experiments both on a real robot and in simulation using artificial evolution. We find that the morphology that is most successful at following a wall strongly resembles the morphologies of natural whiskers. This can be better understood by considering the relation of the agent body to its tactile sensing range, as well as the challenges of various tasks faced by agents endowed with different sensory modalities. Author Affiliation: Artificial Intelligence Laboratory, University of Zurich, Andreasstr. 15, 8050 Zurich, Switzerland Article History: Received 14 October 2005; Revised 20 February 2006; Accepted 22 February 2006

Prosthetic hands introduce an artificial sensorimotor interface between the prosthesiswearer and the environment that is prone to perturbations. We analyze theoretically and evaluate psychophysically the performance in stable grip control in conditions of physical grasps perturbation, such as object slip. Simulation results suggest that user-centered stable grasp control depends on two primal user parameters: reaction time to slip and grip force intensity. Experiments with human users indicate that a user's response time can be controlled by relaying information about the speed of the slipping object, while minimal grip force intensity can be adjusted with information about grip force at the onset of the slip. Based on our theoretical and experimental findings, we propose a stable grasp control method for prosthetic hands. [ABSTRACT FROM AUTHOR]

It is unavoidable for a soft manipulator to interact with environments during some tasks. These interactions may affect the soft manipulator and make the kinematic model different from the one in free space, e.g., the soft manipulator's effective length and the target positions might change. In order to apply the soft manipulator to constrained environments, an adaptive visual servo controller based on piecewise-constant curvature kinematic, without knowing the true values of the manipulator's length and the target positions, is proposed in this paper. Experimental results in the free space, constrained environment, and the gravity-influenced environment, demonstrate the convergence of the image errors under the proposed controller. [ABSTRACT FROM PUBLISHER]

The shape of soft a manipulator cannot be sensed by the operator directly, when applied to rescue of mine disaster, science exploration, or minimally invasive surgery due to the narrow and closed environment. Shape information is sometimes important for the soft manipulator to be controlled. In order to deal with the problem of shape sensing, a shape sensing algorithm and sensor network based on Fiber Bragg Gratings (FBGs) are introduced in this paper. The shape sensing algorithm is based on piecewise constant curvature and torsion assumption, and can translate the curvature and torsion measured by sensor network into global positions and orientations of nodes. Three-dimensional experiments show that the algorithm introduced in this paper can achieve high accuracy for 3-D shapes. [ABSTRACT FROM PUBLISHER]

In recent years, the development of legged locomotion robots that can achieve both efficiency and versatility has been one of the most important challenges in robotics research. In general, fully actuated systems that can achieve many variations of behaviors show comparatively low energy efficiency, while it is extremely difficult to enrich the behavioral diversity of passivity-based systems that exhibit efficient behaviors. In order to overcome the tradeoff, there has been an increasing interest in the development of actuation technologies, such as variable stiffness actuators (VSAs) that can autonomously adjust mechanical dynamics. However, although many VSAs have been proposed and developed in the past, researchers are yet to clarify how such actuators can improve both energy efficiency and behavioral diversity. From this perspective, the goal of this paper is to investigate a one-legged hopping robot that is equipped with a class of VSA with the intention of explaining how behavioral diversity can be enhanced with modest impact in the energy efficiency. Through a systematic analysis including both simulation and a real-world robot platform, this paper investigates how the natural dynamics of hopping robots can be varied by the actuator resulting in variations in stride frequencies and locomotion speed while maximizing energy efficiency. [ABSTRACT FROM PUBLISHER]

Rich information about artificial grasps can be obtained using tactile sensing arrays. However, the complexity of the integration and computation inherent to tactile sensor arrays limits their applicability for prosthetic manipulators. We present an artificial ridged skin that detects the position and speed of a slipping object using a single force sensor. The artificial skin features parallel ridges arranged in a nonuniform configuration. An evolutionary algorithm generates distributions of ridges evaluated by the accuracy and resolution of detecting the position and speed of a slipping object. Slip experiments on real skins featuring ridge distributions generated by the evolutionary algorithm show that ridge arrangement is critical for an improved sensing of object position and slip speed. We report ridge patterns that detect object position and speed with errors as low as 10 $\%$ at slip speeds of up to 60 mm/s. The artificial skin has an average speed sensing resolution of 10 mm/s, an average position sensing resolution of 15 mm, and is robust to various grip conditions, e.g., speed variation, object weight, and contact area. By exploiting the geometrical features of the artificial skin, enhanced tactile information is acquired. The concept opens a promising avenue for robust and energy-efficient tactile sensing systems. [ABSTRACT FROM PUBLISHER]

Interfacing robots with real biological systems is a potential approach to realizing truly adaptive machines, which is a long-standing engineering challenge. Although plants are widely spread and versatile, little attention has been given to creating cybernetic systems incorporating plants. Producing such systems requires two main steps: the acquisition and interpretation of biological signals, and issuing the appropriate stimulation signals for controlling the physiological response of the biological part. We investigate an automated physiological recovery of young avocado plants by realizing a closed interaction loop between the avocado plant and a water-control device. The study considers the two aforementioned steps by reading out postural cues (leaf inclination) and electrophysiological (biopotential) signals from the plant, and controlling the water resource adaptive to the drought condition of an avocado plant. Analysis of the two signals reveals time-frequency patterns of increased power and global synchronization in the narrow bands when water is available, and local synchronization in the broad bands for water shortage. The results indicate the feasibility of interface technologies between plants and machines, and provide preliminary support for achieving adaptive plant-based ‘machines’ based on plants’ large and robust physiological spectrum and machines’ control scheme diversity. We further discuss fundamental impediments hindering the use of living organisms like plants for artificial systems. [ABSTRACT FROM PUBLISHER]

In quadruped animals, spinal movements contribute to locomotion in terms of controlling body posture and integrating limb and trunk actions. In this paper, we develop quadruped models with different numbers of spinal joints to demonstrate the spine-driven locomotion. Actuated spinal joint(s) are exclusively employed to these models with a minimalistic control strategy. We choose some typical individuals from two models and analyze them on gait properties. Results show that employing the spine morphology with two joints can greatly enhance the stability and speed of locomotion by readjusting the center of mass, increasing the stride length, and generating double flight phases similar to running cheetahs’ gait, which makes significant difference in the speed and the gait. Furthermore, we explore and compare models with more spinal joints. Results show that all gaits emerged from them can be categorized into three types (bounding, bounding with double flight phase, and stotting gaits). Overall, bounding gait with double flight phases is a more biologically inspired locomotive behavior; model with two spinal joints could be sufficient to emulate biological spine-driven locomotive behaviors. [ABSTRACT FROM AUTHOR]

The behaviors of the animals or embodied agents are characterized by the dynamic coupling between the brain, the body, and the environment. This implies that control, which is conventionally thought to be handled by the brain or a controller, can partially be outsourced to the physical body and the interaction with the environment. This idea has been demonstrated in a number of recently constructed robots, in particular from the field of "soft robotics". Soft robots are made of a soft material introducing high-dimensionality, non-linearity, and elasticity, which often makes the robots difficult to control. Biological systems such as the octopus are mastering their complex bodies in highly sophisticated manners by capitalizing on their body dynamics. We will demonstrate that the structure of the octopus arm cannot only be exploited for generating behavior but also, in a sense, as a computational resource. By using a soft robotic arm inspired by the octopus we show in a number of experiments how control is partially incorporated into the physical arm's dynamics and how the arm's dynamics can be exploited to approximate non-linear dynamical systems and embed non-linear limit cycles. Future application scenarios as well as the implications of the results for the octopus biology are also discussed. [ABSTRACT FROM AUTHOR]

Animals and humans engage in an enormous variety of behaviors which are orchestrated through a complex interaction of physical and informational processes: The physical interaction of the bodies with the environment is intimately coupled with informational processes in the animal's brain. A crucial step toward the mastery of all these behaviors seems to be to understand the flows of information in the sensorimotor networks. In this study, we have performed a quantitative analysis in an artificial agent -- a running quadruped robot with multiple sensory modalities -- using tools from information theory (transfer entropy). Starting from very little prior knowledge, through systematic variation of control signals and environment, we show how the agent can discover the structure of its sensorimotor space, identify proprioceptive and exteroceptive sensory modalities, and acquire a primitive body schema. In summary, we show how the analysis of directed information flows in an agent's sensorimotor networks can be used to bootstrap its perception and development. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented in which the editor discusses various reports within the issue on topics including formalization of the concept of morphological computation, the influence of morphology on locomotion, and the link of emotions with changes in morphology.

Anthropomimetic robotics differs from conventional approaches by capitalizing on the replication of the inner structures of the human body, such as muscles, tendons, bones, and joints. Here we present our results of more than three years of research in constructing, simulating, and, most importantly, controlling anthropomimetic robots. We manufactured four physical torsos, each more complex than its predecessor, and developed the tools required to simulate their behavior. Furthermore, six different control approaches, inspired by classical control theory, machine learning, and neuroscience, were developed and evaluated via these simulations or in small-scale setups. While the obtained results are encouraging, we are aware that we have barely exploited the potential of the anthropomimetic design so far. But, with the tools developed, we are confident that this novel approach will contribute to our understanding of morphological computation and human motor control in the future. [ABSTRACT FROM AUTHOR]

Self-organization is a phenomenon found in biomolecular self-assembly by which proteins are spontaneously driven to assemble and attain various functionalities. This study reports on self-organized behavior in which distributed centimeter-sized modules stochastically aggregate and exhibit a translational wheeling motion. The system consists of two types of centimeter-sized water-floating modules: a triangular-shaped module that is equipped with a vibration motor and a permanent magnet (termed the active module), which can quasi- randomly rove around; and circular modules that are equipped with permanent magnets (termed passive modules). In its quasi-random movement in water, the active module picks up passive modules through magnetic attraction. The contacts between the modules induce a torque transfer from the active module to the passive modules. This results in rotational motion of the passive modules. As a consequence of the shape difference between the triangular module and the circular module, the passive modules rotate like wheels, being kept on the same edges as the active module. The motion of the active module is examined, as well as the characteristics and behavior of the self-organization process. [ABSTRACT FROM AUTHOR]

Grasp stability in the human hand has been resolved by means of an intricate network of mechanoreceptors integrating numerous cues about mechanical events, through an ontogenetic grasp practice. An engineered prosthetic interface introduces considerable perturbation risks in grasping, calling for feedback modalities that address the underlying slip phenomenon. In this study, we propose an enhanced slip feedback modality, with potential for myoelectric-based prosthetic applications, that relays information regarding slip events, particularly slip occurrence and slip speed. The proposed feedback modality, implemented using electrotactile stimulation, was evaluated in psychophysical studies of slip control in a simplified setup. The obtained results were compared with vision and a binary slip feedback that transmits on–off information about slip detection. The slip control efficiency of the slip speed display is comparable to that obtained with vision feedback, and it clearly outperforms the efficiency of the on–off slip modality in such tasks. These results suggest that the proposed tactile feedback is a promising sensory method for the restoration of stable grasp in prosthetic applications. [ABSTRACT FROM PUBLISHER]

Self-assembly is a phenomenon broadly observed in nature where a vast number of various molecules spontaneously synthesize complex structures. In this article, prompted by the need for the realization of highly autonomous self-assembly systems that employ magnetism as a driving force, we discuss fundamental issues associated with magnetically driven self-assembly systems. We first introduce some examples from our case studies, in which the models all subscribe to a distributed approach, and thus lack central control. Then we categorize them by their type of magnetic attachment. The issues discussed include several fundamental properties, such as the effect of morphology, stochasticity, the difference between two-dimensional models and three-dimensional models, emergence, allostericity, and parallelism. The conclusions obtained support our stance that the appropriate morphology lightens the control cost for the assembly, providing primal but engaging instances of magnetic self-assembly systems that warrant further study. [ABSTRACT FROM PUBLISHER]

The decay in structure size of manufacturing products has yielded new demands on spontaneous composition methods. The key for the realization of small-sized robots lies in how to achieve the efficient assembly sequence in a bottom-up manner, where most of the parts have only limited (or no) computational (i.e. deliberative) abilities. In this paper, based on a novel self-assembly platform consisting of self-propulsive centimetre-sized modules capable of aggregation on the surface of water, we study the effect of stochasticity and morphology (shape) on the yield of targeted formations in self-assembly processes. Specifically, we focus on a unique phenomenon: that a number of modules instantly compose a target product without forming intermediate subassemblies, some of which constitute undesired geometrical formations (termed one-shot aggregation). Together with a focus on the role that the morphology of the modules plays, we validate the effect of one-shot aggregation with a kinetic rate mathematical model. Moreover, we examined the degree of parallelism of the assembly process, which is an essential factor in self-assembly, but is not systematically taken into account by existing frameworks. [ABSTRACT FROM AUTHOR]

How is our body imprinted in our brain? This seemingly simple question is a subject of investigations of diverse disciplines, psychology, and philosophy originally complemented by neurosciences more recently. Despite substantial efforts, the mysteries of body representations are far from uncovered. The most widely used notions—body image and body schema—are still waiting to be clearly defined. The mechanisms that underlie body representations are coresponsible for the admiring capabilities that humans or many mammals can display: combining information from multiple sensory modalities, controlling their complex bodies, adapting to growth, failures, or using tools. These features are also desirable in robots. This paper surveys the body representations in biology from a functional or computational perspective to set ground for a review of the concept of body schema in robotics. First, we examine application-oriented research: how a robot can improve its capabilities by being able to automatically synthesize, extend, or adapt a model of its body. Second, we summarize the research area in which robots are used as tools to verify hypotheses on the mechanisms underlying biological body representations. We identify trends in these research areas and propose future research directions. [ABSTRACT FROM PUBLISHER]