This paper exploits the robotic capabilities of an orbital manipulator equipped with an actuation module at its end-effector to perform close-proximity robotic operations. The proposed control strategy enables repositioning the system's center-of-mass by reconfiguring the manipulator configuration and using the end-effector-mounted thrusting mechanism to achieve displacement. The key advantage of the proposed method is that the plume impingement due to thruster firing of the servicer satellite in close-proximity operations towards the client is mitigated. This is achieved by regulating the internal motion of the manipulator such that the thrust firing does not occur near the space asset. The effectiveness of the controller is verified through a multibody dynamic simulation of an orbital manipulator.

At first glance, a floating-base robotic system is a kinematic chain, and its equations of motion are described by the inertia-coupled dynamics of its shape and movable base. However, the dynamics embody an additional structure due to the momentum evolution, which acts as a velocity constraint. In prior works of robot dynamics, matrix transformations of the dynamics revealed a block-diagonal inertia. However, the structure of the transformed matrix of Coriolis/Centrifugal (CC) terms was not examined, and is the primary contribution of this article. To this end, we simplify the CC terms from robot dynamics and derive the analogous terms from geometric mechanics. Using this interdisciplinary link, we derive a two-part structure of the CC matrix, in which each partition is iteratively computed using a self-evident velocity dependency. Through this CC matrix, we reveal a commutative property, the velocity dependencies of the skew-symmetry property, the invariance of the shape dynamics to the basis of momentum, and the curvature as a matrix operator. Finally, we show the application of the proposed CC matrix structure through controller design and locomotion analysis.

This paper proposes a parameterization method to represent SO (3) over multiple turns. This method is called a memory-based parameterization, because the idea is to integrate the past trajectory of exponential coordinates. The parameterization is consistent in the sense that the true rotation matrix can be reconstructed by using the exponential map. As an application of the proposed method, a 6D impedance controller is designed with a radially unbounded potential function. Consequently, in contrast to the conventional methods, an arbitrarily large angular deflection can be accommodated, resulting in a more realistic impedance behavior. The proposed schemes are validated through simulations and experiments.

Multi-agent control of a robot using multiple controllers is vital in domains like shared control and reliable control. The strategy of assigning a varying priority (authority) to each agent controller, and commanding the robot using an authority-weighted sum of the forces produced by all the agents has been exploited in prior works. In this paper, firstly, we show that this strategy results in a loss of passivity, and we identify the passivity-disrupting scaling-related terms. Secondly, we propose a model independent method to ensure finite-gain L2stability of such a generic multi-agent robot control system with time-varying force scaling factors. Thirdly, the analysis is validated with simulations and hardware experiments.

In the present paper, we propose a novel system-driven adaptive shared control framework in which the autonomous system allocates the authority among the human operator and itself. Authority allocation is based on a metric derived from a Bayesian filter, which is being adapted online according to real measurements. In this way, time-varying measurement noise characteristics are incorporated. We present the stability proof for the proposed shared control architecture with adaptive authority allocation, which includes time delay in the communication channel between the operator and the robot. Furthermore, the proposed method is validated through experiments and a user-study evaluation. The obtained results indicate significant improvements in task execution compared with pure teleoperation.

In this paper, we propose three novel Hardware-in-the-loop simulation (HLS) methods for a fully-actuated orbital robot in the presence of external interactions using On-Ground Facility Manipulators (OGFM). In particular, a fixed-base and a vehicle-driven manipulator are considered in the analyses. The key idea is to describe the orbital robot's dynamics using the Lagrange-Poincaré(LP) equations, which reveal a block-diagonalized inertia. The resulting advantage is that noisy joint acceleration/torque measurements are avoided in the computation of the spacecraft motion due to manipulator interaction even while considering external forces. The proposed methods are a consequence of two facilitating theorems, which are proved herein. These theorems result in two actuation maps between the simulated orbital robot and the physical OGFM. The chief advantage of the proposed methods is physical consistency without level-set assumptions on the momentum map. We validate this through experiments on both types of OGFM in the presence of external forces. Finally, the effectiveness of our approach is validated through a HLS of a fully-actuated orbital robot while interacting with the environment.