## 1 Introduction  
Teleoperation is typically used in hazardous or unstructured environments where direct human operations or automatic controls are not available, such as nuclear power plants (NPPs). Therefore, many studies have attempted to use teleoperation in NPPs. Some teleoperation applications in NPP for power plant dismantling [1; 2; 3; 4], object handling [5; 6; 7], pipe cutting [8], and rescue [9] have been studied. In general, teleoperation is performed by viewing only the image screens that appear on the monitor. As a result, this prevents the operator from accurately determining the distance or direction of the target object because the operator only sees the image of the target object displayed on the monitor. Many techniques for performing sophisticated teleoperation tasks to overcome this problem are being studied. Force-rendering techniques are widely used methods in teleoperation to assist operators in controlling haptic devices. In [10], a method was developed to formulate the desired behavior in any number of task frames associated with the task to optimize motion control in a limited workspace. Furthermore, additional linear constraints could have been applied to each task frame. In [11], the effects of force feedback on a blunt dissection task were examined. It was argued that force feedback is useful in this context when there is a large contrast in the mechanical properties along the dissection plane between adjacent areas of the tissue. A parallel robot-aided minimum surgical system with a force-feedback function was employed to study the practical force-feedback effects of artificial tissue samples [12]. The force feedback was provided using pre-programmed rules and provided to the user through the joystick to prevent the robot from falling into an unstable state or coming in contact with an obstacle [13]. In [14; 15], interactive virtual fixture generation with shared control was proposed to harness the cognitive abilities of teleoperators. A retargeting function was used to deal with complex kinematic constraints owing to the difference in topology, anthropometry, joint limits, and degrees of freedom between the human demonstrator and the robot [16; 17; 18]. In [19], a Cartesian-to-Cartesian mapping retargeting function using a data glove and wrist-tracking sensors to control the slave robot was proposed. Overcoming the conspicuous workspace disparity between the master device and the slave robots is also a major problem in teleoperation. To solve this problem, some researchers have implemented hybrid control for teleoperation [20; 21; 22; 23; 24]. In [20], a control method for teleoperation by integrating hybrid position and velocity control with an interoperability protocol was proposed. The proposed method can overcome the difference in the workspace between the master device and the slave robot. Most of the hybrid position-velocity controllers are switched on manually with a specific button at the operator site [20; 21]. The bubble technique, which is based on hybrid position-rate control was also implemented to overcome the disparity in workspace between the master and slave [25; 26; 27]. The control method applied depends on whether the haptic device is inside or outside of the bubble. When the haptic device is inside the bubble, position control is used for fine positioning, and when it is outside the bubble, rate control is applied for coarse positioning. The motion-scaling technique [27; 28] is another well-known technique for dealing with the disparity between the master and slave workspaces. A motion-scaling factor is handled with a scale equal to the ratio of the maximum workspace of the haptic device workspace to the largest workspace of the virtual environment. Another issue in teleoperation is its difficulty, as it is necessary to simultaneously manipulate the slave robot's multiple degrees of freedom while viewing only two-dimensional (2D) camera images that do not give an accurate perspective of the machinery installed at a remote site.