## 3 Our Approach  
In a conventional manufacturing process, a worker usually performs repetitive manual and often unergonomic tasks. Workers do most of these tasks mainly using their hands, such as assembly, machine tending, object handling, material processing, etc. Manual work, however, has many limitations which consequently influence the whole process efficiency. Integrating a collaborative robotic solution could significantly improve efficiency while, at the same time, it can alleviate a human worker's physical and mental workload. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Lit.**} & \multirow{2}{*}{**Robotic System**} & \multirow{2}{*}{**Sensor**} & **Visual** & \multirow{2}{*}{**Weareables**} & **Tele-** & **Workspace** & **Pointing** \\  & & & & & **Operation** & **Interaction** & **to Objects** \\ \hline
[11] & UR10 & Leap Motion & Yes & - & Yes & - & - \\
[17] & UR10 simulation & Leap Motion & Yes & - & Yes & - & - \\
[16] & EPSON SCARA LS3-401x & Leap Motion & Yes & - & Yes & - & - \\
[21] & Custom Delta architecture & Leap Motion & Yes & - & Yes & - & - \\
[5] & UR5 & Leap Motion & Yes & - & Yes & - & - \\
[12] & GOOCOL GRB3016 & Leap Motion & Yes & - & Yes & - & - \\
[31] & UR5 & Leap Motion & Yes & - & Yes & - & - \\
[20] & ABB IRB120 & Kinect V2 & Yes & - & Yes & - & - \\
[32] & Baxter & MYO Armband & - & Yes & Yes & Yes & - \\
[33] & UR5 & Microsoft HoloLens & Yes & Yes & Yes & Yes & Yes \\
[19] & Custom 7 DOF robot & Kinect V2 & Yes & - & Yes & - & - \\
[18] & UR5 & Kinect V2 & Yes & - & Yes & - & - \\
[13] & Motoman SDA 10 & Kinect V1 & Yes & - & Yes & - & - \\
[22] & Scorbot ER-7 & Stereo CCD cameras & Yes & - & Yes & Yes & Yes \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of key related works. Our proposed concept for the gestural HRI framework for the collaborative robotic arm aims to create such interaction, where the human worker could interact with the robot as naturally and conveniently as possible. Secondly, besides ergonomics, the framework focuses on flexibility, providing the user with functionality that could be used in numerous application scenarios. Lastly, the framework lays basic foundations for further application development, pushing the flexibility even further. The fundamental principles of the proposed framework are based on the so-called \"linear HRI\" concept introduced by [PERSON] et al. [6], which formulates three simple laws for HRI that state:  
1. Every pair of two joints of a human sensed by a robot form a line. 2. Every line defined by the first law intersects with the robot's environment in one or two places. 3. Every intersection defined by the second law is a potential navigation target or a potential object of reference for the robot. The proposed framework was developed under the laws of linear HRI, where the core functionality lies in the ability to send the end effector of the robotic arm to a specific location on a horizontal/vertical plane using the operator's hand pointing gestures. Humans naturally use pointing gestures to direct someone's attention to the precise location of something in space. Combined with speech, it can be a powerful communication tool. Pointing gestures have many great use-cases among people to signify the importance of a particular object (\"That's the pen I was looking for\" (pointing to the specific one)), express intention (\"I'm going there!\" (pointing to the place)), or specify the exact location of something (\"Can you hand me that screwdriver please?\" (pointing to the specific location in space)). Pointing gestures are incredibly efficient when the traditional speech is insufficient or impossible due to circumstances, such as loud and noisy environments. Let us imagine a collaborative application scenario where the worker performs a delicate assembly task that requires specific knowledge. A collaborative robot would fulfill the role of an intelligent assistant/co-worker.