Search results

The purpose of this paper is to propose a robotic system for percutaneous surgery. The key component in the system, a robotic arm that can manipulate a puncture needle is presented. The mechanical design, the motion control and the force control method of the robotic arm are discussed in the paper.

The arm with an arc mechanism placed on a 3D Cartesian stage is developed as a puncture needle manipulator to locate the position of the needle tip, tune the needle’s posture and actuate the puncture motion under the visual guidance of two orthogonal X-ray images of a patient by a surgeon. A focusing method by using two laser spots is proposed to automatically move the needle tip to a surgery entry point on the skin. A dynamics model is developed to control the position of the needle mechanism and an explicit force control strategy is utilized to perform the needle insertion.

With the surgical system, a surgeon can easily perform puncture operation by taking two orthogonal real-time X-ray images as a visual feedback and accurately navigating the needle insertion. The laser-guided focusing method is efficient in placement of the needle tip. The explicit force control strategy is proved to be effective for holding constant and stable puncture force in experiments.

The robotic arm has an advantage in easy redirection of the needle because the rotation and the translation are decoupled in the mechanism. By adopting simple laser pens and a well-developed kinematics model, the system can handle the entry point, locating task automatically. The focusing method and the force control method proposed in the paper are useful for the present system and could be intuitive for similar surgical robots.

The first step toward developing an automated construction workers performance monitoring system is to initially establish a complete and competent activity recognition solution, which is still lacking. This study aims to propose a novel approach of using labor physiological data collected through wearable sensors as means of remote and automatic activity recognition.

A pilot study is conducted against three pre-fabrication stone construction workers throughout three full working shifts to test the ability of automatically recognizing the type of activities they perform in-site through their lively measured physiological signals (i.e. blood volume pulse, respiration rate, heart rate, galvanic skin response and skin temperature). The physiological data are broadcasted from wearable sensors to a tablet application developed for this particular purpose, and are therefore used to train and assess the performance of various machine-learning classifiers.

A promising result of up to 88% accuracy level for activity recognition was achieved by using an artificial neural network classifier. Nonetheless, special care needs to be taken for some activities that evoke similar physiological patterns. It is expected that blending this method with other currently developed camera-based or kinetic-based methods would yield higher activity recognition accuracy levels.

The proposed method complements previously proposed labor tracking methods that focused on monitoring labor trajectories and postures, by using additional rich source of information from labors physiology, for real-time and remote activity recognition. Ultimately, this paves for an automated and comprehensive solution with which construction managers could monitor, control and collect rich real-time data about workers performance remotely.

Lubricating oil leakage is a common issue in thermal power plant operation sites, requiring prompt equipment maintenance. The real-time detection of leakage occurrences could avoid disruptive consequences caused by the lack of timely maintenance. Currently, inspection operations are mostly carried out manually, resulting in time-consuming processes prone to health and safety hazards. To overcome such issues, this paper proposes a machine vision-based inspection system aimed at automating the oil leakage detection for improving the maintenance procedures.

The approach aims at developing a novel modular-structured automatic inspection system. The image acquisition module collects digital images along a predefined inspection path using a dual-light (i.e. ultraviolet and blue light) illumination system, deploying the fluorescence of the lubricating oil while suppressing unwanted background noise. The image processing module is designed to detect the oil leakage within the digital images minimizing detection errors. A case study is reported to validate the industrial suitability of the proposed inspection system.

On-site experimental results demonstrate the capabilities to complete the automatic inspection procedures of the tested industrial equipment by achieving an oil leakage detection accuracy up to 99.13%.

The proposed inspection system can be adopted in industrial context to detect lubricant leakage ensuring the equipment and the operators safety.

The proposed inspection system adopts a computer vision approach, which deploys the combination of two separate sources of light, to boost the detection capabilities, enabling the application for a variety of particularly hard-to-inspect industrial contexts.

This paper aims to analyze the application of remotely piloted aircraft (RPA) for remote oil spill sensing.

This paper is an analysis of RPA strong points.

To increase the accuracy and eliminate potentially false contamination detection, which can be caused by external factors, an oil thickness measurement algorithm is used with the help of the multispectral imaging that provides high accuracy and is versatile for any areas of water and various meteorological and atmospheric conditions.

SWOT analysis of implementation of RPA for remote sensing of oil spills.

The use of RPA will improve the remote sensing of oil spills.

The concept of oil spills monitoring needs to be developed for quality data collection, oil pollution control and emergency response.

The research covers the development of a method and design of a device intended for taking samples and determining the presence of oil contamination in an aquatorium area; the procedure includes taking a sample from the water surface, preparing it for transportation and delivering the sample to a designated location by using the RPA. The objective is to carry out the analysis of remote oil spill sensing using RPA. The RPA provides a reliable sensing of oil pollution with significant advantages over other existing methods. The objective is to analyze the use of RPA employing all of their strong points. In this paper, technical aspects of sensors are analyzed, as well as their advantages and limitations.

The authors set out to show how key private security industry actors in Sweden establish body-worn cameras (BWCs) as a tool to protect private security officers from the public the officers police and to improve the work environment of the officers.

The authors conducted qualitative semi-structured interviews with key personnel involved in the implementation of BWCs. The authors' analysis focused on delineating recurrent moral stories and affirmative environments to show how BWC use was made legitimate as a work environment tool.

The authors show how BWC use by private security officers patrolling public spaces in Sweden is legitimized by four organizational narratives: (1) the vulnerable security officer and the caring employer, (2) defenders of protective regulation, (3) moral selves and morally dubious others and (4) function creep and moral guardians. The authors explain how such organizational narratives are key to establishing and legitimizing the use of BWCs as a tool to improve the work environment of private security guards, and how certain narrative environments promote such organizational narratives in Sweden to improve the work environment of private security guards.

The authors' findings in this article add to a small but growing literature on BWC use in policing outside of the USA and the UK as well as to the hitherto very limited research from the work environment and managerial perspectives. The authors illustrate the importance of organizational narratives and narrative environments for understanding organizational change involving legitimation of new technologies.

To support the standardized evaluation of bicyclist automatic emergency braking (AEB) systems, test scenarios, test procedures and test system hardware and software tools have been investigated and developed by the Transportation Active Safety Institute (TASI) at Indiana University-Purdue University Indianapolis. This paper aims to focus on the development of test scenarios and bicyclist surrogate for evaluating vehicle–bicyclist AEB systems.

The harmonized general estimates system (GES)/FARS 2010-2011 crash data and TASI 110-car naturalistic driving data (NDD) are used to determine the crash geometries and environmental factors of crash scenarios including lighting conditions, vehicle speeds, bicyclist speeds, etc. A surrogate bicyclist including a bicycle rider and a bicycle surrogate is designed to match the visual and radar characteristics of bicyclists in the USA. A bicycle target is designed with both leg pedaling and wheel rotation to produce proper micro-Doppler features and generate realistic motion for camera-based AEB systems.

Based on the analysis of the harmonized GES/FARS crash data, five crash scenarios are recommended for performance testing of bicyclist AEB systems. Combined with TASI 110-car naturalistic driving data, the crash environmental factors including lighting conditions, obscuring objects, vehicle speed and bicyclist speed are determined. The surrogate bicyclist was designed to represent the visual and radar characteristics of the real bicyclists in the USA. The height of the bicycle rider mannequin is 173 cm, representing the weighted height of 50th percentile US male and female adults. The size and shape of the surrogate bicycle were determined as 26-inch wheel and mountain/road bicycle frame, respectively. Both leg pedaling motion and wheel rotation are suggested to produce proper micro-Doppler features and support the camera-based AEB systems.

The results have demonstrated that the developed scenarios, test procedures and bicyclist surrogate will provide effective objective methods and necessary hardware and software tools for the evaluation and validation of bicyclist AEB systems. This is crucial for the development of advanced driver assistance systems.

This study aims to present a vision-guided robotic system design for application in vat photopolymerization additive manufacturing (AM), enabling vat photopolymerization AM hybrid with injection molding process.

In the system, a robot equipped with a camera and a custom-made gripper as well as driven by a visual servoing (VS) controller is expected to perceive objective, handle variation, connect multi-process steps in soft tooling process and realize automation of vat photopolymerization AM. Meanwhile, the vat photopolymerization AM printer is customized in both hardware and software to interact with the robotic system.

By ArUco marker-based vision-guided robotic system, the printing platform can be manipulated in arbitrary initial position quickly and robustly, which constitutes the first step in exploring automation of vat photopolymerization AM hybrid with soft tooling process.

The vision-guided robotic system monitors and controls vat photopolymerization AM process, which has potential for vat photopolymerization AM hybrid with other mass production methods, for instance, injection molding.