## 3 Intuitive and Natural Teleoperation
Communication delays between different hardware components could disrupt the real-time feedback loop, impacting teleoperation tasks that demand quick response times. Minimizing latency and optimizing communication protocols were crucial in maintaining stable and efficient communication [62]. Furthermore, coordinating control signals sent to different hardware modules, such as manipulator arms and grippers, necessitated precise synchronization to prevent erratic movements or inaccuracies, highlighting the importance of synchronization mechanisms for ensuring precise and coordinated actions. To overcome these challenges and ensure stable and efficient communication in the integration of teleoperation systems with diverse hardware platforms, several strategies were employed. Implementing standardized communication protocols, such as ROS (Robot Operating System) messages, facilitated interoperability between different hardware components, ensuring consistent data exchange and compatibility across various devices that use different programming languages. Designing a unified software architecture with ROS and interface engines, such as Unity 3D, which abstracted underlying hardware complexities, was essential. This design allowed for the implementation of high-level control algorithms and user interfaces without the need to consider hardware-specific details, thereby promoting interoperability and ease of development [63; 64]. In summary, the integration of ROS and Unity-based software architectures enable easy expansion and adaptation to new devices and sensors used in telemanufacturing aspects, such as remote robotic welding. Teleoperation systems cope with dynamic environments by integrating advanced technologies such as sensor fusion, artificial intelligence, machine learning, adaptive algorithms, and human supervision [65; 66]. These systems use various sensors to gather real-time data and employ AI algorithms to process and adapt to dynamic changes. Environmental mapping techniques, like simultaneous localization and mapping (SLAM), enable the system to create and update detailed maps, aiding in adaptive navigation. Dynamic path planning algorithms calculate optimal routes in real time, considering obstacles and changing environmental conditions [67]. Additionally, collaborative teleoperation strategies leverage human expertise for high-level decision making while allowing robots to execute tasks based on human guidance, ensuring adaptability and safe operation in complex and unpredictable environments. Human supervisors also play a vital role in remotely monitoring operations, providing contextual understanding and intervention capabilities when necessary [68]. In adapting teleoperation technology for telehealth scenarios, particularly in remote regions, several key strategies can be employed. Firstly, enhancing the robustness of internet connectivity through satellite-based solutions and low-bandwidth protocols can ensure real-time communication between remote robots and healthcare professionals [69]. Developing affordable and portable robotic platforms, customized for telehealth applications, can address cost and accessibility issues. Moreover, comprehensive training programs for local healthcare providers are crucial to ensure effective operation and maintenance of teleoperation equipment [70]. However, these implementations are not without challenges. Limited infrastructure, such as unstable internet connectivity and power supply, poses a significant hurdle. Finding cost-effective solutions, considering the financial constraints of remote regions, is crucial for the widespread adoption of teleoperation technology [71]. Addressing training gaps and ensuring cultural acceptance are equally vital. Ethical considerations, particularly related to patient consent and data security, require careful attention.