  Telemanipulation has become a promising technology that combines human
intelligence with robotic capabilities to perform tasks remotely. However, it
faces several challenges such as insufficient transparency, low immersion, and
limited feedback to the human operator. Moreover, the high cost of haptic
interfaces is a major limitation for the application of telemanipulation in
various fields, including elder care, where our research is focused. To address
these challenges, this paper proposes the usage of nonlinear model predictive
control for telemanipulation using low-cost virtual reality controllers,
including multiple control goals in the objective function. The framework
utilizes models for human input prediction and taskrelated models of the robot
and the environment. The proposed framework is validated on an UR5e robot arm
in the scenario of handling liquid without spilling. Further extensions of the
framework such as pouring assistance and collision avoidance can easily be
included.

Robotics;Systems and Control;Systems and Control