Robotic arm- Automated real time object detection

In robotic industry, today, interactions between human and machine usually consists of programming and maintaining machine using human operator. Using a robotic system in any industry for work provides precision and a certain level of accuracy. A robotic entity such as a robotic arm will not ask for time out and can work efficiently day and night which will in turn increase efficiency in workplace. In this paper, we have explained about an arm created, which works in such a way that while the robotic arm is working, camera is able to identify any object it sees which is taken care by the worker looking over the arm. The major outcome and result is the increased efficiency in workplace, precision and accuracy in low cost which can also be used for house hold chores too.

Building a Realistic Virtual Simulator for Unmanned Aerial Vehicle Teleoperation

Unmanned Aerial Vehicles (UAVs) support humans in performing an increasingly varied number of tasks. UAVs need to be remotely operated by a human pilot in many cases. Therefore, pilots require repetitive training to master the UAV movements. Nevertheless, training with an actual UAV involves high costs and risks. Fortunately, simulators are alternatives to face these difficulties. However, existing simulators lack realism, do not present flight information intuitively, and sometimes do not allow natural interaction with the human operator. This work addresses these issues through a framework for building realistic virtual simulators for the human operation of UAVs. First, the UAV is modeled in detail to perform a dynamic simulation in this framework. Then, the information of the above simulation is utilized to manipulate the elements in a virtual 3D operation environment developed in Unity 3D. Therefore, the interaction with the human operator is introduced with a proposed teleoperation algorithm and an input device. Finally, a meta-heuristic optimization procedure provides realism to the simulation. In this procedure, the flight information obtained from an actual UAV is used to optimize the parameters of the teleoperation algorithm. The quadrotor is adopted as the study case to show the proposal’s effectiveness.

A New Approach to Images’ Pespective Transformation in Robotics Telemetry

Remotely controlled robots are the majority of contemporary robots’ population. As a rule such robots are used for inspection, patrolling, mines disposal. This is caused by a fact that today’s level of robots’ autonomy is rather low and autonomous robots can not secure reliable performance. However performance of remotely operated robots depends largely on efficiency of information perception by human-operator. This paper studies images representation to operators on robots’ control pendants. More specifically it studies 3D images representation on flat displays. The goal of this study is to increased reaction rate and decrease errors done by robot’s operator due to image’s uncertainty or poor quality. Our main attention is paid to the development of software that implements the technology of transforming the perspective of images. Matrixes for perspective transformation are studied. Hence application of these matrixes within remotely operated robots is discussed. A novelty of this research is in new knowledge about perspective transformation which is done for a better information perception by human-operator and, as an outcome, to increase efficiency of remotely operated robots. The related technologies in the field of telemetry and technical vision systems have been investigated. Also considered are works in medical fields, in particular, the psychology of perception of images and space. A static software model has been developed. The video camera has been implemented with the introduction of perspective distortions to improve the reliability of the transmission of the necessary areas in the image. Research on the technology is carried out jointly with the Institute of Biomedical Problems of the Russian Academy of Sciences. A special prototype for perspective transformation basing on various scenarios is being developed.

THE INFLUENCE OF DEPENDENCES OF PSYCHOPHYSIOLOGICAL CHARACTERISTICS OF DRIVERS

The article analyzes the "man-machine-environment" system in relation to the psychophysiological characteristics of the driver - "human operator". The methods of diagnosing the psychophysiological characteristics of drivers were analyzed. The dependencies between the parameters of psychophysiological characteristics were established: complex visual-motor reaction and emotional stability (Pearson correlation coefficient r = -0.7), as well as the correlation between emotional stability and the level of perception of speed and distance (r = 0.5). The psychophysiological characteristics at different stages of the driving experience were revealed and practical recommendations were formulated for their development.

Liability for robots I: legal challenges

In robot torts, robots carry out activities that are partially controlled by a human operator. Several legal and economic scholars across the world have argued for the need to rethink legal remedies as we apply them to robot torts. Yet, to date, there exists no general formulation of liability in case of robot accidents, and the proposed solutions differ across jurisdictions. We proceed in our research with a set of two companion papers. In this paper, we present the novel problems posed by robot accidents, and assess the legal challenges and institutional prospects that policymakers face in the regulation of robot torts. In the companion paper, we build on the present analysis and use an economic model to propose a new liability regime which blends negligence-based rules and strict manufacturer liability rules to create optimal incentives for robot torts.

Egocentric Gesture Recognition Using 3D Convolutional Neural Networks for the Spatiotemporal Adaptation of Collaborative Robots

Collaborative robots are currently deployed in professional environments, in collaboration with professional human operators, helping to strike the right balance between mechanization and manual intervention in manufacturing processes required by Industry 4.0. In this paper, the contribution of gesture recognition and pose estimation to the smooth introduction of cobots into an industrial assembly line is described, with a view to performing actions in parallel with the human operators and enabling interaction between them. The proposed active vision system uses two RGB-D cameras that record different points of view of gestures and poses of the operator, to build an external perception layer for the robot that facilitates spatiotemporal adaptation, in accordance with the human's behavior. The use-case of this work is concerned with LCD TV assembly of an appliance manufacturer, comprising of two parts. The first part of the above-mentioned operation is assigned to a robot, strengthening the assembly line. The second part is assigned to a human operator. Gesture recognition, pose estimation, physical interaction, and sonic notification, create a multimodal human-robot interaction system. Five experiments are performed, to test if gesture recognition and pose estimation can reduce the cycle time and range of motion of the operator, respectively. Physical interaction is achieved using the force sensor of the cobot. Pose estimation through a skeleton-tracking algorithm provides the cobot with human pose information and makes it spatially adjustable. Sonic notification is added for the case of unexpected incidents. A real-time gesture recognition module is implemented through a Deep Learning architecture consisting of Convolutional layers, trained in an egocentric view and reducing the cycle time of the routine by almost 20%. This constitutes an added value in this work, as it affords the potential of recognizing gestures independently of the anthropometric characteristics and the background. Common metrics derived from the literature are used for the evaluation of the proposed system. The percentage of spatial adaptation of the cobot is proposed as a new KPI for a collaborative system and the opinion of the human operator is measured through a questionnaire that concerns the various affective states of the operator during the collaboration.

MODELLING OF VTS SUPERVISOR BY ALGORITHM BASED ON PETRI NET: CASE STUDY OF DOVER INCIDENT

The paper deals with collision prevention problem in maritime transport in the area of the narrow canals with predefined routes. The Dover incident, which is analysed and described in the paper, has shown that the control of the passage of ships through the critical areas must be upgraded with an automatic supervising system, which warns the human operator of incorrect ship motion and help the operator to make the right and timely decision. The general idea is to improve the safety of navigation by introduction of automatic collision prevention based on automated supervisor helping to human operator in Vessel Traffic System (VTS) control centre. The VTS supervisor automatically monitors marine traffic by using data from Automatic Radar Plotting Aid (ARPA) radar and others sensors. Such supervisor detects real time and Course Over Ground (COG) of the vessel entering a particular sector, and then estimates the required time for vessel’s passage into another sector. VTS supervisor compares the real time and estimated time of passage of the specific ship through particular sector as a part of surveillance area. In addition, it compares and monitors the deviation of the course during transition of zones (sectors). If significant difference for both values are occurred VTS supervisor triggers a time alarm or a course alarm respectively. In the paper authors have modelled and simulated collision prevention with performed by the alarm actions of VTS supervisor improved with algorithm module based on hybrid Petri net formalism and Visual Object Net ++ tool.

Designing a User-Centered Interaction Interface for Human–Swarm Teaming

A key challenge in human–swarm interaction is to design a usable interface that allows the human operators to monitor and control a scalable swarm. In our study, we restrict the interactions to only one-to-one communications in local neighborhoods between UAV-UAV and operator-UAV. This type of proximal interactions will decrease the cognitive complexity of the human–swarm interaction to O(1). In this paper, a user study with 100 participants provides evidence that visualizing a swarm as a heat map is more effective in addressing usability and acceptance in human–swarm interaction. We designed an interactive interface based on the users’ preference and proposed a controlling mechanism that allows a human operator to control a large swarm of UAVs. We evaluated the proposed interaction interface with a complementary user study. Our testbed and results establish a benchmark to study human–swarm interaction where a scalable swarm can be managed by a single operator.

Virtual reality in Industry

The article deals with the issue and overview of the current trends in the field of virtual reality usage in various sectors. The main aim of contribution is an overview of virtual reality and its key components and tools nowadays, especially in areas such as engineering, automotive industry, civil administration, health care and entertainment industry. There are described the basic tools, applications and functions of virtual reality and its interaction with human operator. The main attention is paid to the use of virtual reality in the engineering industry and its division.

From Human-Human to Human-Machine Cooperation in Manufacturing 4.0

Humans are currently experiencing the fourth industrial revolution called Industry 4.0. This revolution came about with the arrival of new technologies that promise to change the way humans work and interact with each other and with machines. It aims to improve the cooperation between humans and machines for mutual enrichment. This would be done by leveraging human knowledge and experience, and by reactively balancing some complex or complicated tasks with intelligent systems. To achieve this objective, methodological approaches based on experimental studies should be followed to ensure a proper evaluation of human-machine system design choices. This paper proposes an experimental study based on a platform that uses an intelligent manufacturing system made up of mobile robots, autonomous shuttles using the principle of intelligent products, and manufacturing robots in the context of Manufacturing 4.0. Two experiments were conducted to evaluate the impact of teamwork human-machine cooperation, performance, and workload of the human operator. The results showed a lower level of participants’ assessment of time demand and physical demand in teamwork conditions. It was also found that the team working improves the subjective human operator Know-how-to-cooperate when controlling the autonomous shuttles. Moreover, the results showed that in addition to the work organization, other personal parameters, such as the frequency of playing video games could affect the performance and state of the human operator. They raised the importance of further analysis to determine cooperative patterns in a group of humans that can be adapted to improve human-machine cooperation.