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The purpose of this paper is to describe the reviews of past research work on various in-pipe robotic systems and their operations. This investigation has been focussed on the implemented methodologies for performing in-pipe cleaning and inspection tasks.

This work has been concentrated on review of various sensors used in robots to perform in-pipes inspection operation for determining flaws/cracks, corrosion-affected areas, blocks and coated paint thickness. Various actuators like DC motors, servo motors, pneumatic operated and hydraulic operated are discussed in this review analysis to control the motion of various mechanical components of the robot.

In the current analysis, categorisation of various pipe cleaning robots according to their mechanical structure has been addressed. A lot of information has been gathered regarding the control of in-pipe robots for performing inspection and cleaning tasks.

In this paper, various in-pipe cleaning and inspection techniques have been studied. Necessary information provided regarding different types of in-pipe robots like PIG, wall-pressed, walking, wheel and inchworm. This investigation provides a through literature on various types of sensors like ultrasonic, magnetic, touch, light amplification by stimulated emission of radiation, X-ray, etc., that have been used for inspection and detection of flaws in the pipe.

The purpose of this paper is to study the path-planning problem of an unmanned ground vehicle (UGV) in a predefined, structured environment.

In this investigation, the environment chosen was the roadmap of the National Institute of Technology, Rourkela, obtained from Google maps as reference. An UGV is developed and programmed so as to move autonomously from an indicated source location to the defined destination in the given map following the most optimal path.

An algorithm based on linear search is implemented to the autonomous robot to generate shortest paths in the environment. The developed algorithm is verified with the simulations as well as in experimental environments.

Unlike the past methodologies, the current investigation deals with the global path-planning strategy as the line following mechanism. Moreover, the proposed technique has been implemented in a real-time environment.

In the capricious span of this current millennium, there is a deafening roar in the demand for modernization in the sector of robotics and technology to perform tasks in an intelligent manner. Thus to replenish such necessities, the innovations and inventions of researchers came forward as blessings on human civilization due to their sheer ingenuity and relentless and arduous efforts with each nanosecond passed from now onwards. With the same sublime goal, same resilient endeavor, same aggressive demeanor, the paper on obstacle avoiding robots comes forward. The paper aims to discuss these issues.

It exhibits how to control a differential drive robot wirelessly by analog thumb joystick module with added obstacle avoidance protection. The variations made by the user in the control of analog thumb joystick module are fed as input to the Atmega 16 microcontroller board which further transfers it wirelessly to the robot through the radio frequency (RF) transmitting module. The Arduino mega microcontroller equipped to the robot cross-checks the instructions gained through the RF receiving module and provides power accordingly to the geared motors through the motor driver board for movement along with scanning the environment to avoid obstacles present thereby.

The improvisation of RF technology in controlling the obstacle avoiding robot has enhanced its application and reliability by leaps and bounds reducing the anxiety and tension of the human controller.

With more advanced algorithm and genuine deployment sensors, the idea behind this research work can be used in humanoid robots which can help immensely in going to the extremely dangerous terrains, war zones and also in human rescue operations.

The purpose of this study is to develop an intelligent methodology to find out an optimal feasible assembly sequence while considering the assembly predicates.

This proposed study is carried out by using two artificial immune system-based models, namely, Bone Marrow Model and Negative Selection Algorithms, to achieve the following objectives: to obtain the possible number of assembly sequences; to obtain the feasible assembly sequences while considering different assembly predicates; and to obtain an optimal feasible assembly sequence.

Proposed bone-marrow model determines the possible assembly sequences to ease the intricacy of the problem formulation. Further evaluation has been carried out through negative-selection censoring and monitoring models. These developed models reduce the overall computational time to determine the optimal feasible assembly sequence.

In this paper, the novel and efficient strategies based on artificial immune system have been developed and proposed to obtain all valid assembly sequences and optimized assembly sequence for a given assembled product using assembly attributes. The introduced methodology has proven its effectiveness in achieving optimal assembly sequence with less computational time.

This paper aims to automate the welding operation that motion control, sensor integration and coordination with the welding power source. Therefore, there is a need for sophisticated technologies to control precisely the process in terms of positioning the welding torch, and controlling the welding parameters through the use of correct devices which are aided by appropriate control tools and techniques.

A new seam tracking methodology, named sewing technique, has been introduced for the welded joints available in computer-aided design (CAD) environment. This methodology gives the seam path by drawing a line through the adjacent centroids of curve fitted in the weld joint volume. Obtained geometric path and kinematic constraints are given as input to the modeled robot for performing welding operation followed by desired trajectory.

In this investigation, a novel and efficient weld seam technique has been developed to produce uniform welded joints. The key feature of this approach is that the initial and end positions of the weld seams can be obtained easily. Because of this, the robot can be controlled flexibly during welding operation.

This investigation deals with the development of an automated seam tracking methodology for the welded joints available in CAD environment. Validation of the developed methodology has been done through simulation results while performing welding operations for different weld profiles.

From the past few decades, parallel grippers are used successfully in the automation industries for performing various pick and place jobs due to their simple design, reliable nature and its economic feasibility. So, the purpose of this paperis to design a suitable gripper with appropriate design parameters for better performance in the robotic production systems.

In this paper, an enhanced multi-objective ant lion algorithm is introduced to find the optimal geometric and design variables of a parallel gripper. The considered robotic gripper systems are evaluated by considering three objective functions while satisfying eight constraint equations. The beta distribution function is introduced for generating the initial random number at the initialization phase of the proposed algorithm as a replacement of uniform distribution function. A local search algorithm, namely, achievement scalarizing function with multi-criteria decision-making technique and beta distribution are used to enhance the existing optimizer to evaluate the optimal gripper design problem. In this study, the newly proposed enhanced optimizer to obtain the optimum design condition of the design variables is called enhanced multi-objective ant lion optimizer.

This study aims to obtain optimal design parameters of the parallel gripper with the help of the developed algorithms. The acquired results are investigated with the past research paper conducted in that field for comparison. It is observed that the suggested method to get the best gripper arrangement and variables of the parallel gripper mechanism outperform its counterparts. The effects of the design variables are needed to be studied for a better design approach concerning the objective functions, which is achieved by sensitivity analysis.

The developed gripper is feasible to use in the assembly operation, as well as in other pick and place operations in different industries.

In this study, the problem to find the optimum design parameter (i.e. geometric parameters such as length of the link and parallel gripper joint angles) is addressed as a multi-objective optimization. The obtained results from the execution of the algorithm are evaluated using the performance indicator algorithm and a sensitivity analysis is introduced to validate the effects of the design variables. The obtained optimal parameters are used to develop a gripper prototype, which will be used for the assembly process.

The purpose of this paper is to obtain an optimal mobile robot path planning by the hybrid algorithm, which is developed by two nature inspired meta-heuristic algorithms, namely, cuckoo-search and bat algorithm (BA) in an unknown or partially known environment. The cuckoo-search algorithm is based on the parasitic behavior of the cuckoo, and the BA is based on the echolocation behavior of the bats.

The developed algorithm starts by sensing the obstacles in the environment using ultrasonic sensor. If there are any obstacles in the path, the authors apply the developed algorithm to find the optimal path otherwise reach the target point directly through diagonal distance.

The developed algorithm is implemented in MATLAB for the simulation to test the efficiency of the algorithm for different environments. The same path is considered to implement the experiment in the real-world environment. The ARDUINO microcontroller along with the ultrasonic sensor is considered to obtain the path length and time of travel of the robot to reach the goal point.

In this paper, a new hybrid algorithm has been developed to find the optimal path of the mobile robot using cuckoo search and BAs. The developed algorithm is tested with the real-world environment using the mobile robot.

The purpose of this research work is helpful for recognizing the crushing characteristics of a single toggle jaw crusher during its operation. It is useful for designing a new prototype of this kind of machine with optimal dimensions of the jaw crusher frame and the crushing chamber.

The efficiency of the jaw crusher primarily depends on the kinematic characteristics of the swing jaw plate during the crushing process. The present research work deals with the kinematic analysis of the swing jaw plate of a single toggle jaw crusher.

During the analysis, the system is considered as a four-bar crank rocker mechanism. The force distribution is analyzed based on the results obtained from the motion analysis of the swing jaw plate.

The movement of the swing jaw plate is explained in detail while the machine is in operation. Kinematic analysis of the liner has been performed by considering some points along the swing jaw plate. The results obtained from the movement analysis of the swing jaw plate force distribution along the liner are analyzed. From this analysis, the chamber geometry can be optimized according to the requirement for the crushing motion of different zones in the crushing chamber.

This paper aims to propose fuzzy-regression-particle swarm optimization (PSO) based hybrid optimization approach for getting maximum weld quality in terms of weld strength and bead depth of penetration.

The prediction of welding quality to achieve best of it is not possible by any single optimization technique. Therefore, fuzzy technique has been applied to predict the weld quality in terms of weld strength and weld bead geometry in combination with a multi-performance characteristic index (MPCI). Then regression analysis has been applied to develop relation between the MPCI output value and the input welding process parameters. Finally, PSO method has been used to get the optimal welding condition by maximizing the MPCI value.

The predicted weld quality or the MPCI values in terms of combined weld strength and bead geometry has been found to be highly co-related with the weld process parameters. Therefore, it makes the process easy for setting of weld process parameters for achieving best weld quality, as there is no need to finding the relation for individual weld quality parameter and weld process parameters although they are co-related in a complicated manner.

In this paper, a new hybrid approach for predicting the weld quality in terms of both mechanical properties and weld geometry and optimizing the same has been proposed. As these parameters are highly correlated and dependent on the weld process parameters the proposed approach can effectively analyzing the ambiguity and significance of each process and performance parameter.

In the previous decade, unmanned aerial vehicles (UAVs) have turned into a subject of enthusiasm for some exploration associations. UAVs are discovering applications in different regions going from military applications to activity reconnaissance. The purpose of this paper is to overview a particular sort of UAV called quadrotor or quadcopter.

This paper includes the dynamic models of a quadrotor and the distinctive model-reliant and model-autonomous control systems and their correlation.

In the present time, focus has moved to outlining autonomous quadrotors. Ultimately, the paper examines the potential applications of quadrotors and their part in multi-operators frameworks.

This investigation deals with the review on various quadrotors, their applications and motion control strategies.