Active sensorimotor control for tactile exploration

In this paper, we present a novel and robust Bayesian approach for autonomous active exploration of unknown objects using tactile perception and sensorimotor control. Despite recent advances in tactile sensing, robust active exploration remains a challenging problem, which is a major hurdle to the practical deployment of tactile sensors in robots. Our proposed approach is based on a Bayesian perception method that actively controls the sensor with local small repositioning movements to reduce perception uncertainty, followed by explorative movements based on the outcome of each perceptual decision making step. Two sensorimotor control strategies are proposed for improving the accuracy and speed of the active exploration that weight the evidence from previous exploratory steps through either a weighted prior or weighted posterior. The methods are validated both off-line and in real-time on a contour following exploratory procedure. Results clearly demonstrate improvements in both accuracy and exploration time when using the proposed active methods compared to passive perception. Our work demonstrates that active perception has the potential to enable robots to perform robust autonomous tactile exploration in natural environments

Adaptive perception: learning from sensory predictions to extract object shape with a biomimetic fingertip

In this work, we present an adaptive perception method to improve the performance in accuracy and speed of a tactile exploration task. This work extends our previous studies on sensorimotor control strategies for active tactile perception in robotics. First, we present the active Bayesian perception method to actively reposition a robot to accumulate evidence from better locations to reduce uncertainty. Second, we describe the adaptive perception method that, based on a forward model and a predicted information gain approach, allows to the robot to analyse `what would have happened' if a different decision `would have been made' at previous decision time. This approach permits to adapt the active Bayesian perception process to improve the performance in accuracy and reaction time of an exploration task. Our methods are validated with a contour following exploratory procedure with a touch sensor. The results show that the adaptive perception method allows the robot to make sensory predictions and autonomously adapt, improving the performance of the exploration task

Whisking with robots from rat vibrissae to biomimetic technology for active touch

This article summarizes some of the key features of the rat vibrissal system, including the actively controlled sweeping movements of the vibrissae known as whisking, and reviews the past and ongoing research aimed at replicating some of this functionality in biomimetic robots

On Neuromechanical Approaches for the Study of Biological Grasp and Manipulation

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas

Assessing plantar sensation in the foot using the FOot Roughness Discrimination Test (FoRDT™): a reliability and validity study in stroke

BACKGROUND: The foot sole represents a sensory dynamometric map and is essential for balance and gait control. Sensory impairments are common, yet often difficult to quantify in neurological conditions, particularly stroke. A functionally oriented and quantifiable assessment, the Foot Roughness Discrimination Test (FoRDT™), was developed to address these shortcomings. OBJECTIVE: To evaluate inter- and intra-rater reliability, convergent and discriminant validity of the Foot Roughness Discrimination Test (FoRDT™). DESIGN: Test-retest design. SETTING: Hospital Outpatient. PARTICIPANTS: Thirty-two people with stroke (mean age 70) at least 3 months after stroke, and 32 healthy, age-matched controls (mean age 70). MAIN OUTCOME MEASURES: Roughness discrimination thresholds were quantified utilising acrylic foot plates, laser-cut to produce graded spatial gratings. Stroke participants were tested on three occasions, and by two different raters. Inter- and intra-rater reliability and agreement were evaluated with Intraclass Correlation Coefficients and Bland-Altman plots. Convergent validity was evaluated through Spearman rank correlation coefficients (rho) between the FoRDT™ and the Erasmus modified Nottingham Sensory Assessment (EmNSA). RESULTS: Intra- and inter rater reliability and agreement were excellent (ICC =.86 (95% CI .72-.92) and .90 (95% CI .76 -.96)). Discriminant validity was demonstrated through significant differences in FoRDT™ between stroke and control participants (p.05). CONCLUSIONS: This simple and functionally oriented test of plantar sensation is reliable, valid and clinically feasible for use in an ambulatory, chronic stroke and elderly population. It offers clinicians and researchers a sensitive and robust sensory measure and may further support the evaluation of rehabilitation targeting foot sensation. This article is protected by copyright. All rights reserved

The role of self-touch experience in the formation of the self

The human self has many facets: there is the physical body and then there are different concepts or representations supported by processes in the brain such as the ecological, social, temporal, conceptual, and experiential self. The mechanisms of operation and formation of the self are, however, largely unknown. The basis is constituted by the ecological or sensorimotor self that deals with the configuration of the body in space and its action possibilities. This self is prereflective, prelinguistic, and initially perhaps even largely independent of visual inputs. Instead, somatosensory (tactile and proprioceptive) information both before and after birth may play a key part. In this paper, we propose that self-touch experience may be a fundamental mechanisms to bootstrap the formation of the sensorimotor self and perhaps even beyond. We will investigate this from the perspectives of phenomenology, developmental psychology, and neuroscience. In light of the evidence from fetus and infant development, we will speculate about the possible mechanisms that may drive the formation of first body representations drawing on self-touch experience

Augmenting Sensorimotor Control Using “Goal-Aware” Vibrotactile Stimulation during Reaching and Manipulation Behaviors

We describe two sets of experiments that examine the ability of vibrotactile encoding of simple position error and combined object states (calculated from an optimal controller) to enhance performance of reaching and manipulation tasks in healthy human adults. The goal of the first experiment (tracking) was to follow a moving target with a cursor on a computer screen. Visual and/or vibrotactile cues were provided in this experiment, and vibrotactile feedback was redundant with visual feedback in that it did not encode any information above and beyond what was already available via vision. After only 10 minutes of practice using vibrotactile feedback to guide performance, subjects tracked the moving target with response latency and movement accuracy values approaching those observed under visually guided reaching. Unlike previous reports on multisensory enhancement, combining vibrotactile and visual feedback of performance errors conferred neither positive nor negative effects on task performance. In the second experiment (balancing), vibrotactile feedback encoded a corrective motor command as a linear combination of object states (derived from a linear-quadratic regulator implementing a trade-off between kinematic and energetic performance) to teach subjects how to balance a simulated inverted pendulum. Here, the tactile feedback signal differed from visual feedback in that it provided information that was not readily available from visual feedback alone. Immediately after applying this novel “goal-aware” vibrotactile feedback, time to failure was improved by a factor of three. Additionally, the effect of vibrotactile training persisted after the feedback was removed. These results suggest that vibrotactile encoding of appropriate combinations of state information may be an effective form of augmented sensory feedback that can be applied, among other purposes, to compensate for lost or compromised proprioception as commonly observed, for example, in stroke survivors

Active haptic perception in robots: a review

In the past few years a new scenario for robot-based applications has emerged. Service and mobile robots have opened new market niches. Also, new frameworks for shop-floor robot applications have been developed. In all these contexts, robots are requested to perform tasks within open-ended conditions, possibly dynamically varying. These new requirements ask also for a change of paradigm in the design of robots: on-line and safe feedback motion control becomes the core of modern robot systems. Future robots will learn autonomously, interact safely and possess qualities like self-maintenance. Attaining these features would have been relatively easy if a complete model of the environment was available, and if the robot actuators could execute motion commands perfectly relative to this model. Unfortunately, a complete world model is not available and robots have to plan and execute the tasks in the presence of environmental uncertainties which makes sensing an important component of new generation robots. For this reason, today\u2019s new generation robots are equipped with more and more sensing components, and consequently they are ready to actively deal with the high complexity of the real world. Complex sensorimotor tasks such as exploration require coordination between the motor system and the sensory feedback. For robot control purposes, sensory feedback should be adequately organized in terms of relevant features and the associated data representation. In this paper, we propose an overall functional picture linking sensing to action in closed-loop sensorimotor control of robots for touch (hands, fingers). Basic qualities of haptic perception in humans inspire the models and categories comprising the proposed classification. The objective is to provide a reasoned, principled perspective on the connections between different taxonomies used in the Robotics and human haptic literature. The specific case of active exploration is chosen to ground interesting use cases. Two reasons motivate this choice. First, in the literature on haptics, exploration has been treated only to a limited extent compared to grasping and manipulation. Second, exploration involves specific robot behaviors that exploit distributed and heterogeneous sensory data