The increasing number of robots in everyday life will lead to more interactions between
robots and humans in the future. One interpersonal interaction that takes place in everyday
life is the handover of an object. This interaction is a fundamental task for more complex
collaborations between two actors. Consequently, in the future, this interaction will also be
performed in the context of everyday robot collaborations. To hand over the object, a physical
proximity between robot and human is necessary. This proximity can lead to rejection of the
interaction by users, as they are unable to perceive the robot or suspect dangers that might
be caused by the robot. Therefore, it is necessary to optimize the interaction based on user
acceptance and the user’s sense of safety.
Overall, three research goals are considered in this thesis. Besides investigating applicationspecific
adaptations and extensions for feasible and user-friendly robot-to-human handovers,
the focus is also on modeling and implementing anthropomorphic motions for robot-tohuman
handovers. The final goal is to evaluate the impact of anthropomorphic motion
models on user acceptance and the user’s sense of safety, in particular non-experts. For all
three objectives, these will be executed on different types of robots.
In order to address this goal, this thesis first presents a robot system that mimics handovers
between two humans. For this purpose, results and approaches of related studies are used
and adapted for the robotic system. The generation of handover configurations based on
specific context parameters is an open question that will be answered in this thesis. To this
end, a human-robot study is presented in which test subjects showed robots both appropriate
and inappropriate configurations. Based on the statistical results, a model for generating
the configurations is proposed. The user’s body size and posture, positioning, and handover
object are taken into account.
In the development of anthropomorphic motion models for the robot’s arm motion, the focus
is on three different conventional motion models. The two basic models are modeled in two
different configuration spaces. Thus, the first model is related to the Cartesian trajectory of
the end effector and the second model is related to the joint motions of specific joints of the
arm. Starting from the models, the recording of the baseline data is a challenge. For this,
two studies are shown in which two subjects pass an object to each other. In the process, two
different measurement techniques are used to collect the baseline data. Both models show
disadvantages in the application based on the given configuration space. As a consequence,
a third model is presented that combines the features and supposed advantages of both basic
models. During this research objective, different requirements of the models are evaluated
subjectively and objectively.
The influences of the developed robot system and the modelled movements regarding the
feeling of safety and user acceptance are investigated in a human-robot study. The evaluation
of the motion models shows that they have no significant influence on the users’ sense
of safety. This is applicable to non-experts as well as to experts. Other evaluation criteria,
such as intuitiveness, human similarity or user acceptance, are positively influenced by the
developed models, as they are mostly performing better compared to reference models. On
average, the combined model performed better than the anthropomorphic joint motion
model. The anthropomorphic motion model in Cartesian space does not reach an acceptable
quality level in the evaluation of human similarity. The evaluation of the other concepts of
the robotic system shows different results, where individual hypotheses are rejected against
expectations.
Further research in the field of robot-to-human handover could deal with the implementation
of the interactions in real scenarios. In this context, the kitchen is an exciting field of
application, since dangerous objects such as knives and hot utensils are handed over here.
These may require extensions to the robot system as well as alternative motion models.
