The interaction between humans and robot teams is highly relevant in many application domains, for example in collaborative manufacturing, search and rescue, and logistics. It is well-known that humans and robots have complementary capabilities: Humans are excellent in reasoning and planning in unstructured environments, while robots are very good in performing tasks repetitively and precisely. In consequence, one of the key research questions is how to combine human and robot team decision making and task execution capabilities in order to exploit their complementary skills. From a controls perspective this question boils down to how control should be shared among them. This article surveys advances in humanrobot team interaction with special attention devoted to control sharing methodologies. Additionally, aspects affecting the control sharing design, such as human behavior modeling, level of autonomy and humanmachine interfaces are identified. Open problems and future research directions towards joint decision making and task execution in human-robot teams are discussed.

Abstract-The interaction of a single human with a team of cooperative robots, which collaboratively manipulate an object, poses a great challenge by means of the numerous possibilities of issuing commands to the team or providing appropriate feedback to the human. In this paper we propose a formationbased approach in order to avoid deformations of the object and to virtually couple the human to the formation. Here the human can be interpreted as a leader in a leader-follower formation with the robotic manipulators being the followers. The results of a controllability analysis in such a leader-follower formation suggest that it is beneficial to measure the state of the human (leader) by all physically cooperating manipulators (followers). The proposed approach is evaluated in a full-scale multi-robot cooperative manipulation experiment with humans.

Abstract-Robot teams require planning and adaptive capabilities in order to perform cooperative manipulation tasks in dynamic or unstructured environments. Since these capabilities are inherent to humans, it is suitable to consider humanrobot team teleoperation for cooperative manipulation where a single human collaborates with the robot team. In this paper, we present a subtask-based control approach which enables a simultaneous execution of two subtasks by the robot team, interacting with the object: trajectory tracking and formation preservation. Control inputs for both subtasks are provided by the human operator. The commands are projected onto the spaces of subtasks using a command mapping strategy. Analogously, measured interacting forces are projected onto the space of feedback signals, provided to the human via wearable fingertip haptic devices through a feedback mapping strategy. Experimental results validate the proposed approach.

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The interaction of robot teams and single human in teleoperation scenarios is beneficial in cooperative tasks, for example the manipulation of heavy and large objects in remote or dangerous environments. The main control challenge of the interaction is its asymmetry, arising because robot teams have a relatively high number of controllable degrees of freedom compared to the human operator. Therefore, we propose a control scheme that establishes the interaction on spaces of reduced dimensionality taking into account the low number of human command and feedback signals imposed by haptic devices. We evaluate the suitability of wearable haptic fingertip devices for multi-contact teleoperation in a user study. The results show that the proposed control approach is appropriate for human-robot team interaction and that the wearable haptic fingertip devices provide suitable assistance in cooperative manipulation tasks.