Safe Interaction Research Articles

Human-like driving decision at unsignalized intersections based on game theory

Unsignalized intersection driving is challenging for automated vehicles. For safe and efficient performances, the diverse and dynamic behaviors of interacting vehicles should be considered. Based on a game-theoretic framework, a human-like payoff design methodology is proposed for the automated decision at unsignalized intersections. Prospect Theory is introduced to map the objective collision risk to the subjective driver payoffs, and the driving style can be quantified as a tradeoff between safety and speed. To account for the dynamics of interaction, a probabilistic model is further introduced to describe the acceleration tendency of drivers. Simulation results show that the proposed decision algorithm can describe the dynamic process of two-vehicle interaction in limit cases. Statistics of uniformly-sampled cases simulation indicate that the success rate of safe interaction reaches 98%, while the speed efficiency can also be guaranteed. The proposed approach is further applied and validated in four-vehicle interaction scenarios at a four-arm intersection.

A Statistical Model to Determine Biomechanical Limits for Physically Safe Interactions With Collaborative Robots

Collaborative robots (cobots) provide a wide range of opportunities to improve the ergonomics and efficiency of manual work stations. ISO/TS 15066 defines power and force limiting (PFL) as one of four safeguarding modes for these robots. PFL specifies biomechanical limits for hazardous impacts and pinching contacts that a cobot must not exceed to protect humans from serious injuries. Most of the limits in ISO/TS 15066 are preliminary, since they are based on unverified data from a literature survey. This article presents a human-subject study that provides new and experimentally verified limits for biomechanically safe interactions between humans and cobots. The new limits are specifically tailored to impact and pinching transferred through blunt and semi-sharp surfaces as they can occur in the event of human error or technical failures. Altogether 112 subjects participated in the study and were subjected to tests with emulated impact and pinching loads at 28 different body locations. During the experiments, the contact force was gradually increased until the load evoked a slightly painful feeling on the subject’s body location under test. The results confirm that the pain thresholds of males and females are different in specific body regions. Therefore, when defining biomechanical limits, the gender difference must be taken into account. A regression model was utilized to incorporate the gender effect as a covariate into a conventional statistical distribution model that can be used to calculate individual limits, precisely fitted to a specific percentile of a mixed group of male and female workers which interacting with cobots.

Minimum distance calculation using skeletal tracking for safe human-robot interaction

One of the main issues about safety in human-robot interaction is the distance calculation between robot and human. The acquisition of real-time distance information between robot and human allows the robot to modify its motion to ensure safety. This paper presents a real-time distance calculation framework that enables safe human-robot interaction. The human is tracked by an RGB-D sensor, and the joint positions of the human are acquired from the skeletal tracking algorithm. The representation of the robot and the human are formed by capsules to simplify and speed up the distance calculation. The distance calculation is implemented by using the GJK (Gilbert-Johnson-Keerthi) algorithm. The framework is validated by simulations and real experiments to show the efficiency of the framework. The results demonstrate the applicability of the framework for safe human-robot interaction applications.

Research on technical scheme for multi type load resource information access

In order to improve the regulation ability of adjustable load resources, realize the aggregation, sharing and regulation of “source-load-storage” regulation resources in the region, and improve the adjustable load management ability, the criteria and methods for accessing the operation system of load resource aggregators to the regulation center are proposed according to the safety protection requirements of power monitoring system and the communication ability of multi type load resource aggregators. To meet the security access of multiple resources, combined with different access modes of load resources, a network security protection mechanism combining software and hardware is proposed. Digital certificate, data encryption, situation awareness, analysis and early warning and other technologies are used to build security protection strategies for private network and different access modes such as Internet, wireless and optical fiber, so as to adapt to the security access of multiple resources. An interaction mode based on standardized data format, using web services (restful HTTPS), file interaction and 104 protocol could be established to adapt multi type adjustable load resource model and safe interaction of real-time data..

Robot System Assistant (RoSA): Towards Intuitive Multi-Modal and Multi-Device Human-Robot Interaction.

This paper presents an implementation of RoSA, a Robot System Assistant, for safe and intuitive human-machine interaction. The interaction modalities were chosen and previously reviewed using a Wizard of Oz study emphasizing a strong propensity for speech and pointing gestures. Based on these findings, we design and implement a new multi-modal system for contactless human-machine interaction based on speech, facial, and gesture recognition. We evaluate our proposed system in an extensive study with multiple subjects to examine the user experience and interaction efficiency. It reports that our method achieves similar usability scores compared to the entirely human remote-controlled robot interaction in our Wizard of Oz study. Furthermore, our framework’s implementation is based on the Robot Operating System (ROS), allowing modularity and extendability for our multi-device and multi-user method.

Bouncing Back: Resilient Human Factor Management

Due to the fourth industrial revolution employees in high-risk environments are confronted with increasing complexity and thus, the need to make ever greater and faster adaptations. As a consequence, the importance of efficient and safe human-machine interactions – in other words, human factors – is constantly growing. In this context, one skill is becoming increasingly relevant: resilience. This ability to react appropriately in difficult situations, recognize mistakes and ‘bounce back’ from adverse or altering circumstances, increasing challenges and possible setbacks is of enormous value, especially for employees in high-risk environments. The basic prerequisite of resilience is considered to be balance of a person’s life energy among the various areas of life – a basic principle of Positive Psychotherapy. In addition, there are several personality traits, competencies and psychosocial factors that have been shown to help improve resilience. Both aspects will be examined in the following article. Also, the article invites self-reflection on one’s own life balance, personality traits and competencies central to resilience. For the encouraging and interesting message is: Resilience can be developed and promoted – and can thereby contribute to increasing safety in high-risk environments as well as to promoting the employees’ health.

Вплив освітнього середовища на психологічне благополуччя студентської молоді

The article analyzes the features of the impact the educational environment on the psychological well-being of student youth. A psychological analysis of the content the educational environment and the essence of the phenomenon of "psychological well-being". The relationship between the psychological well-being of student youth and the psychological characteristics the educational environment is determined. It is stated that the psychological well-being of student youth largely depends on the level of development and quality of the educational environment. It is established that external objective indicators of well-being, such as criteria of success, indicators of health, material well-being, do not affect a person's experience of well-being. Psychological well-being is basically subjective, it is largely due to the special attitude of the individual to himself, the world around him and its individual parties. It is determined that a favorable psychological atmosphere in the educational environment is important for student youth. The more opportunities there are in the educational environment to seek help, the higher the protection against psychological violence, threats, ignoring and hostility from teachers and public humiliation from classmates, the higher the level of student self-acceptance. It is stated that the importance of correct and safe interaction of the subjects of the educational environment is a significant factor in maintaining a high level of psychological well-being of student youth.

APPLICATION OF A PSEUDO-RANDOM NUMBER GENERATOR TO INCREASE THE EFFICIENCY OF SMART DUST TECHNOLOGY IN SMART HOME CONTROL

The article is devoted to the use of pseudo-random number generators to improve the efficiency of Smart Dust technology in the context of smart home management. The article examines the problem of ensuring reliable and safe interaction between Smart Dust technology and the Internet of Things (IoT) in the context of smart home management. To solve this problem, it is proposed to use generators of pseudo-random numbers. The article provides a detailed overview of Smart Dust and IoT technology, including their application in smart home management. The advantages and disadvantages of Smart Dust and IoT technology are analyzed, their possible problems with security and reliability of interaction are indicated. Next, the article describes in detail the principles of pseudorandom number generators and their use in Smart Dust technology. In particular, research is presented on how the use of pseudo-random numbers can help improve the security and reliability of the interaction between Smart Dust technology and IoT. The article also presents a mathematical model of using Smart Dust technology using pseudo-random number generators in smart home management. The algorithm of operation of the Smart Dust technology using a generator of pseudo-random numbers in a smart house has been built. The article provides an analysis of the effectiveness of using pseudorandom number generators for Smart Dust technology in smart home management. For this, experiments were conducted that showed that the use of pseudorandom number generators increases the efficiency of Smart Dust technology and reduces the risk of errors and incorrect system operation. The prospects of using a sequence of pseudo-random numbers in Smart Dust technology are characterized.

FEM-based trajectory tracking control of a soft trunk robot

As a novel class of robots, soft robots have demonstrated many desirable mechanical properties than traditional rigid robots due to their nature of being compliant, flexible and hyper-redundant, such as great adaptability to unknown environments, safe human robot interaction (HRI), energy-saving actuation and the maneuverability to display diverse mechanical properties. However, its inherent high-DoF nature would result in some complex nonlinear behaviors, and their kinematic or dynamic models are therefore harder to deduce than the ones of conventional rigid robots. In this paper, we propose a trajectory tracking control strategy for a soft trunk robot based on Finite Element Method (FEM). We first plan a feasible trajectory for the studied robot in SOFA (a FEM-based simulator) by solving a model-prediction-control (MPC)-based optimization problem. The second step is to conduct linearization around the pre-designed trajectory, based on which an associated controller can be then developed. The detailed derivation of the mentioned work is explained accordingly. In the end, the results of experimental validation is presented to prove the feasibility of the proposed method.

Hand-Eye-Object Tracking for Human Intention Inference

Optimizing human-robot interaction in the performance of collaborative tasks is a challenging problem. An important aspect of this problem relates to the robot's understanding of human intentions. Empowering robots with accurate intention inference capabilities sets the stage for more natural, safe, and effcient interactions and greater confidence in the Human-Robot Interaction domain. Intentions can be deduced by observing human cues as they interact with the environment, but currently, there is no clear-cut method for achieving this in an effective way. Here, we present a novel method for intention inference based on the integration of three visual cues, namely, hand movement, eye fixation, and object interaction, coupled with a bidirectional LSTM neural network for the classification of human intention. Experimental studies evaluating our approach against two-visual cue alternatives confirm the utility of our approach.

Joint-Space Kinematic Control of a Bionic Continuum Manipulator in Real-Time by Using Hybrid Approach

Continuum manipulators are a type of robot used for delicate applications, including safe human-robot interactions. Controlling these manipulators for an accurate trajectory, especially in the case of pneumatic actuation, is extremely challenging. Thus, this article proposes a real-time kinematic trajectory control of a pneumatically actuated multi-segment bionic continuum manipulator with a mobile base by combining a neural network and analytical model with a cascaded controller to overcome this challenge. The inverse kinematics solution of the multi-segment manipulator is developed by using a neural network and an inverse piecewise constant curvature approach. The neural network is trained by using a separate learning algorithm. Although hybrid inverse modeling gives better solutions than existing techniques, significant residual positional error of the manipulator tip remains due to inherent material hysteresis. Thus, a cascaded PI-controller is utilized to compensate for the residual positional error. The controller gains are updated in each step by predictions of the actuator length, where the Jacobian entries are computed from the neural network model. The proposed procedure is validated on Festo Didactics’ elephant trunk-like two-segment continuum manipulator, Robotino-XT. Three different cases are considered for real-time trajectory tracking, where the OptiTrack vision system is used for validation by tracking the manipulator tip pose. For the trajectory points outside the manipulator workspace, simultaneous trunk and base movements are used. In experimental validation, the proposed scheme is shown to give much reduced manipulator tip trajectory error as compared to the existing methods.

ОПЫТ ИСПОЛЬЗОВАНИЯ ФОРМАТА ВИДЕОКОНФЕРЕНЦСВЯЗИ В РАМКАХ ДОПОЛНИТЕЛЬНОГО ПРОФЕССИОНАЛЬНОГО ОБРАЗОВАНИЯ СТУДЕНТОВ ИНЖЕНЕРНЫХ СПЕЦИАЛЬНОСТЕЙ

Currently, we observe a wide use of distance learning technologies at different levels of education, including higher education. The need for safe indirect interaction between teachers and students during the COVID-19 pandemic became the impetus for the widespread implementing and mass “testing” of such technologies. Various types of distance technologies and learning formats are still widely employed, which makes it relevant to search for the ways of their effective usage. The research aims to identify the advantages and disadvantages of using videoconferencing within the system of continuing professional education for engineering students. The tasks of the research are to define the basic concepts of videoconferencing as a tool of pedagogical interaction, as well as to identify, analyze and generalize its advantages and disadvantages based on a survey conducted among students and teachers. The results show generally positive attitude of the respondents to videoconferencing and their readiness to use this format in education process. The findings can help overcome a number of shortcomings of videoconferencing, increase its efficiency and adopt this format in the future.

Ensuring Robot-Human Safety for the BD Spot Using Active Visual Tracking and NMPC With Velocity Obstacles

When humans and robots operate in and occupy the same local space, proximity detection and proactive collision avoidance is of high importance. As legged robots, such as the Boston Dynamics (BD) Spot, start to appear in real-world application environments, ensuring safe robot-human interactions, while operating in full autonomy mode, becomes a critical gate-keeping technology for trust in robotic workers. Towards that problem, this article proposes a track-and-avoid architecture for legged robots that combines a visual object detection and estimation pipeline with a Nonlinear Model Predictive Controller (NMPC) based on the Optimization Engine, capable of generating trajectories that satisfy the avoidance and tracking problems in real-time operations. The system is experimentally evaluated using the BD Spot, in a custom sensor and computational suite, in fully autonomous operational conditions, for the robot-human safety scenario of quickly moving noncooperative obstacles.

State Estimation and Control with a Robust Extended Kalman Filter for a Fabric Soft Robot

Soft robots have shown great potential in safe human-robot interaction. However, their compliant nature makes posture measurement and trajectory tracking a challenging task. Accurate sensing systems such as motion capture devices aren't portable enough to use in any environment, while body-integrated soft sensors create problems like hysteresis. In this work, a robust extended Kalman filter (REKF) based sensor fusion method with an accelerometer, gyroscope, and draw wire sensor is introduced to estimate the bending angle of a fabric-based inflatable bending actuator. The REKF improves upon similar estimation techniques by ensuring a robust estimate regardless of non-linearity or uncertainty in the model. Linear Quadratic Gaussian (LQG) control is integrated with the proposed REKF to demonstrate the REKF based sensor fusion method is useful in control. The results show that the REKF based sensor fusion system presents a portable, robust, accurate estimation of the actuator's bending angle.

Experimental Evaluation Of Intuitive Programming Of Robot Interaction Behaviour During Kinesthetic Teaching Using sEMG And Cutaneous Feedback

Modern applications related to service or production can nowadays benefit from the introduction of collaborative robots already available on the market and endowed with several advanced features such as precise torque control or safe physical interaction with operators. More importantly, collaborative robots allow operators to teach end-effector trajectories by means of physical interaction – known as kinesthetic teaching – which is one of the most intuitive programming-by-demonstration techniques. However, important functionalities provided by modern collaborative robots, like the possibility of performing smooth interactions, cannot be programmed intuitively with the available framework of kinesthetic teaching. In the present study, we propose and experimentally evaluate a robot programming framework for the simultaneous teaching of both trajectories by means of kinesthetic teaching, and robot interaction behavior by means of impedance shaping along the trajectory exploiting a wearable interface. Specifically, the wearable interface is designed to not affect the free motion of the operator, necessary to perform kinesthetic teaching, and it is based on the usage of surface electromyography (sEMG) and vibrotactile stimulation. In this way, we propose an intuitive robot programming framework for an offline robot trajectory and interaction behavior programming, according to which the operator will be able to plan interactions with the environment and humans. In this article, we report a preliminary experimental evaluation of the proposed system, in which an operator will teach a 7-degrees-of-freedom manipulator the execution of a task on a robotic wiring test-bed. In the experiment, the programming of requested compliance levels during the kinesthetic teaching of a trajectory is performed, and the reported results show that the provided wearable interface is successfully exploited by the operator. Finally, the experiment also demonstrates that the offline intuitive programming of trajectories and impedance levels can be exploited online for human-robot co-work.

Designing for Safe, Fun and Informative Online Cross-Partisan Interactions

Designing for Safe, Fun and Informative Online Cross-Partisan Interactions

Toward Safe Wearer-Prosthesis Interaction: Evaluation of Gait Stability and Human Compensation Strategy Under Faults in Robotic Transfemoral Prostheses.

Although advanced wearable robots can assist human wearers, their internal faults (i.e., sensors or control errors) also pose a challenge. To ensure safe wearer-robot interactions, how internal errors by the prosthesis limb affect the stability of the user-prosthesis system, and how users react and compensate for the instability elicited by internal errors are imperative. The goals of this study were to 1) systematically investigate the biomechanics of a wearer-robot system reacting to internal errors induced by a powered knee prosthesis (PKP), and 2) quantify the error tolerable bound that does not affect the user's gait stability. Eight non-disabled participants and two unilateral transfemoral amputees walked on a pathway wearing a PKP, as the controller randomly switched the control parameters to disturbance parameters to mimic the errors caused by locomotion mode misrecognition. The size of prosthesis control errors was systematically varied to determine the error tolerable bound that disrupted gait stability. The effect of the error was quantified based on the 1) mechanical change described by the angular impulse applied by the PKP, and 2) overall gait instability quantified using human perception, angular momentum, and compensatory stepping. The results showed that the error tolerable bound is dependent on the gait phase and the direction of torque change. Two balance recovery strategies were also observed to allow participants to successful respond to the induced errors. The outcomes of this study may assist the future design of an auto-tuning algorithm, volitionally-controlled powered prosthetic legs, and training of gait stability.

Application of Realtime Robotics platform to execute unstructured industrial tasks involving industrial robots, cobots, and human operators

Small and medium-sized craft enterprises are still characterized by production process involving human labour to a large extent. The possibility of a safe interaction of the operator in the collaborative working area of the machine, and the development of an easy-to-program robotic cell, would pave the way to the introduction of automation in such an environment. This paper proposes an application of a commercial platform for collision avoidance, based on Dynamic Road-map algorithms, to execute unstructured industrial tasks involving industrial robots, cobots, and human operators at the same time. An example is presented in a pick-and-place and assembling application, in which the components are feed by a conveyor belt with random order and random flow rate. The adopted platform enhances the possibility to exploit in the same robotic cell both industrial robots and human labour, thus allowing a reduction of costs and more precise applications. Moreover, the possibility to calculate at run-time alternative trajectories to avoid obstacles (both human being and other robot in the cell), avoiding to make the robot temporarily inactive, allows to improve the system productivity.

A 79.7g Manipulator Prototype for E-Flap Robot: A Plucking-Leaf Application

The manipulation capabilities of flapping-wing flying robots (FWFRs) is a problem barely studied. This is a direct consequence of the load-carrying capacity limitation of the flapping-wing robots. Ornithopters will improve the existent multirotor unmanned aerial vehicles (UAVs) since they could perform longer missions and offer a safe interaction in proximity to humans. This technology also opens the possibility to perch in some trees and perform tasks such as obtaining samples from nature, enabling biologists to collect samples in remote places, or assisting people in rescue missions by carrying medicines or first-aid kits. This paper presents a very lightweight manipulator (79.7g) prototype to be mounted on an ornithopter. The distribution of the mass on the flapping-wing robot is sensitive and an extra lumped mass far from the center-of-mass (CoM) of the robot deteriorates the flight stability. A configuration was proposed to avoid changing the CoM. Flight experiments show that adding the arm to the robot only moved the CoM 6mm and the performance of the flight with the manipulator has been satisfactory. Plucking leaf is chosen as an application to the designed system and several experimental tests confirmed successful sampling of leaves by the prototype.

Sensor-based skeleton modeling and MVEEs approach of the redundant manipulator for reaction motion

With the wide application of redundant manipulators, sharing a working space with humans and dealing with uncertainty seems an inevitable problem, especially in the dynamic and unstructured domain. How to deal with obstacle avoidance is of particular importance that robots and humans/environments are safe interactions to fulfill the complex cooperating tasks. This paper aimed at solving the problem of multiple points avoidance for the reaction motion based on the skeleton algorithm in unstructured and dynamic environments. A method named “sensor-based skeleton modeling and MVEEs approach of the redundant manipulator for the reaction motion” is proposed. The extraction of skeleton information from image is obtained to calculate the distances of the multiple control points and establish the repulsion in this method. Afterward, the force Jacobian related to the priority weighting factors is calculated and then a reaction force with damping term is established, which is corresponding nominal torque commands. For the redundant manipulator, the joint angles are obtained through torque iteration instead of inverse kinematics to reduce calculation cost. Finally, the method was tested by a 7-DOF manipulator in the ROS framework. The obtained results indicate that the method in this method can realize dynamic obstacle avoidance and time cost reduction.