About this Research Topic
Space exploration and exploitation depend on tasks such as satellite servicing, refueling of space assets, orbital debris removal, and construction and maintenance of large orbital infrastructures. Until now, all notable servicing tasks have been performed at Low Earth Orbit (LEO) by Extravehicular Activities (EVAs). However, EVAs are by nature risky operations for astronauts requiring careful planning and preparation. Unfortunately, this increases mission costs drastically, making servicing missions too costly, or even unfeasible. For critical space assets located in the Geostationary Earth Orbit (GEO), EVA is not an option in the foreseeable future.
To execute tasks in orbit, being inaccessible to, or too dangerous for humans, on-orbit servicing (OOS) can be employed, with tasks to be performed by chaser or servicer space manipulator systems (SMSs), consisting of a spacecraft base fitted with one or more robotic manipulators. Depending upon the activation of the spacecraft, the SMS will operate in the free-flying (spacecraft actuators active), free-floating (spacecraft actuators inactive), or attitude-only control mode.
In OOS tasks, a number of challenges must be addressed, that render missions difficult and complex. These include the performance of a SMS during capture of a client or target, when its end-effector comes into physical contact with the client, aiming at client servicing or reentry/ de-orbiting. To obtain a desired response and controlled contact interactions, both suitable design approaches and effective control methods are required.
Design approaches include design for desired manipulator workspace, for minimum manipulator mass and volume taking into account servicer/client mass ratios and actuator constraints, for cooperative manipulation, for versatility regarding tasks, manipulator reconfigurability, collision avoidance, and more. Model-based Control is an approach important in space, due to the paramount importance of dynamics in orbit. Various forms of Impedance/Compliance Control have been proposed to mitigate the disturbances on spacecraft bases and minimize the strain on the manipulator. Impedance controllers for multi-arm servicers have been proposed also.
Usually, it is assumed that the properties of orbital man-made objects are known fully. However, uncertainties do exist in terms of both parameter variations and unmodeled disturbances, that can result in errors and significant risk. Approaches to deal with uncertainty include Robust Control, Adaptive Control, and Parameter Identification and their combinations, and are all important for the successful deployment of robots in orbit.
Ground-based test and validation of perception and control systems for SMSs performing 3D contact operations is another key challenge in the presence of gravity. A number of experimental methods exist, such as flat floors and hardware-in-the-loop approaches. Addressing method limitations and increasing their scope is a prerequisite in boosting our confidence in their performance in space.
• Robotic capture of an object in orbit (cooperative or not)
• Contact dynamics modeling in orbit
• Spacecraft actuation modes and planning of capture operations
• Control algorithms for the capture of space objects
• Kinematics and dynamics of SMS under operational constraints
• SMS design for minimum volume, mass, modularity, and versatility
• Uncertainty reduction via system identification or control methods
• Implementation of SMS control systems (bandwidth, sensors, available energy, etc.)
• Ground-based testing and validation methods for in orbit manipulation and capture
• Hardware-in-the-Loop (HIL) challenges
Image Credit: NASA
Keywords: Space Robotics, Robotic Capture, Contact Dynamics, Control for Capture in Orbit, Validation Methodologies
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