A Whole-Body Pose Taxonomy for Loco-Manipulation Tasks

Exploiting interaction with the environment is a promising and powerful way to enhance stability of humanoid robots and robustness while executing locomotion and manipulation tasks. Recently some works have started to show advances in this direction considering humanoid locomotion with multi-contacts, but to be able to fully develop such abilities in a more autonomous way, we need to first understand and classify the variety of possible poses a humanoid robot can achieve to balance. To this end, we propose the adaptation of a successful idea widely used in the field of robot grasping to the field of humanoid balance with multi-contacts: a whole-body pose taxonomy classifying the set of whole-body robot configurations that use the environment to enhance stability. We have revised criteria of classification used to develop grasping taxonomies, focusing on structuring and simplifying the large number of possible poses the human body can adopt. We propose a taxonomy with 46 poses, containing three main categories, considering number and type of supports as well as possible transitions between poses. The taxonomy induces a classification of motion primitives based on the pose used for support, and a set of rules to store and generate new motions. We present preliminary results that apply known segmentation techniques to motion data from the KIT whole-body motion database. Using motion capture data with multi-contacts, we can identify support poses providing a segmentation that can distinguish between locomotion and manipulation parts of an action.Comment: 8 pages, 7 figures, 1 table with full page figure that appears in landscape page, 2015 IEEE/RSJ International Conference on Intelligent Robots and System

Physiological Profile of Male Competitive and Recreational Surfers

Surfing consists of both high- and low-intensity paddling of varying durations, using both the aerobic and anaerobic systems. Surf-specific physiological studies lack adequate group sample sizes, and V[Combining Dot Above]O2peak values are yet to determine the differences between competitive and recreational surfers. The purpose of this study was therefore to provide a comprehensive physiological profile of both recreational and competitive surfers. This multisite study involved 62 male surfers, recreational (n = 47) and competitive (n = 15). Anthropometric measurements were conducted followed by dual-energy x-ray absorptiometry, anaerobic testing and finally aerobic testing. V[Combining Dot Above]O2peak was significantly greater in competitive surfers than in recreational surfers (M = 40.71 ± 3.28 vs. 31.25 ± 6.31 ml·kg·min, p \u3c 0.001). This was also paralleled for anaerobic power (M = 303.93 vs. 264.58 W) for competitive surfers. Arm span and lean total muscle mass was significantly (p ≤ 0.01) correlated with key performance variables (V[Combining Dot Above]O2peak and anaerobic power). No significant (p ≥ 0.05) correlations were revealed between season rank and each of the variables of interest (V[Combining Dot Above]O2peak and anaerobic power). Key performance variables (V[Combining Dot Above]O2peak and anaerobic power) are significantly higher in competitive surfers, indicating that this is both an adaptation and requirement in this cohort. This battery of physiological tests could be used as a screening tool to identify an athlete\u27s weaknesses or strengths. Coaches and clinicians could then select appropriate training regimes to address weaknesses

Fast and Continuous Foothold Adaptation for Dynamic Locomotion through CNNs

Legged robots can outperform wheeled machines for most navigation tasks across unknown and rough terrains. For such tasks, visual feedback is a fundamental asset to provide robots with terrain-awareness. However, robust dynamic locomotion on difficult terrains with real-time performance guarantees remains a challenge. We present here a real-time, dynamic foothold adaptation strategy based on visual feedback. Our method adjusts the landing position of the feet in a fully reactive manner, using only on-board computers and sensors. The correction is computed and executed continuously along the swing phase trajectory of each leg. To efficiently adapt the landing position, we implement a self-supervised foothold classifier based on a Convolutional Neural Network (CNN). Our method results in an up to 200 times faster computation with respect to the full-blown heuristics. Our goal is to react to visual stimuli from the environment, bridging the gap between blind reactive locomotion and purely vision-based planning strategies. We assess the performance of our method on the dynamic quadruped robot HyQ, executing static and dynamic gaits (at speeds up to 0.5 m/s) in both simulated and real scenarios; the benefit of safe foothold adaptation is clearly demonstrated by the overall robot behavior.Comment: 9 pages, 11 figures. Accepted to RA-L + ICRA 2019, January 201

The multi-modality cardiac imaging approach to the Athlete's heart: an expert consensus of the European Association of Cardiovascular Imaging

The term 'athlete's heart' refers to a clinical picture characterized by a slow heart rate and enlargement of the heart. A multi-modality imaging approach to the athlete's heart aims to differentiate physiological changes due to intensive training in the athlete's heart from serious cardiac diseases with similar morphological features. Imaging assessment of the athlete's heart should begin with a thorough echocardiographic examination. Left ventricular (LV) wall thickness by echocardiography can contribute to the distinction between athlete's LV hypertrophy and hypertrophic cardiomyopathy (HCM). LV end-diastolic diameter becomes larger (>55 mm) than the normal limits only in end-stage HCM patients when the LV ejection fraction is <50%. Patients with HCM also show early impairment of LV diastolic function, whereas athletes have normal diastolic function. When echocardiography cannot provide a clear differential diagnosis, cardiac magnetic resonance (CMR) imaging should be performed. With CMR, accurate morphological and functional assessment can be made. Tissue characterization by late gadolinium enhancement may show a distinctive, non-ischaemic pattern in HCM and a variety of other myocardial conditions such as idiopathic dilated cardiomyopathy or myocarditis. The work-up of athletes with suspected coronary artery disease should start with an exercise ECG. In athletes with inconclusive exercise ECG results, exercise stress echocardiography should be considered. Nuclear cardiology techniques, coronary cardiac tomography (CCT) and/or CMR may be performed in selected cases. Owing to radiation exposure and the young age of most athletes, the use of CCT and nuclear cardiology techniques should be restricted to athletes with unclear stress echocardiography or CMR

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 320)

This bibliography lists 125 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during January, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 145

This bibliography lists 301 reports, articles, and other documents introduced into the NASA scientific and technical information system in August 1975

Nonlinear modeling of FES-supported standing-up in paraplegia for selection of feedback sensors

This paper presents analysis of the standing-up manoeuvre in paraplegia considering the body supportive forces as a potential feedback source in functional electrical stimulation (FES)-assisted standing-up. The analysis investigates the significance of arm, feet, and seat reaction signals to the human body center-of-mass (COM) trajectory reconstruction. The standing-up behavior of eight paraplegic subjects was analyzed, measuring the motion kinematics and reaction forces to provide the data for modeling. Two nonlinear empirical modeling methods are implemented-Gaussian process (GP) priors and multilayer perceptron artificial neural networks (ANN)-and their performance in vertical and horizontal COM component reconstruction is compared. As the input, ten sensory configurations that incorporated different number of sensors were evaluated trading off the modeling performance for variables chosen and ease-of-use in everyday application. For the purpose of evaluation, the root-mean-square difference was calculated between the model output and the kinematics-based COM trajectory. Results show that the force feedback in COM assessment in FES assisted standing-up is comparable alternative to the kinematics measurement systems. It was demonstrated that the GP provided better modeling performance, at higher computational cost. Moreover, on the basis of averaged results, the use of a sensory system incorporating a six-dimensional handle force sensor and an instrumented foot insole is recommended. The configuration is practical for realization and with the GP model achieves an average accuracy of COM estimation 16 /spl plusmn/ 1.8 mm in horizontal and 39 /spl plusmn/ 3.7 mm in vertical direction. Some other configurations analyzed in the study exhibit better modeling accuracy, but are less practical for everyday usage