Simple Kinesthetic Haptics for Object Recognition

Object recognition is an essential capability when performing various tasks. Humans naturally use either or both visual and tactile perception to extract object class and properties. Typical approaches for robots, however, require complex visual systems or multiple high-density tactile sensors which can be highly expensive. In addition, they usually require actual collection of a large dataset from real objects through direct interaction. In this paper, we propose a kinesthetic-based object recognition method that can be performed with any multi-fingered robotic hand in which the kinematics is known. The method does not require tactile sensors and is based on observing grasps of the objects. We utilize a unique and frame invariant parameterization of grasps to learn instances of object shapes. To train a classifier, training data is generated rapidly and solely in a computational process without interaction with real objects. We then propose and compare between two iterative algorithms that can integrate any trained classifier. The classifiers and algorithms are independent of any particular robot hand and, therefore, can be exerted on various ones. We show in experiments, that with few grasps, the algorithms acquire accurate classification. Furthermore, we show that the object recognition approach is scalable to objects of various sizes. Similarly, a global classifier is trained to identify general geometries (e.g., an ellipsoid or a box) rather than particular ones and demonstrated on a large set of objects. Full scale experiments and analysis are provided to show the performance of the method

Learning Haptic-based Object Pose Estimation for In-hand Manipulation Control with Underactuated Robotic Hands

Unlike traditional robotic hands, underactuated compliant hands are challenging to model due to inherent uncertainties. Consequently, pose estimation of a grasped object is usually performed based on visual perception. However, visual perception of the hand and object can be limited in occluded or partly-occluded environments. In this paper, we aim to explore the use of haptics, i.e., kinesthetic and tactile sensing, for pose estimation and in-hand manipulation with underactuated hands. Such haptic approach would mitigate occluded environments where line-of-sight is not always available. We put an emphasis on identifying the feature state representation of the system that does not include vision and can be obtained with simple and low-cost hardware. For tactile sensing, therefore, we propose a low-cost and flexible sensor that is mostly 3D printed along with the finger-tip and can provide implicit contact information. Taking a two-finger underactuated hand as a test-case, we analyze the contribution of kinesthetic and tactile features along with various regression models to the accuracy of the predictions. Furthermore, we propose a Model Predictive Control (MPC) approach which utilizes the pose estimation to manipulate objects to desired states solely based on haptics. We have conducted a series of experiments that validate the ability to estimate poses of various objects with different geometry, stiffness and texture, and show manipulation to goals in the workspace with relatively high accuracy

Recognition and Estimation of Human Finger Pointing with an RGB Camera for Robot Directive

In communication between humans, gestures are often preferred or complementary to verbal expression since the former offers better spatial referral. Finger pointing gesture conveys vital information regarding some point of interest in the environment. In human-robot interaction, a user can easily direct a robot to a target location, for example, in search and rescue or factory assistance. State-of-the-art approaches for visual pointing estimation often rely on depth cameras, are limited to indoor environments and provide discrete predictions between limited targets. In this paper, we explore the learning of models for robots to understand pointing directives in various indoor and outdoor environments solely based on a single RGB camera. A novel framework is proposed which includes a designated model termed PointingNet. PointingNet recognizes the occurrence of pointing followed by approximating the position and direction of the index finger. The model relies on a novel segmentation model for masking any lifted arm. While state-of-the-art human pose estimation models provide poor pointing angle estimation accuracy of 28deg, PointingNet exhibits mean accuracy of less than 2deg. With the pointing information, the target is computed followed by planning and motion of the robot. The framework is evaluated on two robotic systems yielding accurate target reaching

Unique cerebrospinal fluid peptides: potential amyotrophic lateral sclerosis biomarkers and etiological factors

Aim: Amyotrophic lateral sclerosis (ALS) is a progressive disease of unknown etiology, characterized by degeneration of motoneurons and skeletal muscle strength decline that progressively evolves to respiratory failure and death. A key point in the therapeutic approach is to understand the pathological processes associated with disease evolution. In spite of intensive research on the molecular/cellular mechanisms involved in ALS initiation and progression disease etiology, unfortunately, poorly understood and there is no efficient specific/decisive treatment for ALS patients. The aims of the present study are to identify specific factors in the cerebrospinal fluid (CSF) of ALS patients and to test their potential relevance to the etiology of this disease. Methods: Peptides were identified by liquid chromatography tandem mass spectrometry (LC-MS/MS). Motor activity of mice was tested by the Rota-rod test and peptide-induced inflammation was assessed by induction nitric oxide synthase activity in BV2 microglia cells. Results: Analysis of CSF samples of ALS patients (n = 15) detected two peptides, C-terminal fragments of transthyretin and osteopontin, which were absent in a control group (n = 15). In addition to being potential biomarker candidates, the relevancy of these peptides to the disease etiology was tested by assessing their effects on motor activity in mice and inflammation model in cell culture. Intranasal administration of the peptides reduced motor activity in the Rota-rod test and activated lipopolysaccharide-induced inflammation in BV2 microglia cells. Conclusions: These findings suggest that during ALS onset and progression two potentially neurotoxic peptides are formed, released, or penetrated the central nervous system thus inducing neuroinflammation and neurodegeneration

AllSight: A Low-Cost and High-Resolution Round Tactile Sensor with Zero-Shot Learning Capability

Tactile sensing is a necessary capability for a robotic hand to perform fine manipulations and interact with the environment. Optical sensors are a promising solution for high-resolution contact estimation. Nevertheless, they are usually not easy to fabricate and require individual calibration in order to acquire sufficient accuracy. In this letter, we propose AllSight, an optical tactile sensor with a round 3D structure potentially designed for robotic in-hand manipulation tasks. AllSight is mostly 3D printed making it low-cost, modular, durable and in the size of a human thumb while with a large contact surface. We show the ability of AllSight to learn and estimate a full contact state, i.e., contact position, forces and torsion. With that, an experimental benchmark between various configurations of illumination and contact elastomers are provided. Furthermore, the robust design of AllSight provides it with a unique zero-shot capability such that a practitioner can fabricate the open-source design and have a ready-to-use state estimation model. A set of experiments demonstrates the accurate state estimation performance of AllSight

Reduced levels of alpha-1-antitrypsin in cerebrospinal fluid of amyotrophic lateral sclerosis patients: a novel approach for a potential treatment

Abstract Background: Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative motor neuron disease that involves activation of the immune system and inflammatory response in the nervous system. Reduced level of the immuno-modulatory and anti-inflammatory protein alpha-1-antitrypsin (AAT) is associated with inflammation-related pathologies. The objective of the present is to determine AAT levels and IL-23 in the cerebrospinal fluid (CSF) of ALS patients and control group. Findings: CSF samples from newly diagnosed ALS patients and age-matched controls were analyzed for AAT and IL-23 by ELISA and magnetic luminex screening, respectively. A statistically significant reduction of 45 % in mean AAT levels was observed in the CSF of ALS patients (21.4 μg/ml) as compared to the control group (mean 38.8 μg/ml, p = 0.013). A statistically significant increase of 30.8 % in CSF mean levels of the pro-inflammatory cytokine IL-23 was observed in ALS patients (1647 pg/ml) in comparison to the controls (1259 pg/ml, p = 0.012). A negative correlation coefficient (r = −0.543) was obtained by linear regression analysis of the two measured parameters (p = 0.036). Conclusions: Reduced AAT and elevated IL-23 CSF levels support the notion of neuroinflammatory process occurring in ALS patients. Increasing AAT levels in the patients’ nervous system should be further investigated as a new therapeutic approach and a novel potential tool for ALS treatment

Controlled release implants for cardiovascular disease

The systemic therapy of many cardiovascular diseases is often hampered by adverse drug effects. The present paper examines the use of controlled release implants as a means for optimizing drug concentrations at the affected site in the cardiovascular system, while using a relatively low systemic dose. Controlled release systems have been prepared by combining a drug of choice with either a non-degradable polymer, such as a silicone rubber, polyurethane, and ethylene vinylacetate, or a biodegradable compound such as poly(glycolic-lactic acid) or a high molecular weight polyanhydride. Controlled release matrices containing ethylenehydroxydiphosphonate (EHDP), when implanted next to a bioprosthetic heart valve leaflet, prevented pathologic calcification. Similarly, controlled release matrices containing lidocaine-HCl have been used experimentally as epicardial implants to convert ventricular tachycardia to normal sinus rhythm in dogs. A matrix system containing gentamicin has been used by others [35] to prevent experimental valvular endocarditis. Other workers have used a dexamethasone-releasing cardiac pacing lead in clinical studies, to prevent scar tissue formation, which leads to elevated electrical pacing threshold [15,16]. Future controlled release systems for cardiovascular use will very likely incorporate innovative design features including: a reservoir configuration to replenish or change drug therapy, modulatable drug release to vary drug dosing as desired, and closed-loop feedback to increase or decrease release rates in response to disease status.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28850/1/0000685.pd

Cardiac controlled release for arrhythmia therapy: Lidocaine-polyurethane matrix studies

Cardiac arrhythmias are the principal cause of sudden death due to heart disease, and current therapy is inadequate. A novel approach for formulating a lidocaine-polyurethane controlled release matrix and implanting this drug delivery system directly onto the arrhythmic epicardium is reported. Lidocaine-HCl-polyurethane matrices (28% w/w) were fabricated and studied for their in vitro drug release into physiologic buffer, and their in vivo pharmacologie effectiveness in rapidly converting ouabain-induced ventricular tachycardia in dogs to normal sinus rhythm. In vitro lidocaine release was successfully modulated as a result of variations in fabrication: compression molding, and stirring during polymer synthesis. Lidocaine release in vitro from the most rapidly releasing matrix formulation delivered more than 40% of the contained drug delivered after only 20 minutes, and the remainder slowly released over one week or more. Direct epimyocardial placement of this formulation resulted in the prompt conversion of ouabain-induced ventricular tachycardia to normal sinus rhythm in all experimental animals (n = 6) studied in 1.5 +/- 0.77 min(mean +/- standard error), while controls (n = 4) had persistent ventricular tachycardia for more than 60 min. Site-specific therapy was as rapid as intravenous administration, but with lower plasma lidocaine levels after comparable dosages. It is concluded that lidocaine-polyurethane controlled release matrices can be fabricated with a broad range of initial release profiles, and that these matrices can rapidly initiate the conversion of ouabain-induced ventricular tachycardia to normal sinus rhythm.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/27025/1/0000013.pd