Amit Shukla

A review of robotics in onshore oil-gas industry

With shrinking resources and increasing demand for petroleum products, oil and gas industries are forced to rethink over their present pace for automatization of industry. New oil fields, mostly located in extreme conditions, are posing serious challenges to both human and environment in terms of safety. Tasks which are repeated, dirty, and dangerous and require high degree of accuracy are already automatized in manufacturing industry. This success has inspired oil and gas industry to lend some of its highly dangerous and repetitive tasks for automation. Most of the processes are remotely operated, and require highly skilled operator. Such processes benefits not only in terms of overall health and safety, by removing humans from hazardous environment, but also by reduction of number staff members required for continuous inspection and manipulation of plant facilities. Considering the sensitivity of inflammable products involved in this industry usage of completely autonomous robots is still a far fetch choice. Therefore, semi-autonomous robots are excellent choice for this industry at-least as near future solution. In oil and gas industry, robots are used both in upstream and downstream process such as pipe handling in drilling operations, pipe inspection, tank inspection, and remote controlled underwater vehicles (ROVs). This paper presents the state of art technology particularly related to application of robotic solutions to in-pipe inspection robots (IPIRs) and tank inspection robots (TIRs) at onshore oil and gas facilities.

Autonomous tracking and navigation controller for an unmanned aerial vehicle based on visual data for inspection of oil and gas pipelines

This paper presents automated navigation control of an Unmanned Aerial Vehicle (UAV) based on visual data gathered by onboard camera. With depletion of easy resources and health, safety and environmental (HSE) challenges in exploiting newly found resources in hostile conditions are forcing oil and gas companies to look for robotic solutions for their problems. Pipelines carrying inflammable and toxic petroleum products are one of the most critical component of oil and gas industry. Being laid in extreme environmental conditions these critical assets require continuous inspection and maintenance. An UAV carrying non-contact sensors is proposed to use for external inspection of the visible pipeline sections. Till now UAVs are mostly used for general purpose visual surveillance while flying at very high altitude but in this novel work we propose accurate tracking and inspection while flying at very low altitude in close vicinity of the ground pipeline structure. Proposed automated inspection of the pipelines by the UAV has two stages firstly identification of the pipeline and secondly navigation control of the UAV for tracking of the pipeline structure. Both identification and tracking are based on visual data gathered by onboard cameras without any additional help of GPS information. This novel navigation control mechanism further has double layers of correction loops namely angular and lateral corrections. Navigation control uses heuristically tunes PID controllers and required geometrical parameters for angular and lateral corrections are extracted from visual data generated by onboard video camera.

Teleoperation by Using Nonisomorphic Mechanisms in the Master–Slave Configuration for Speed Control

This paper presents modeling, simulation, and control of a novel teleoperated mechanism, where two nonisomorphic manipulators are used in one integrated system, with the purpose of usage in oil and gas industry in the future. Overall integration of the teleoperated system has been done in the master–slave configuration, where a stuart-type 6-DOF parallel manipulator is used as a master robot and a 6-DOF serial manipulator is used as a slave robot. Since the parallel manipulator has a closed-loop structure and serial manipulator is an open-loop structure, their work spaces are of completely different nature in terms of overall shape and size. A novel task-space mapping mechanism has been proposed in this work to integrate these two completely nonidentical manipulators. Damped least-squares (DLS) method is used for overcoming the singularity of proposed task-space mapping matrix. This paper also presents detailed dynamic modeling of the parallel manipulator along with comprehensive analysis of proposed novel control technique. The biggest benefit of using proposed integration mechanism is the fullest access of the complete cartesian task spaces of both the master and slave manipulators. This paper also proposes usage of lag compensator for the improved tracking performance. Multilevel control architecture with local actuator-space and joint-space controllers, for the parallel and serial manipulators, respectively, has also been presented in this work.

Autonomous tracking of oil and gas pipelines by an unmanned aerial vehicle

This paper presents automated navigation control of an Unmanned Aerial Vehicle (UAV) for inspection of oil and gas pipelines. The pipelines carrying inflammable and toxic petroleum products require continuous inspection. An UAV equipped with non-contact sensors can be used for external inspection of the pipeline. Most of the UAVs used for surveillance purpose fly at very high altitude and same mechanism can not be used for low flying UAV while tracking ground structures such as pipelines. Current research work proposes novel two layers of autonomous navigation and tracking by UAV. First stage is identification of pipeline and second stage is tracking of it at low altitude. Identification and tracking of the pipelines as linear structure is based on image processing techniques without any assistance of GPS based localization. This autonomous navigation and tracking further has two layers of control loops, firstly angular correction and secondly lateral correction. Both the controllers are based on heuristically tuned simple PID controllers. Overall tracking has shown very good results in terms of stability and visibility of tracked structure from bottom camera of the UAV.

Flocking control of multi-agent system with leader-follower architecture using consensus based estimated flocking center

This paper is concerned about flocking control of a group of mobile agents having leader-follower configuration where the number of leaders is lesser in number than followers. The leaders have the navigation information where the followers only know who the leaders are. Artificial potential function is used to design the distributed control law of the agents. The leaders move as per the tracking information while avoiding collision with other agents. The followers estimate the position of the flocking center and tend to move towards it while aligning velocities and avoiding collisions with neighboring agents. A novel algorithm for estimation of flocking center is introduced in this paper. This algorithm uses consensus concept that makes the followers reach an agreement regarding the flocking center position. The stability analysis of this algorithm shows that the estimation error is asymptotically ε-stable. The agents do not need to know their own positions in global coordinates. The leaders do not access any information from other agents while the followers communicate with its neighboring agents to estimate the flocking center and also to control their motion, the neighborhood being defined by the limited communication range. Simulation results show the effectiveness of the algorithm.

Delay constrained utility maximization in Cyber Physical System with mobile robotic networks

In this work, we approach the problem of maximization of delay constraint utility function for a group of robots using a Cyber-Physical System (CPS) framework. For any task involving coordination of robots, a reliable communication link is required to be established. The maintenance of this link reliability highly depends on trajectories of individual robots. This needs a hybrid approach to be adopted, in which mobility and routing control are taken care of simultaneously. In this paper, a hybrid approach has been proposed based on bidirectional optimization i.e. network utility maximization and energy minimization in the presence of delay constraint. Network Utility function allocates network resources to the robots based on physical constraints involved. The result of this optimization problem would empower the hybrid controller to control both robot position as well as communication link strength.

Autonomous ground piipelines tracking via an UAV

With the aim of inspecting ground pipelines autonomously, an Unmanned Aerial Vehicle (UAV) will be used in this research. Arbitrary object contours in a 2D image could be considered as plane shapes, which will be used to identify their structures. Vision-based tracking is proposed because it is relatively more direct and more accurate than other sensors such as GPS. Image processing is applied to obtain object position information after capturing images by UAV camera, and then the UAV tracks the structure according to these position data autonomously. For such a process, controllers play a key role which can affect response, sensitivity, accuracy and stability of the tracking. In this research, a velocity controller is applied.

Modeling simulation & control of 6-DOF Parallel Manipulator using PID controller and compensator

Abstract This paper presents modeling simulation and control of stuart type 6-DOF parallel manipulator. Dynamic equations of the parallel manipulator are derived by using Kanes method, inheriting all the advantages while circumventing all the disadvantages of Newtown- Euler and Euler-Lagrangian formulations. In this modeling procedure at first all the inertial torques due to platform, motor and actuators are calculated and then this is equated with active torque supplied by the DC-motors in the form of electromagnetic torque. By this force-torque balance, calculation of time varying equivalent inertia of the motor is avoided. Normal PID principle based controllers are not very effective in achieving desired accuracy in trajectory tracking as reported in literature. Therefore, a novel control architecture has been proposed which not only has industry standard PID controller but also includes compensator for drastically improving tracking performance. Since, over all system of parallel manipulator is highly non-linear in nature with coupling terms and varying parameters, only PID controller alone could not reduce this resultant tracking error, even after best tuning. One lag compensator for each actuator has been designed in combination with PID controller, which resulted in significant improvement in trajectory tracking in comparison to former control methods (only normal PID based controller) for all the parameters of cartesian trajectory.