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This paper aims to improve the performance of a two-camera robotic feedback system designed for automatic pick and place application by modifying its velocity profile during switching of control.

Cooperation of global and local vision sensors ensures visibility of the target for a two-camera robotic system. The master camera, monitoring the workspace, guides the robot such that image-based visual servoing (IBVS) by the eye-in-hand camera transcends its inherent shortcomings. A hybrid control law steers the robot until the system switches to IBVS in a region proven for its asymptotic stability and convergence through a qualitative overview of the scheme. Complementary gain factors can ensure a smooth transition in velocity during switching considering the versatility and range of the workspace.

The proposed strategy is verified through simulation studies and implemented on a 6-DOF industrial robot ABB IRB 1200 to validate the practicality of adaptive gain approach while switching in a hybrid visual feedback system. This approach can be extended to any control problem with uneven switching surfaces or coarse/fine controllers which are subjected to discrete time events.

In complex workspace where robots operate in parallel with other robots/humans and share workspaces, the supervisory control scheme ensures convergence. This study proves that hybrid control laws are more effective than conventional approaches in unstructured environments and visibility constraints can be overcome by the integration of multiple vision sensors.

The supervisory control is designed to combine the visual feedback data from eye-in-hand and eye-to-hand sensors. A gain adaptive approach smoothens the velocity characteristics of the end-effector while switching the control from master camera to the end-effector camera.

Real-time implementation of sophisticated algorithms on robotic systems demands a rewarding interface between hardware and software components. Individual robot manufacturers have dedicated controllers and languages. However, robot operation would require either the knowledge of additional software or expensive add-on installations for effective communication between the robot controller and the computation software. This paper aims to present a novel method of interfacing the commercial robot controllers with most widely used simulation platform, e.g. MATLAB in real-time with a demonstration of visual predictive controller.

A remote personal computer (PC), running MATLAB, is connected with the IRC5 controller of an ABB robotic arm through the File Transfer Protocol (FTP). FTP server on the IRC5 responds to a request from an FTP client (MATLAB) on a remote computer. MATLAB provides the basic platform for programming and control algorithm development. The controlled output is transferred to the robot controller through Ethernet port as files and, thereby, the proposed scheme ensures connection and control of the robot using the control algorithms developed by the researchers without the additional cost of buying add-on packages or mastering vendor-specific programming languages.

New control strategies and contrivances can be developed with numerous conditions and constraints in simulation platforms. When the results are to be implemented in real-time systems, the proposed method helps to establish a simple, fast and cost-effective communication with commercial robot controllers for validating the real-time performance of the developed control algorithm.

The proposed method is used for real-time implementation of visual servo control with predictive controller, for accurate pick-and-place application with different initial conditions. The same strategy has been proven effective in supervisory control using two cameras and artificial neural network-based visual control of robotic manipulators.

This paper elaborates a real-time example using visual servoing for researchers working with industrial robots, enabling them to understand and explore the possibilities of robot communication.

This study assesses the SDG-related well-being of indigenous communities in India using bibliometric analysis and the ADO-TCM framework. It provides insights into their alignment with sustainable development objectives.

This study analysed 74 high-impact journals using bibliometric analysis to evaluate the well-being of India’s indigenous peoples about the SDGs.

This study analyses the well-being of tribal communities in India using existing scholarly articles and the ADO-TCM framework. It emphasises the importance of implementing Sustainable Development Goals (SDGs) to promote the well-being of indigenous populations.

This study uses bibliometric analysis and the ADO-TCM framework to investigate factors impacting tribal community welfare. It proposes theoretical frameworks, contextual considerations and research methodologies to achieve objectives.

COVID-19 pandemic interrupted global supply chains (SCs) affecting both developed and developing countries. In context of the COVID-19 pandemic, numerous studies were conducted on sustainable supply chain (SSC) in emerging markets (EMs). However, the contributions of these studies require to be systematically reviewed to provide a platform of knowledge. The purpose of this review is to systematically explore the relevant literature on SSC management during the COVID-19 pandemic in EMs.

The authors applied Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to perform a systematic literature review. Scopus database was used to extract the relevant literature, and 51 journal articles along with 5 conference proceedings were included in the study.

This study identified the major contents along with four different themes, which are the impacts of COVID-19 on the SC, recovery strategies to alleviate the adverse impacts of COVID-19, sustainable practices to improve SC performance and resilience activities to assure firms' survivability. Furthermore, the research reveals that interview/survey/case study–based research and review articles focusing on various industries have dominated the field of SSC management in the context of EMs.

This research enriches the literature by providing an overall scenario of SSC during the COVID-19 pandemic in the context of emerging economies.