Exploring planet geology through force-feedback telemanipulation from orbit.

Current space exploration roadmaps envision exploring the surface geology of celestial bodies with robots for both scientific research and in situ resource utilization. In such unstructured, poorly lit, complex, and remote environments, automation is not always possible, and some tasks, such as geological sampling, require direct teleoperation aided by force-feedback (FF). The operator would be on an orbiting spacecraft, and poor bandwidth, high latency, and packet loss from orbit to ground mean that safe, stable, and transparent interaction is a substantial technical challenge. For this scenario, a control method was developed that ensures stability at high delay without reduction in speed or loss of positioning accuracy. At the same time, a new level of safety is achieved not only through FF itself but also through an intrinsic property of the approach preventing hard impacts. On the basis of this method, a tele-exploration scenario was simulated in the Analog-1 experiment with an astronaut on the International Space Station (ISS) using a 6-degree-of-freedom (DoF) FF capable haptic input device to control a mobile robot with manipulator on Earth to collect rock samples. The 6-DoF FF telemanipulation from space was performed at a round-trip communication delay constantly between 770 and 850 milliseconds and an average packet loss of 1.27%. This experiment showcases the feasibility of a complete space exploration scenario via haptic telemanipulation under spaceflight conditions. The results underline the benefits of this control method for safe and accurate interactions and of haptic feedback in general.

Planning Fail-Safe Trajectories for Space Robotic Arms.

A frequent concern for robot manipulators deployed in dangerous and hazardous environments for humans is the reliability of task executions in the event of a joint failure. A redundant robotic manipulator can be used to mitigate the risk and guarantee a post-failure task completion, which is critical for instance for space applications. This paper describes methods to analyze potential risks due to a joint failure, and introduces tools for fault-tolerant task design and path planning for robotic manipulators. The presented methods are based on off-line precomputed workspace models. The methods are general enough to cope with robots with any type of joint (revolute or prismatic) and any number of degrees of freedom, and might include arbitrarily shaped obstacles in the process, without resorting to simplified models. Application examples illustrate the potential of the approach.

A Digital Twin Approach for Contextual Assistance for Surgeons During Surgical Robotics Training.

Minimally invasive robotic surgery copes with some disadvantages for the surgeon of minimally invasive surgery while preserving the advantages for the patient. Most commercially available robotic systems are telemanipulated with haptic input devices. The exploitation of the haptics channel, e.g., by means of Virtual Fixtures, would allow for an individualized enhancement of surgical performance with contextual assistance. However, it remains an open field of research as it is non-trivial to estimate the task context itself during a surgery. In contrast, surgical training allows to abstract away from a real operation and thus makes it possible to model the task accurately. The presented approach exploits this fact to parameterize Virtual Fixtures during surgical training, proposing a Shared Control Parametrization Engine that retrieves procedural context information from a Digital Twin. This approach accelerates a proficient use of the robotic system for novice surgeons by augmenting the surgeon's performance through haptic assistance. With this our aim is to reduce the required skill level and cognitive load of a surgeon performing minimally invasive robotic surgery. A pilot study is performed on the DLR MiroSurge system to evaluate the presented approach. The participants are tasked with two benchmark scenarios of surgical training. The execution of the benchmark scenarios requires basic skills as pick, place and path following. The evaluation of the pilot study shows the promising trend that novel users profit from the haptic augmentation during training of certain tasks.

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.