Model-Augmented Haptic Telemanipulation: Concept, Retrospective Overview, and Current Use Cases

Certain telerobotic applications, including telerobotics in space, pose particularly demanding challenges to both technology and humans. Traditional bilateral telemanipulation approaches often cannot be used in such applications due to technical and physical limitations such as long and varying delays, packet loss, and limited bandwidth, as well as high reliability, precision, and task duration requirements. In order to close this gap, we research model-augmented haptic telemanipulation (MATM) that uses two kinds of models: a remote model that enables shared autonomous functionality of the teleoperated robot, and a local model that aims to generate assistive augmented haptic feedback for the human operator. Several technological methods that form the backbone of the MATM approach have already been successfully demonstrated in accomplished telerobotic space missions. On this basis, we have applied our approach in more recent research to applications in the fields of orbital robotics, telesurgery, caregiving, and telenavigation. In the course of this work, we have advanced specific aspects of the approach that were of particular importance for each respective application, especially shared autonomy, and haptic augmentation. This overview paper discusses the MATM approach in detail, presents the latest research results of the various technologies encompassed within this approach, provides a retrospective of DLR's telerobotic space missions, demonstrates the broad application potential of MATM based on the aforementioned use cases, and outlines lessons learned and open challenges

Haptic Augmentation for Teleoperation through Virtual Grasping Points

Future challenges in teleoperation arise from a new complexity of tasks and from constraints in unstructured environments. In industrial applications as nuclear research facilities, the operator has to manipulate large objects whereas medical robotics requires extremely high precision. In the last decades, research optimized the transparency in teleoperation setups through accurate hardware, higher sampling rates and improved sensor technologies. To further enhance the performance in telemanipulation, the idea of haptic augmentation has been briefly introduced in [Panzirsch et al., IEEE ICRA, 2015, pp. 312-317]. Haptic augmentation provides supportive haptic cues to the operator that promise to ease the task execution and increase the control accuracy. Therefore, an additional haptic interface can be added into the control loop. The present paper introduces the stability analysis of the resulting multilateral framework and equations for multi-DoF coupling and time delay control. Furthermore, a detailed analysis via experiments and a user study is presented. The control structure is designed in the network representation and based on passive modules. Through this passivity-based modular design, a high adaptability to new tasks and setups is achieved. The results of the user study indicate that the bimanual control brings large benefits especially in improving rotational precision

A Stable and Transparent Framework for Adaptive Shared Control of Robots

In mixed-initiative haptic shared control of robots, humans and automatic control system work in parallel. The commands to the robot are a weighted sum of forces from these two agents. This thesis develops control methods to improve the force feedback performance for mixed-initiative shared teleoperation and to adapt the control authority between human and automatic control system in a stable manner even in the presence of communication delays. All methods are validated on real robotic hardware