A lunar base reference mission for the phased implementation of bioregenerative life support system components

Previous design efforts of a cost effective and reliable regenerative life support system (RLSS) provided the foundation for the characterization of organisms or 'biological processors' in engineering terms and a methodology was developed for their integration into an engineered ecological LSS in order to minimize the mass flow imbalances between consumers and producers. These techniques for the design and the evaluation of bioregenerative LSS have now been integrated into a lunar base reference mission, emphasizing the phased implementation of components of such a BLSS. In parallel, a designers handbook was compiled from knowledge and experience gained during past design projects to aid in the design and planning of future space missions requiring advanced RLSS technologies. The lunar base reference mission addresses in particular the phased implementation and integration of BLS parts and includes the resulting infrastructure burdens and needs such as mass, power, volume, and structural requirements of the LSS. Also, operational aspects such as manpower requirements and the possible need and application of 'robotics' were addressed

Attention and Anticipation in Fast Visual-Inertial Navigation

We study a Visual-Inertial Navigation (VIN) problem in which a robot needs to estimate its state using an on-board camera and an inertial sensor, without any prior knowledge of the external environment. We consider the case in which the robot can allocate limited resources to VIN, due to tight computational constraints. Therefore, we answer the following question: under limited resources, what are the most relevant visual cues to maximize the performance of visual-inertial navigation? Our approach has four key ingredients. First, it is task-driven, in that the selection of the visual cues is guided by a metric quantifying the VIN performance. Second, it exploits the notion of anticipation, since it uses a simplified model for forward-simulation of robot dynamics, predicting the utility of a set of visual cues over a future time horizon. Third, it is efficient and easy to implement, since it leads to a greedy algorithm for the selection of the most relevant visual cues. Fourth, it provides formal performance guarantees: we leverage submodularity to prove that the greedy selection cannot be far from the optimal (combinatorial) selection. Simulations and real experiments on agile drones show that our approach ensures state-of-the-art VIN performance while maintaining a lean processing time. In the easy scenarios, our approach outperforms appearance-based feature selection in terms of localization errors. In the most challenging scenarios, it enables accurate visual-inertial navigation while appearance-based feature selection fails to track robot's motion during aggressive maneuvers.Comment: 20 pages, 7 figures, 2 table

Autonomous Systems, Robotics, and Computing Systems Capability Roadmap: NRC Dialogue

Contents include the following: Introduction. Process, Mission Drivers, Deliverables, and Interfaces. Autonomy. Crew-Centered and Remote Operations. Integrated Systems Health Management. Autonomous Vehicle Control. Autonomous Process Control. Robotics. Robotics for Solar System Exploration. Robotics for Lunar and Planetary Habitation. Robotics for In-Space Operations. Computing Systems. Conclusion

Development of On-Ground Hardware In Loop Simulation Facility for Space Robotics

Over a couple of decades, space junk has increased rapidly, which has caused significant threats to the LEO operation satellites. An Active Debris Removal $(ADR)$ concept continuously evolves for space junk removal. One of the ADR methods is Space Robotics, whose function is to chase, capture and de-orbit the space junk. This paper presents the development of an on-ground space robotics facility in the TCS Research for on-orbit servicing $(OOS)$ like refueling and debris capture experiments. A Hardware in Loop Simulation (HILS) system will be used for integrated system development, testing, and demonstration of on-orbit docking mechanisms. The HiLS test facility of TCS Research Lab will use two URs in which one UR is attached to the RG2 gripper, and the other is attached to a force-torque sensor and with a scaled mock-up model. The first UR5 will be mounted on a 7-axis linear rail and contain the docking probe. First, UR5 with a suitable gripper has to interface its control boxes. The grasping algorithm was run through the ROS interface line to demonstrate and validate the on-orbit operations. The manipulator will be mounted with LIDAR and a camera to visualize the mock-up model, find the target model's pose and rotational velocity estimation, and a gripper that will move relative to the target model. The other manipulator has the UR10 control, providing rotational and random motion to the mockup, enabling a dynamic simulator fed by force-torque data. The dynamic simulator is fed up with the orbit propagator, which will provide the orbiting environment to the target model. For the simulation of the docking and grasping of the target model, a linear rail of a 6m setup is still in the procurement process. Once reaching proximity, the grasping algorithm will be launched to capture the target model after reading the random motion of the mock-up model.Comment: 11 pages, 15 figures, Accepted at Small Satellite Conference 2023; Weekday Sessions: Orbital Debris, SSA & STM; Tuesday, 8th Aug 202

Development of On-Ground Hardware In Loop Simulation Facility for Space Robotics

Over a couple of decades, space junk has increased rapidly, which has caused significant threats to the LEO operation satellites. A mitigating measure should be taken to protect the LEO space environment. An Active Debris Removal (ADR) concept continuously evolves for space junk removal. One of the ADR methods is Space Robotics, whose function is to chase, capture and de-orbit the space junk. This paper presents the development of an on-ground space robotics facility in the TCS Research for on-orbit refueling and debris capture experiments. A Hardware-in-Loop Simulation (HILS) system will be used for integrated system development, testing, and demonstration. HILS is the most effective and vital system to test the on-orbit docking mechanism\u27s reliability, usability, and safety. The HiLS test facility of TCS Research Lab will use two Universal Robot(UR)5e and UR10 manipulators in which one manipulator is attached to the robotic-RG2 gripper, and the other is attached to a force-torque sensor named Hexa-E Onrobot and with a scaled mock-up satellite model. The first UR5 manipulator will be mounted on a 7-axis linear rail and contain the docking probe. First UR5 manipulator with the suitable gripper has to interface its control boxes. The grasping algorithm was run through the ROS interface line to demonstrate and validate the On-orbit and Debris removal operation. The manipulator will be mounted with LIDAR and a Real sense camera to visualize the mock-up model, find the target model\u27s pose and rotational velocity estimation, and a gripper that will move relative to the target model. The other manipulator has the UR10 control, providing rotational and random motion to the mock-up satellite, enabling a dynamic simulator fed by force-torque data. The dynamic simulator is fed up with the orbit propagator model SGP4, which will provide the orbiting environment to the target model. For the simulation of the docking and grasping of the target model, a 7-axis linear rail of a 6-meter setup is still in the procurement process. Once reaching proximity, the grasping algorithm will be launched to capture the target model after reading the random motion of the mock-up satellite model. The HILS system proposed in this paper helps develop on-orbit servicing (OOS) like repairing, upgrading, transporting, rescuing technologies, on-orbit refueling and berthing and debris removals