This study investigates error handling intricacies in supervised autonomy orbit-to-ground teleoperation for space exploration robots, emphasizing scenarios with communication delays that render Earth-based ground control assistance unfeasible. In this setting, one major challenge lies in empowering the crew to independently mitigate robot errors that may occur as the robot plans its actions. To address this limitation of current supervised autonomy interfaces, we propose a third-person perspective and game design principles to improve environmental awareness in error situations. 16 experts with similar technical background as the target crew members tested the interface in a physical user study, while 42 people assessed it in an online study. We conclude that a third-person view brings significant improvements to mental workload, overall experience and the ability to identify and rectify planning errors.

The crewed exploration of Moon and Mars requires the construction and maintenance of infrastructure on the alien surfaces before a crew arrives. Robotic coworkers are envisioned to take over the physical labor required to set-up crew habitats, energy supplies, and return vehicles in the hazardous environment. Deploying these robots in such a remote location poses a challenge that requires autonomous robot capabilities in combination with effective Human Robot Interfaces (HRIs), which comply with the harsh conditions of deep space operations. An astronaut-robot teleoperation concept targeting these topics has been evaluated in DLR and ESA's METERON SUPVIS Justin experiment where astronauts on-board the International Space Station (ISS) commanded DLR's humanoid robot Rollin' Justin in a simulated Martian environment on Earth. This work extends on our previously presented approach to supervised autonomy. It examines the results of the two follow-up experiment sessions which investigated maintenance and assembly tasks in real-world scenarios. We discuss the use of our system in real space-to-ground deployment and analyze key performance metrics of the HRI and the feedback given by the astronauts.

Advances in exoskeleton technology now enable interacting with rigid objects in a virtual or remote environment using one's hand and fingertips. However, interaction with non-solid materials - such as liquids, sediments and regolith - alongside solids, can greatly extend the versatility of this technology. Rendering rigid objects adequately requires a control loop with high update rates, whereas fluid dynamics equations are computationally expensive. To accommodate this, the fluid dynamics can be simplified - particularly for fluids with high viscosity - resulting in a fast-to-calculate model to enabling haptic rendering of viscous fluids and rigid bodies simultaneously using DLR's Exodex Adam hand exoskeleton. Viscosity as a proprioceptive cue of fluids can be presented to the human through force feedback at multiple points on the human hand - fingers and palm - letting the user interact with a virtual environment in a more natural way and making the experience more immersive. We carry out two user studies to investigate the human perception abilities of virtual fluids rendered with simplified dynamics, and the discernability of different viscosity in virtual fluids compared real fluids. Results show that virtual media can give the user the perception of interacting with a fluid, even with simplified models, at a high update frequency. Furthermore, the material discernibility corresponds well to actual interaction with real viscous fluids. This shows great promise forward for haptic in-hand interaction in fluid and mixed media environments.

Accurate real-time estimation of the pose and configuration of the human hand attached to a dexterous haptic input device is crucial to improve the interaction possibilities for teleoperation and in virtual and augmented reality. In this paper, we present an approach to reconstruct the pose of the human hand and the joint angles of the fingers when wearing a novel fixed-base (grounded) hand exoskeleton. Using a kinematic model of the human hand built from MRI data, we can reconstruct the hand pose and joint angles without sensors on the human hand, from attachment points on the first three fingers and the palm. We test the accuracy of our approach using motion capture as a ground truth. This reconstruction can be used to determine contact geometry and force-feedback from virtual or remote objects in virtual reality or teleoperation.

As the human race expands its horizon toward a multiplanetary existence, infrastructures on the target planets have to be constructed and maintained to pave the way for humans. The support of robotic coworkers plays a key role in setting up habitats, energy supplies, and return vehicles, until the completion of such infrastructures in the hazardous planetary environment. The operation of these robots require capabilities including autonomy, communication, and human-robot interface design to meet the challenges of the harsh conditions in space deployment. This letter examines these topics through German Aerospace Center (DLR) and European Space Agency's METERON SUPVIS Justin space telerobotics experiments, during that astronauts on-board the International Space Station command DLR's humanoid robot Rollin' Justin to survey and maintain a simulated Martian solar farm on Earth. Based on the first experiments conducted on August 25, 2017, this letter discusses several astronaut-robot collaboration concepts in real space-to-ground deployment and provides preliminary insights for future manned Mars missions.