Editorial: Robotic Manipulation and Capture in Space
Bibliographic record
Abstract
Robotic Manipulation and Capture in SpaceΤasks such as inspecting, refueling, upgrading, repairing, or rescuing satellites, removing of orbital debris, and construction and maintenance of large orbital assets and infrastructures are important for maintenance of space infrastructure on orbit.Until now, all notable servicing tasks have been performed at Low Earth Orbit (LEO) by astronaut Extravehicular Activities (EVAs).However, these are risky, costly, slow, and sometimes unfeasible operations.EVAs can be replaced by robotic onorbit servicing (OOS), during which the tasks are performed by space manipulator systems (SMSs), also called chasers or servicers in the literature.These consist of a satellite base equipped with one or more robotic manipulators (arms) endowed with grappling devices on them, and driven by a vision system, which enables the capture of a target (client) satellite.An SMS also can be a large servicing manipulator mounted on a space facility.This Research Topic is focused on manipulation and capture on-orbit, and on aspects related to these activities.Therefore, it includes work related to the dynamics of rigid and flexible SMS, the associated contact dynamics, the identification methods for space systems, the pose and state sensing needed for monitoring and control, the motion planning methods for grasping a target, the feedback control methods during motion or interaction tasks, and the ground testing testbeds for such systems.The Research Topic includes five articles.In Estimation of Vibration Characteristics of a Space Manipulator from Air Bearing Supported Test Data, Li et al., study theoretically and experimentally an issue related to planar experimental testing testbeds, which use air bearings to support vertically a scaled SMS and create a zero gravity environment on the plane.The authors point out that air bearings influence the dynamics behavior of a scaled SMS, and therefore its apparent joints' stiffness and damping, its natural frequencies, and its vibration response.The authors present a set of procedures to remove the air bearings influence and identify the true equivalent joint stiffness and damping from the test data of a motor-braked system.The inertial properties are identified, and the equivalent joint stiffness and damping are determined using a genetic algorithm.The true vibration characteristics of the manipulator are estimated by removing the additional inertia caused by the air bearings.In On-Orbit Robotic Grasping of a Spent Rocket Stage: Grasp Stability Analysis and Experimental Results, Mavrakis et al., studied the grasping of a spent rocket stage, analyzed the grasp stability, and presented experimental results.A novel methodology for evaluating the stability of a spent rocket stage robotic grasp is presented based on the calculation of an Intrinsic Stiffness Matrix of a 2fingered grasp of an Apogee Kick Motor nozzle and a stability metric is defined as a function of the local contact curvature, material properties, applied force, and target mass.The stability metric is
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.038 | 0.025 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".