This paper focuses on the development and evaluation of a haptic enhanced virtual reality system which allows a human user to make physical handshakes with a virtual partner through a haptic interface. Multimodal feedback signals are designed to generate the illusion that a handshake with a robotic arm is a handshake with another human. Advanced controllers of the haptic interface are developed to respond to user behaviors online. Techniques to achieve online behavior generation are presented, such as a hidden-Markov-model approach to human interaction strategy estimation. Human-robot handshake experiments were carried out to evaluate the performance of the system. Two different approaches to haptic rendering were compared in experiments: a controller in basic mode with an embedded curve in the robot that disregards the human partner, and an interactive robot controller for online behavior generation. The two approaches were compared with the ground truth of another human driving the robot via teleoperation instead of the controller implementing a virtual partner. In the evaluation results, the human approach is rated to be most human-like, with the interactive controller following closely behind, followed by the controller in basic mode. This paper mainly concentrates on discussing the development of the haptic rendering algorithm for the handshaking system, its integration with visual and haptic cues, and reports about the results of subjective evaluation experiments that were carried out.

In the past, working spaces of humans and robots were strictly separated, but recent developments have sought to bring robots into closer interaction with humans. In this context, physical human–robot interaction represents a major challenge, as it is based on continuous bilateral information and energy exchanges which result in a mutual adaptation of the partners. To address the challenge of designing robot collaboration partners, making them as human-like as possible is an approach often adopted. In order to compare different implementations with each other, their degree of human-likeness on a continuous scale is required. So far, the human-likeness of haptic interaction partners has only been studied in the form of binary choices. In this paper, we first introduce methods that allow measuring the human-likeness of haptic interaction partners on a continuous scale. In doing so, two subjective rating methods are proposed and correlated with a task performance measure. To demonstrate the applicability and validity of the proposed measures, they are applied to a joint kinesthetic manipulation task and used to compare two different implementations of a haptic interaction partner: a feedforward model based on force replay, and a feedback model. This experiment demonstrates the use of the proposed measures in building a continuous human-likeness scale and the interpretation of the scale values achieved for formulating guidelines for future robot implementations.

One of the main objectives in telerobotics is the development of a telemanipulation system that allows a high task performance to be achieved by simultaneously providing a high degree of telepresence. Specific mechatronic design guidelines and appropriate control algorithms as well as augmented visual, auditory, and haptic feedback systems are typical approaches adopted in this context. This work aims at formulating new design guidelines by incorporating human factors in the development process and analyzing the effects of varied human movement control on task performance and on the feeling of telepresence. While it is well known that humans are able to coordinate and integrate multiple degrees of freedom (DOF), the focus of this work is on how humans utilize rotational degrees of freedom provided by a human-system interface and if and how varied human movement control affects task performance and the feeling of telepresence. For this analysis, a telemanipulation experiment with varying degrees of freedom has been conducted. The results indicate that providing the full range of movement, even though this range is not necessary to accomplish a task, has a beneficial effect on the feeling of telepresence and task performance in terms of measured interaction forces. Further, increasing visual depth cues provided to the human operator also had a positive effect.