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.

The human hand is one of the most complex structures in the body, being involved in dexterous manipulation and fine sensing. Traditional engineering approaches have mostly attempted to match such complexity in robotics without sufficiently stressing on the underlying mechanisms that its morphology encodes. In this work, we propose an artificial skin able to encode, through its morphology, the tactile sense of a robotic hand, characteristic to slippage events. The underlying layout consists of ridges and allows slippage detection and the quantification of slippage speed. Such encoding of slippage signal becomes suitable for relaying tactile feedback to users in prosthetic applications. This approach emphasizes the importance of exploiting morphology and mechanics in structures for the design of prosthetic interfaces. Artificial Ridged Skin for Slippage Speed Detection in Prosthetic Hand ApplicationsDana D. Damian, Harold Martinez, Konstantinos Dermitzakis, Alejandro Hernandez-Arieta and Rolf Pfeifer Abstract-The human hand is one of the most complex structures in the body, being involved in dexterous manipulation and fine sensing. Traditional engineering approaches have mostly attempted to match such complexity in robotics without sufficiently stressing on the underlying mechanisms that its morphology encodes. In this work, we propose an artificial skin able to encode, through its morphology, the tactile sense of a robotic hand, characteristic to slippage events. The underlying layout consists of ridges and allows slippage detection and the quantification of slippage speed. Such encoding of slippage signal becomes suitable for relaying tactile feedback to users in prosthetic applications. This approach emphasizes the importance of exploiting morphology and mechanics in structures for the design of prosthetic interfaces.

In this paper we adopt the spring loaded inverted pendulum (SLIP) model as the mathematical framework to represent biped locomotion, but in contrast with previous studies, we redefine the conditions for valid locomotion. As a consequence we identify new ways to produce gait transitions (e.g. change from walking to running) through the control of the angle of attack, at a constant energy level. Moreover, we show that the new valid conditions of locomotion allow the representation of the hopping gait. This new gait requires two different angles of attack for its execution, hence constant angle of attack policies are not applicable. First, we show the regions of phase space where one step gait transitions exist. Next, we report the region where it is possible to generate a periodic hopping gait. Mainly, the two results imply that through the control of the angle of attack the system can exploit its passive dynamics to induce transitions between running, walking and hooping or keep the system stable in any of these gaits. Finally, we briefly discuss the relation between these findings and the use of complaints legs in robots

In the field of developmental robotics, a lot of attention has been devoted to algorithms that allow agents to build up skills through sensorimotor interaction. Such interaction is largely affected by the agent's morphology, that is, its shape, limb articulation, as well as the position and density of sensors on its body surface. Despite its importance, the impact of morphology on behavior has not been systematically addressed. In this paper, we take inspiration from the human vision system, and demonstrate using a binocular active vision platform why sensor morphology in combination with other properties of the body, are essential conditions to achieve coordinated visual behavior (here, vergence). Specifically, to evaluate the effect of sensor morphology on behavior, we present an information-theoretic analysis quantifying the statistical regularities induced through sensorimotor interaction. Our results show that only for an adequate sensor morphology, vergence increases the amount of information structure in the sensorimotor loop. On the Influence of Sensor Morphology on Vergence AbstractIn the field of developmental robotics, a lot of attention has been devoted to algorithms that allow agents to build up skills through sensorimotor interaction. Such interaction is largely affected by the agent's morphology, that is, its shape, limb articulation, as well as the position and density of sensors on its body surface. Despite its importance, the impact of morphology on behavior has not been systematically addressed. In this paper, we take inspiration from the human vision system, and demonstrate using a binocular active vision platform why sensor morphology in combination with other properties of the body, are essential conditions to achieve coordinated visual behavior (here, vergence). Specifically, to evaluate the effect of sensor morphology on behavior, we present an information-theoretic analysis quantifying the statistical regularities induced through sensorimotor interaction. Our results show that only for an adequate sensor morphology, vergence increases the amount of information structure in the sensorimotor loop. On the Influence of Sensor Morphology on VergenceHarold Martinez, Hidenobu Sumioka, Max Lungarella, and Rolf Pfeifer Abstract. In the field of developmental robotics, a lot of attention has been devoted to algorithms that allow agents to build up skills through sensorimotor interaction. Such interaction is largely affected by the agent's morphology, that is, its shape, limb articulation, as well as the position and density of sensors on its body surface. Despite its importance, the impact of morphology on behavior has not been systematically addressed. In this paper, we take inspiration from the human vision system, and demonstrate using a binocular active vision platform why sensor morphology in combination with other properties of the body, are essential conditions to achieve coordinated visual behavior (here, vergence). Specifically, to evaluate the effect of sensor morphology on be...

Developmental robotics focuses on how to endow robots with adaptive capabilities. Even though embodiment has been recognized as an essential factor for understanding development, there is yet not much work that investigates how the morphology of sensors and actuators shapes adaptivity and learning processes. Moreover, these studies are largely at an intuitive and qualitative level. In this paper, we address the issue by studying how in an active vision system sensor morphology and bodily features affect a behavior such as vergence. Specifically, we present an information-theoretic analysis of two experiments showing how adequate sensor morphology influences statistical dependencies in the sensorimotor loop. The results show that an appropriate morphology reduces the amount of input without disrupting the information structure in the sensorimotor loop. The second result shows how the later morphology under the vergence behavior increases the information structure among the motor actions and the pixels. We also speculate on the implications of our results for attention, reaching and grasping. Abstract-Developmental robotics focuses on how to endow robots with adaptive capabilities. Even though embodiment has been recognized as an essential factor for understanding development, there is yet not much work that investigates how the morphology of sensors and actuators shapes adaptivity and learning processes. Moreover, these studies are largely at an intuitive and qualitative level. In this paper, we address the issue by studying how in an active vision system sensor morphology and bodily features affect a behavior such as vergence. Specifically, we present an information-theoretic analysis of two experiments showing how adequate sensor morphology influences statistical dependencies in the sensorimotor loop. The results show that an appropriate morphology reduces the amount of input without disrupting the information structure in the sensorimotor loop. The second result shows how the later morphology under the vergence behavior increases the information structure among the motor actions and the pixels. We also speculate on the implications of our results for attention, reaching and grasping.