A survey of ontology-enabled processes for dependable robot autonomy.

Autonomous robots are already present in a variety of domains performing complex tasks. Their deployment in open-ended environments offers endless possibilities. However, there are still risks due to unresolved issues in dependability and trust. Knowledge representation and reasoning provide tools for handling explicit information, endowing systems with a deeper understanding of the situations they face. This article explores the use of declarative knowledge for autonomous robots to represent and reason about their environment, their designs, and the complex missions they accomplish. This information can be exploited at runtime by the robots themselves to adapt their structure or re-plan their actions to finish their mission goals, even in the presence of unexpected events. The primary focus of this article is to provide an overview of popular and recent research that uses knowledge-based approaches to increase robot autonomy. Specifically, the ontologies surveyed are related to the selection and arrangement of actions, representing concepts such as autonomy, planning, or behavior. Additionally, they may be related to overcoming contingencies with concepts such as fault or adapt. A systematic exploration is carried out to analyze the use of ontologies in autonomous robots, with the objective of facilitating the development of complex missions. Special attention is dedicated to examining how ontologies are leveraged in real time to ensure the successful completion of missions while aligning with user and owner expectations. The motivation of this analysis is to examine the potential of knowledge-driven approaches as a means to improve flexibility, explainability, and efficacy in autonomous robotic systems.

A Review and Evaluation of Control Architectures for Modular Legged and Climbing Robots.

Robotic control is a fundamental part of autonomous robots. Modular legged and climbing robots are complex machines made up of a variety of subsystems, ranging from a single robot with simple legs to a complex system composed of multiple legs (or modules) with computing power and sensitivity. Their complexity, which is increased by the fact of needing elements for climbing, makes a correct structure crucial to achieve a complete, robust, and versatile system during its operation. Control architectures for legged robots are distinguished from other software architectures because of the special needs of these systems. In this paper, we present an original classification of modular legged and climbing robots, a comprehensive review of the most important control architectures in robotics, focusing on the control of modular legged and climbing robots, and a comparison of their features. The control architecture comparison aims to provide the analytical tools necessary to make informed decisions tailored to the specific needs of your robotic applications. This article includes a review and classification of modular legged and climbing robots, breaking down each category separately.

Supervised learning for improving the accuracy of robot-mounted 3D camera applied to human gait analysis.

BACKGROUND AND OBJECTIVE: the use of 3D cameras for gait analysis has been highly questioned due to the low accuracy they have demonstrated in the past. The objective of the study presented in this paper is to improve the accuracy of the estimations made by robot-mounted 3D cameras in human gait analysis by applying a supervised learning stage. METHODS: the 3D camera was mounted in a mobile robot to obtain a longer walking distance. This study shows an improvement in detection of kinematic gait signals and gait descriptors by post-processing the raw estimations of the camera using artificial neural networks trained with the data obtained from a certified Vicon system. To achieve this, 37 healthy participants were recruited and data of 207 gait sequences were collected using an Orbbec Astra 3D camera. There are two basic possible approaches for training and both have been studied in order to see which one achieves a better result. The artificial neural network can be trained either to obtain more accurate kinematic gait signals or to improve the gait descriptors obtained after initial processing. The former seeks to improve the waveforms of kinematic gait signals by reducing the error and increasing the correlation with respect to the Vicon system. The second is a more direct approach, focusing on training the artificial neural networks using gait descriptors directly. RESULTS: the accuracy of the 3D camera to objectify human gait was measured before and after training. In both training approaches, a considerable improvement was observed. Kinematic gait signals showed lower errors and higher correlations with respect to the ground truth. The accuracy of the system to detect gait descriptors also showed a substantial improvement, mostly for kinematic descriptors rather than spatio-temporal. When comparing both training approaches, it was not possible to define which was the absolute best. CONCLUSIONS: supervised learning improves the accuracy of 3D cameras but the selection of the training approach will depend on the purpose of the study to be conducted. This study reveals the great potential of 3D cameras and encourages the research community to continue exploring their use in gait analysis.

Bioinspired Whisker Sensor for 3D Mapping of Underground Mining Environments.

Traversing through challenging, unstructured environments, particularly in mining scenarios characterized by dust concentration, darkness, and lack of communication presents formidable obstacles for traditional sensing technologies. Drawing inspiration from naked mole rats, characterized as being skilled subterranean navigators that depend heavily on touch to navigate their environment, this study introduces a new whisker-sensing disk designed for 3D mapping in unstructured environments. The disk comprises a circular array of 32 whisker sensors, each featuring a slender flexible plastic rod attached to a compliant base housing a 3D Hall-effect sensor. The whisker sensor is modeled using both analytical and data-driven approaches to predict rotation angles based on magnetic field measurements. The validation and comparison of both models are performed by evaluating data from other whisker sensors. Additionally, a series of experiments demonstrates the whisker disk's capability in performing 3D-mapping tasks, along with successful implementation on diverse robotic platforms, highlighting its future potential for effective 3D mapping in complex and unstructured subterranean environments.

Design and Kinematic Modeling of a Soft Continuum Telescopic Arm for the Self-Assembly Mechanism of a Modular Robot.

In recent years, the development of mining robots has grown significantly, offering improved efficiency and safety in hazardous environments. However, there is still room for improvement in adaptability, scalability, and overall performance. The ROBOMINERS project, funded by the European Union's Horizon 2020 Research and Innovation Program, aims to facilitate Europe's access to mineral resources applying disruptive robotic concepts. One such concept is resilience, which can be achieved providing modular mining robots with the ability to reconfigure during operation. To address this challenge, this article presents the development and kinematic modeling of a soft, telescopic, continuum arm integrated into a modular robot. The arm serves as a mechanical interface for coupling different robotic modules or tools following the principle of the car crane. With a fully 3D-printed design, the arm features two sections of variable length that are driven by an innovative actuation method based on soft racks. It provides a 6 degrees of freedom (DoF) motion. The arm kinematic models are obtained by backbone parameterization assuming constant curvature and independent bending between sections for forward kinematics and applying a machine learning-based approach for inverse kinematics. The models are validated through the evaluation of two trajectories, measuring the deviation in each DoF and rack extension. Furthermore, a demonstration of the arm's coupling procedure between two robotic modules and one possible configuration of the robotic system showcases its functionality.

Rapid sperm length divergence in a polygynandrous passerine: a mechanism of cryptic speciation?

When populations become geographically isolated, they begin to diverge in various traits and at variable rates. The dynamics of such trait divergences are relevant for understanding evolutionary processes such as local adaptation and speciation. Here we examine divergences in sperm and body structures in a polygynandrous songbird, the alpine accentor (Prunella collaris) between two allopatric high-altitude populations, in Morocco and Spain. The populations diverged around 82,000 years ago, as estimated with a coalescence-based phylogenetic analysis of genome-wide single-nucleotide polymorphisms. We found that birds in the two areas had nonoverlapping sperm lengths, which suggests adaptation to divergent female reproductive tract environments. Sperm length also showed an exceptionally low coefficient of among-male variation, a signal of strong stabilizing selection imposed by sperm competition. The evolutionary rate of sperm length was almost twice the rates for the most divergent morphological traits and more than three times higher than expected from literature data over a similar generational timescale. This rapid evolution of a key reproductive trait has implications for reproductive isolation and ultimately for speciation. Strong selection for different sperm length optima in allopatry predicts conspecific sperm precedence and disruptive selection in sympatry, hence a possible postcopulatory prezygotic barrier to gene flow.

Performance of a Mobile 3D Camera to Evaluate Simulated Pathological Gait in Practical Scenarios.

Three-dimensional (3D) cameras used for gait assessment obviate the need for bodily markers or sensors, making them particularly interesting for clinical applications. Due to their limited field of view, their application has predominantly focused on evaluating gait patterns within short walking distances. However, assessment of gait consistency requires testing over a longer walking distance. The aim of this study is to validate the accuracy for gait assessment of a previously developed method that determines walking spatiotemporal parameters and kinematics measured with a 3D camera mounted on a mobile robot base (ROBOGait). Walking parameters measured with this system were compared with measurements with Xsens IMUs. The experiments were performed on a non-linear corridor of approximately 50 m, resembling the environment of a conventional rehabilitation facility. Eleven individuals exhibiting normal motor function were recruited to walk and to simulate gait patterns representative of common neurological conditions: Cerebral Palsy, Multiple Sclerosis, and Cerebellar Ataxia. Generalized estimating equations were used to determine statistical differences between the measurement systems and between walking conditions. When comparing walking parameters between paired measures of the systems, significant differences were found for eight out of 18 descriptors: range of motion (ROM) of trunk and pelvis tilt, maximum knee flexion in loading response, knee position at toe-off, stride length, step time, cadence; and stance duration. When analyzing how ROBOGait can distinguish simulated pathological gait from physiological gait, a mean accuracy of 70.4%, a sensitivity of 49.3%, and a specificity of 74.4% were found when compared with the Xsens system. The most important gait abnormalities related to the clinical conditions were successfully detected by ROBOGait. The descriptors that best distinguished simulated pathological walking from normal walking in both systems were step width and stride length. This study underscores the promising potential of 3D cameras and encourages exploring their use in clinical gait analysis.

MoCLORA-An Architecture for Legged-and-Climbing Modular Bio-Inspired Robotic Organism.

MoCLORA (Modular Climbing-and-Legged Robotic Organism Architecture) is a software framework for climbing bio-inspired robotic organisms composed of modular robots (legs). It is presented as a modular low-level architecture that coordinates the modules of an organism with any morphology, at the same time allowing exchanges between the physical robot and its digital twin. It includes the basic layers to control and coordinate all the elements, while allowing adding new higher-level components to improve the organism's behavior. It is focused on the control of both the body and the legs of the organism, allowing for position and velocity control of the whole robot. Similarly to insects, which are able to adapt to new situations after the variation on the capacity of any of their legs, MoCLORA allows the control of organisms composed of a variable number of modules, arranged in different ways, giving the overall system the versatility to tackle a wide range of tasks in very diverse environments. The article also presents ROMERIN, a modular climbing and legged robotic organism, and its digital twin, which allows the creation of different module arrangements for testing. MoCLORA has been tested and validated with both the physical robot and its digital twin.

ROBOGait: A Mobile Robotic Platform for Human Gait Analysis in Clinical Environments.

Mobile robotic platforms have made inroads in the rehabilitation area as gait assistance devices. They have rarely been used for human gait monitoring and analysis. The integration of mobile robots in this field offers the potential to develop multiple medical applications and achieve new discoveries. This study proposes the use of a mobile robotic platform based on depth cameras to perform the analysis of human gait in practical scenarios. The aim is to prove the validity of this robot and its applicability in clinical settings. The mechanical and software design of the system is presented, as well as the design of the controllers of the lane-keeping, person-following, and servoing systems. The accuracy of the system for the evaluation of joint kinematics and the main gait descriptors was validated by comparison with a Vicon-certified system. Some tests were performed in practical scenarios, where the effectiveness of the lane-keeping algorithm was evaluated. Clinical tests with patients with multiple sclerosis gave an initial impression of the applicability of the instrument in patients with abnormal walking patterns. The results demonstrate that the system can perform gait analysis with high accuracy. In the curved sections of the paths, the knee joint is affected by occlusion and the deviation of the person in the camera reference system. This issue was greatly improved by adjusting the servoing system and the following distance. The control strategy of this robot was specifically designed for the analysis of human gait from the frontal part of the participant, which allows one to capture the gait properly and represents one of the major contributions of this study in clinical practice.

Spatio-temporal variation in the wintering associations of an alpine bird.

Many animals make behavioural changes to cope with winter conditions, being gregariousness a common strategy. Several factors have been invoked to explain why gregariousness may evolve during winter, with individuals coming together and separating as they trade off the different costs and benefits of living in groups. These trade-offs may, however, change over space and time as a response to varying environmental conditions. Despite its importance, little is known about the factors triggering gregarious behaviour during winter and its change in response to variation in weather conditions is poorly documented. Here, we aimed at quantifying large-scale patterns in wintering associations over 23 years of the white-winged snowfinch Montifringilla nivalis nivalis. We found that individuals gather in larger groups at sites with harsh wintering conditions. Individuals at colder sites reunite later and separate earlier in the season than at warmer sites. However, the magnitude and phenology of wintering associations are ruled by changes in weather conditions. When the temperature increased or the levels of precipitation decreased, group size substantially decreased, and individuals stayed united in groups for a shorter time. These results shed light on factors driving gregariousness and points to shifting winter climate as an important factor influencing this behaviour.

Smart Assistive Architecture for the Integration of IoT Devices, Robotic Systems, and Multimodal Interfaces in Healthcare Environments.

This paper presents a new architecture that integrates Internet of Things (IoT) devices, service robots, and users in a smart assistive environment. A new intuitive and multimodal interaction system supporting people with disabilities and bedbound patients is presented. This interaction system allows the user to control service robots and devices inside the room in five different ways: touch control, eye control, gesture control, voice control, and augmented reality control. The interaction system is comprised of an assistive robotic arm holding a tablet PC. The robotic arm can place the tablet PC in front of the user. A demonstration of the developed technology, a prototype of a smart room equipped with home automation devices, and the robotic assistive arm are presented. The results obtained from the use of the various interfaces and technologies are presented in the article. The results include user preference with regard to eye-base control (performing clicks, and using winks or gaze) and the use of mobile phones over augmented reality glasses, among others.

CFD Modelling and Optimization Procedure of an Adhesive System for a Modular Climbing Robot.

Adhesion systems are very important in robots for infrastructure inspection (especially in vertical walls). They present the challenge of optimizing the ratio vacuum/power consumption in battery-powered robots. In this paper, a CFD (computer fluid dynamics) modelling and optimization process of a robot adhesion system is carried out to determine the best performing configuration in terms of vacuum and power consumption. Analytical and numerical models were developed to predict the behaviour of the system for different configurations. The models were validated, using test rig measurements, by calibrating an arbitrary defined inlet height that simulates the leakage flow. Then, different geometric parameters were varied to determine the best performing configuration based on the vacuum/power consumption ratio value. The model presented in the paper was capable of predicting the behaviour of the system for different configurations, with a margin of error of 15% for the vacuum prediction and 25% for the motor power calculation. Finally, the model was used to optimize parameters of the system, like the number of blades of the impeller. The adhesion system was conceived for the modular autonomous climbing legged robot ROMERIN.

The Accuracy of the Microsoft Kinect V2 Sensor for Human Gait Analysis. A Different Approach for Comparison with the Ground Truth.

Several studies have examined the accuracy of the Kinect V2 sensor during gait analysis. Usually the data retrieved by the Kinect V2 sensor are compared with the ground truth of certified systems using a Euclidean comparison. Due to the Kinect V2 sensor latency, the application of a uniform temporal alignment is not adequate to compare the signals. On that basis, the purpose of this study was to explore the abilities of the dynamic time warping (DTW) algorithm to compensate for sensor latency (3 samples or 90 ms) and develop a proper accuracy estimation. During the experimental stage, six iterations were performed using the a dual Kinect V2 system. The walking tests were developed at a self-selected speed. The sensor accuracy for Euclidean matching was consistent with that reported in previous studies. After latency compensation, the sensor accuracy demonstrated considerably lower error rates for all joints. This demonstrated that the accuracy was underestimated due to the use of inappropriate comparison techniques. On the contrary, DTW is a potential method that compensates for the sensor latency, and works sufficiently in comparison with certified systems.

Home Camera-Based Fall Detection System for the Elderly.

Falls are the leading cause of injury and death in elderly individuals. Unfortunately, fall detectors are typically based on wearable devices, and the elderly often forget to wear them. In addition, fall detectors based on artificial vision are not yet available on the market. In this paper, we present a new low-cost fall detector for smart homes based on artificial vision algorithms. Our detector combines several algorithms (background subtraction, Kalman filtering and optical flow) as input to a machine learning algorithm with high detection accuracy. Tests conducted on over 50 different fall videos have shown a detection ratio of greater than 96%.

Impact of two adjustable-autonomy models on the scalability of single-human/multiple-robot teams for exploration missions.

OBJECTIVE: The aim of this study was to evaluate two models for adjusting autonomy in mobile robots to find out the best way for the operator to interact with the system with as many robots as possible. The first model is the most used in mobile robots; the second proposes a flexible autonomy management. BACKGROUND: There are different ways of adjusting the autonomy level in man-machine systems: adjustable autonomy, in which the operator has the initiative over the autonomy level; adaptive autonomy, in which the autonomy level is adjusted depending on the task and context; and mixed initiatives. One of the drawbacks of using adjustable autonomy is that it is claimed not to be flexible enough, resulting in a high operator workload. We propose and evaluate a flexible adjustable autonomy model for robot-team supervision. METHOD: Two experiments were designed to test the scalability and performance of the man-machine system with two alternative configurations for the autonomy management. The independent variable is the number of robots, and the measured variable is the man-machine system performance. The experiments are between subjects. We have used ANOVA and Bonferroni post hoc analysis for analyzing the results. RESULTS: On the basis of these analyses,we conclude that a flexible adjustable autonomy model results in better performance than the classic, rigid one, in which the operator directly chooses the autonomy level. CONCLUSION: Flexible autonomy adjustment permits one operator to control a team of robots with better results in terms of performance and robot use, as he or she can directly act at the error level, leaving the responsibility of readjusting and resuming the task to the system and hence reducing the operator's workload. APPLICATION: The results can be applied to exploration robotics, mainly, in which one operator controls a team of robots. In general, these principles can be extended to other single-man/multiple-machine systems.

A bacterial TrwC relaxase domain contains a thermally stable alpha-helical core.

The TrwC protein is the relaxase-helicase responsible for the initiation and termination reactions of DNA processing during plasmid R388 conjugation. The TrwC-N275 fragment comprises the 275-amino-acid N-terminal domain of the protein that contains the DNA cleavage and strand transfer activities (the relaxase domain). It can be easily purified by keeping a cell lysate at 90 degrees C for 10 min. Infrared spectroscopy shows that this domain has a predominantly alpha/beta structure with some amount of unordered structure. Fast heating and cooling does not change the secondary structure, whereas slow heating produces two bands in the infrared spectrum characteristic of protein aggregation. The denaturation temperature is increased in the protein after the fast-heating thermal shock. Two-dimensional infrared correlation spectroscopy shows that thermal unfolding is a very cooperative two-state process without any appreciable steps prior to aggregation. After aggregation, the alpha-helix percentage is not altered and alpha-helix signal does not show in the correlation maps, meaning that the helices are not affected by heating. The results indicate that the domain has an alpha-helix core resistant to temperature and responsible for folding after fast heating and an outer layer of beta-sheet and unordered structure that aggregates under slow heating. The combination of a compact core and a flexible outer layer could be related to the structural requirements of DNA-protein binding.