Research on robot path tracking and normal trajectory generation on a curved surface has seen a surge in the last two decades to deal with issues in machining operations. Due to the intricacies involved in complex machining, the real-time correction of robot end-effector position and orientation is highly challenging. The existing approaches are either computationally expensive or inadequate for high accuracy in path tracking and desired normal trajectory generation. Hence, this dissertation explores and implements novel sophisticated contact and non-contact approaches, barring minor complications to empower industrial robots to adjust poses in real-time automatically. In contrast to other studies, the proposed techniques do not require any prior geometric information about the workpiece, such as a CAD model or a 3D scan. Initially, an indigenously developed compliant robotic end-effector tool is employed to effectively deal with challenges in obtaining normal trajectory for machining irregular and curved surfaces. The robot pose correction scheme based on active feedback from a force/torque sensor is suggested to estimate the depth and angle adjustment needed to obtain a normal trajectory. The proposed compliant robotic end-effector tool has a 3-axis force/torque sensor that was specifically designed and tested. Three forces and moments are used to estimate the constant depth and normal angle between the end-effector and the contact surface while tracking the curved surface. The implementation of an automatic tool weight compensation algorithm on DAQ enables the tool to obtain the surface normal contact in real-time. It has been observed that in the contact-based technique, the amount of friction between the workpiece surface and the contact ball significantly affects the system's overall effectiveness. Additionally, the robot teaching pendant was used to manually select the tracking path. To overcome these issues, a depth measurement tool is employed with a key-point manual selection approach to address the challenge of the robot's absolute error while tracking the desired path. For instance, the robot needs to track the desired path while generating the normal trajectory. In addition, an RGB-D camera is used to estimate the contact state between the workpiece surface and the robot end-effector. The camera collects point cloud information on the target surface. The point cloud information is utilized to estimate the surface normal on the curved workpiece. Consequently, adjust the pose of the robot by maintaining a target normal to the surface. The key-point manual selection method is a tedious and time-consuming task. Furthermore, it is somehow challenging to create precise normal trajectories with a camera. Hence, an advanced measuring tool is indigenously developed using 3 laser and a camera to track the desired path and generate normal trajectory in real-time during tracking. To estimate the workpiece's reference coordinate, one of the lasers is used to identify key points on the workpiece. Furthermore, 3 lasers are employed for a surface normal generation using a pose correction algorithm while tracking the desired path. The performance of the proposed schemes is evaluated by conducting numerous experiments employing a dedicated experimental setup.

Research on robot path tracking and normal trajectory generation on a curved surface has seen a surge in the last two decades to deal with issues in machining operations. Due to the intricacies involved in complex machining, the real-time correction of robot end-effector position and orientation is highly challenging. The existing approaches are either computationally expensive or inadequate for high accuracy in path tracking and desired normal trajectory generation. Hence, this dissertation explores and implements novel sophisticated contact and non-contact approaches, barring minor complications to empower industrial robots to adjust poses in real-time automatically. In contrast to other studies, the proposed techniques do not require any prior geometric information about the workpiece, such as a CAD model or a 3D scan. Initially, an indigenously developed compliant robotic end-effector tool is employed to effectively deal with challenges in obtaining normal trajectory for machining irregular and curved surfaces. The robot pose correction scheme based on active feedback from a force/torque sensor is suggested to estimate the depth and angle adjustment needed to obtain a normal trajectory. The proposed compliant robotic end-effector tool has a 3-axis force/torque sensor that was specifically designed and tested. Three forces and moments are used to estimate the constant depth and normal angle between the end-effector and the contact surface while tracking the curved surface. The implementation of an automatic tool weight compensation algorithm on DAQ enables the tool to obtain the surface normal contact in real-time. It has been observed that in the contact-based technique, the amount of friction between the workpiece surface and the contact ball significantly affects the system's overall effectiveness. Additionally, the robot teaching pendant was used to manually select the tracking path. To overcome these issues, a depth measurement tool is employed with a key-point manual selection approach to address the challenge of the robot's absolute error while tracking the desired path. For instance, the robot needs to track the desired path while generating the normal trajectory. In addition, an RGB-D camera is used to estimate the contact state between the workpiece surface and the robot end-effector. The camera collects point cloud information on the target surface. The point cloud information is utilized to estimate the surface normal on the curved workpiece. Consequently, adjust the pose of the robot by maintaining a target normal to the surface. The key-point manual selection method is a tedious and time-consuming task. Furthermore, it is somehow challenging to create precise normal trajectories with a camera. Hence, an advanced measuring tool is indigenously developed using 3 laser and a camera to track the desired path and generate normal trajectory in real-time during tracking. To estimate the workpiece's reference coordinate, one of the lasers is used to identify key points on the workpiece. Furthermore, 3 lasers are employed for a surface normal generation using a pose correction algorithm while tracking the desired path. The performance of the proposed schemes is evaluated by conducting numerous experiments employing a dedicated experimental setup.

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