Abstract

The dataset is related to user-centered unilateral telemanipulation systems for robotic manipulators, with a specific focus on the analysis and comparison of hybrid motion mapping strategies. It includes planar end-effector trajectory data recorded during the execution of a haptic manipulation task, where users interact with a robotic system through a haptic interface operating in a hybrid control mode that seamlessly alternates between direct control (position-to-position mapping) and rate control (position-to-velocity mapping). The dataset was acquired from experimental trials involving healthy users performing goal-oriented manipulation tasks in a simulated and real-time teleoperation environment. It is intended for the evaluation and comparison of trajectory-level performance metrics between different control strategies, enabling the assessment of stability, accuracy, and user interaction behavior during telemanipulation. Each data sample captures synchronized kinematic information from both direct and rate control modalities, along with task-related state indicators such as object attachment events. The data were collected within the framework of a unilateral teleoperation system developed to ensure intuitive, accessible, and effective control for operators with varying levels of robotics expertise. The experimental setup integrates a haptic interface with force feedback, a graphical user–machine interface providing real-time visualization, and a simulation environment based on MuJoCo for user training and task rehearsal. The dataset supports the analysis of hybrid control effectiveness in complex industrial-like scenarios, such as remote manipulation and programming by demonstration in weakly structured environments. The dataset is associated with the following publication: M. Tafuri, D. Chiaravalli, M. S. Gharamaleki, C. Melchiorri, G. Palli, and R. Meattini, “Experimental Evaluation of a User-Centered Unilateral Telemanipulation System for Training and Control in Robotic Industrial Scenarios,” Proceedings of the 2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W), 2025. https://doi.org/10.1109/DSN-W65791.2025.00046