# Enhancing Telexistence Control Through Assistive Manipulation and Haptic Feedback
###### Abstract  
The COVID-19 pandemic brought telepresence systems into the spotlight, yet manually controlling remote robots often proves ineffective for handling complex manipulation tasks. To tackle this issue, we present a machine learning-based assistive manipulation approach. This method identifies target objects and computes an inverse kinematic solution for grasping them. The system integrates the generated solution with the user's arm movements across varying inverse kinematic (IK) fusion levels. Given the importance of maintaining a sense of body ownership over the remote robot, we examine how haptic feedback and assistive functions influence ownership perception and task performance. Our findings indicate that incorporating assistance and haptic feedback significantly enhances the control of the robotic arm in telepresence environments, leading to improved precision and shorter task completion times. This research underscores the advantages of assistive manipulation techniques and haptic feedback in advancing telepresence technology. m msite equipped with a head unit and robotic arm. The system detects and localizes objects suitable for interaction at the remote site and sends these data to the local site. The local system then uses this information to compute an inverse kinematic solution tailored to the robot's configuration for grasping the target object. The system integrates the solution with the user's arm movements, with the blending level determining the extent of control assistance provided during operations. In this study, we present a telepresence system designed to support remote manipulation tasks with adjustable assistance levels. The system incorporates a local site featuring a cockpit setup with a head-mounted display, haptic glove, tracking system, and a remote site where users interact with objects through the robotic arm and observe the environment using the head unit. An inverse kinematic solver assigns varying weights to the user's hand movements and the target objective, enabling multiple assistance levels. We implement five distinct levels of assistance and demonstrate their application in controlling the robot effectively. Maintaining a high embodiment effect over the robot is crucial for telepresence systems [7,8]. We explore the impact of assistance and haptics on body ownership in a telepresence system through a user study. Embodiment refers to the user's perception of their physical presence in a remote or virtual body. In contrast, body ownership describes the sensation that the remote or virtual body is an extension of one's own. These factors are critical in telepresence systems as they directly influence the user's ability to perform tasks effectively and maintain a sense of control over remote operations. Our results offer valuable insight into designing telepresence systems that provide assistive manipulation without compromising body ownership. This work is the first to evaluate the impact of telemanipulation assistance within telepresence systems. Previous research employed a five-finger robot hand, presenting challenges for users with limited experience [9]. In this system, we replaced the five-finger hand with a parallel gripper to reduce the error from using the five-finger hand. Also, we fine-tuned the system to ensure stability and utilized a PC with better performance to ensure a higher frame rate for the HMD. Our study delves into the crucial aspect of maintaining high levels of embodiment and body ownership in telepresence systems, a topic that has been underscored in previous research [7,8]. Through a comprehensive user study, we have explored the impact of assistance and haptics on body ownership in telepresence systems, yielding valuable insights for the design of assistive manipulation without compromising body ownership.