No abstract

A majority of industry based robotic systems are interconnected using IoT (Internet of Things) which has majorly evolved Industry 4.0 applications during the recent decade. The proposed method aims to implement IoT communication to log the details of packages sorted by robotic manipulators. An interactive dashboard is developed using CSS to log the package data and mail alerts are sent to notify the person in-charge. By implementing python request, data is sent to Google Apps Script then concurrently updated in Google Sheets once mail alerts are sent. The logged data is published in a webpage accessed by a HTML based dashboard using AJAX library. Upon completion of sorting, various attributes such as name, quantity, priority and corresponding timestamps of the sorted packages are logged and presented to the end user. In this paper, the functionality of the proposed system is demonstrated in the widely used color-based sorting to perform pick and place tasks. However, the proposed IoT-based approach can be extended to keep track of numerous tasks carried out by several industrial robots within a facility.

The railways are one of the most used means of transport globally and especially in India which is the second largest in the world. Almost more than 140 accidents per year Indian Railways are noting down and 48% of the accidents are due to wheel misalignment of the bogies. Wheel cracks are one of the foremost reasons for the misalignment, and the failure in the wheel causes the derailment of train from the rails. Therefore, periodical inspection of the wheels is necessary to avoid such accidents and disasters. Several Non Destructive Testing (NDT) methods that are quick, reliable and cost effective are utilized for the detection of defects. In this work, a comprehensive review on the numerous NDT inspection methods used for the detection of several types of cracks that occurs on the rail wheels along with their advantages and disadvantages are discussed in detail.

In the recent decade, robotic exploration is emerging as a vast research platform as it prolongs to be a challenging task, especially in unknown dynamic environments. Exploration plays a vital role in collecting data from the areas inaccessible to the human. The operation of manual exploration systems in complex environments is cumbersome due to ineffective noise filtering, poor visibility and shuffling of map characteristics. In order to overcome such drawbacks, our approach focuses on the development of autonomous robotic exploration by designing a robust SLAM-based system, incorporating tri-layered mapping technique for automatic map generation and a new geometrical boundary-based path-planning technique to improve the mobility of the robot during navigation. The proposed path-planning algorithm yields better trajectory planning and obstacle avoidance using the pose, odometry and orientation parameters of the robot. The performance of the developed robot is evaluated through real-time experimentation, and it is evident from the results that, the proposed approach is preferable for autonomous exploration applications.