NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Comparing Alternate Modes of Teleoperation for Constrained Tasks

Teleoperation of heavy machinery in industry often requires operators to be in close proximity to the plant and issue commands on a per-actuator level using joystick input devices. However, this is non-intuitive and makes achieving desired job properties a challenging task requiring operators to complete extensive and costly training. Despite this, operator fatigue is common with implications for personal safety, project timeliness, cost, and quality. While full automation is not yet achievable due to unpredictability and the dynamic nature of the environment and task, shared control paradigms allow operators to issue high-level commands in an intuitive, task-informed control space while having the robot optimize for achieving desired job properties. In this paper, we compare a number of modes of teleoperation, exploring both the number of dimensions of the control input as well as the most intuitive control spaces. Our experimental evaluations of the performance metrics were based on quantifying the difficulty of tasks based on the well known Fitts' law as well as a measure of how well constraints affecting the task performance were met. Our experiments show that higher performance is achieved when humans submit commands in low-dimensional task spaces as opposed to joint space manipulations

Development and evaluation of mixed reality-enhanced robotic systems for intuitive tele-manipulation and telemanufacturing tasks in hazardous conditions

In recent years, with the rapid development of space exploration, deep-sea discovery, nuclear rehabilitation and management, and robotic-assisted medical devices, there is an urgent need for humans to interactively control robotic systems to perform increasingly precise remote operations. The value of medical telerobotic applications during the recent coronavirus pandemic has also been demonstrated and will grow in the future. This thesis investigates novel approaches to the development and evaluation of a mixed reality-enhanced telerobotic platform for intuitive remote teleoperation applications in dangerous and difficult working conditions, such as contaminated sites and undersea or extreme welding scenarios. This research aims to remove human workers from the harmful working environments by equipping complex robotic systems with human intelligence and command/control via intuitive and natural human-robot- interaction, including the implementation of MR techniques to improve the user's situational awareness, depth perception, and spatial cognition, which are fundamental to effective and efficient teleoperation. The proposed robotic mobile manipulation platform consists of a UR5 industrial manipulator, 3D-printed parallel gripper, and customized mobile base, which is envisaged to be controlled by non-skilled operators who are physically separated from the robot working space through an MR-based vision/motion mapping approach. The platform development process involved CAD/CAE/CAM and rapid prototyping techniques, such as 3D printing and laser cutting. Robot Operating System (ROS) and Unity 3D are employed in the developing process to enable the embedded system to intuitively control the robotic system and ensure the implementation of immersive and natural human-robot interactive teleoperation. This research presents an integrated motion/vision retargeting scheme based on a mixed reality subspace approach for intuitive and immersive telemanipulation. An imitation-based velocity- centric motion mapping is implemented via the MR subspace to accurately track operator hand movements for robot motion control, and enables spatial velocity-based control of the robot tool center point (TCP). The proposed system allows precise manipulation of end-effector position and orientation to readily adjust the corresponding velocity of maneuvering. A mixed reality-based multi-view merging framework for immersive and intuitive telemanipulation of a complex mobile manipulator with integrated 3D/2D vision is presented. The proposed 3D immersive telerobotic schemes provide the users with depth perception through the merging of multiple 3D/2D views of the remote environment via MR subspace. The mobile manipulator platform can be effectively controlled by non-skilled operators who are physically separated from the robot working space through a velocity-based imitative motion mapping approach. Finally, this thesis presents an integrated mixed reality and haptic feedback scheme for intuitive and immersive teleoperation of robotic welding systems. By incorporating MR technology, the user is fully immersed in a virtual operating space augmented by real-time visual feedback from the robot working space. The proposed mixed reality virtual fixture integration approach implements hybrid haptic constraints to guide the operator’s hand movements following the conical guidance to effectively align the welding torch for welding and constrain the welding operation within a collision-free area. Overall, this thesis presents a complete tele-robotic application space technology using mixed reality and immersive elements to effectively translate the operator into the robot’s space in an intuitive and natural manner. The results are thus a step forward in cost-effective and computationally effective human-robot interaction research and technologies. The system presented is readily extensible to a range of potential applications beyond the robotic tele- welding and tele-manipulation tasks used to demonstrate, optimise, and prove the concepts