In this paper, a robust control solution for a satellite equipped with a robotic manipulator is presented. First, the dynamical model of the system is derived based on quaternions to describe the evolution of the attitude of the base satellite. Then, a non-singular terminal sliding mode controller that employs quaternions for attitude control, is proposed for concurrently handling all the degrees of freedom of the system. Moreover, an additional adaptive term is embedded in the controller to estimate the upper bounds of disturbances and uncertainties. The result is a resilient solution able to withstand unmodelled dynamics and interactions. Lyapunov theory is used to prove the stability of the controller and numerical simulations allow assessing performance and fuel efficiency.

The recent trend toward the development of IoT architectures has entailed the transformation of the standard camera networks into smart multi-device systems capable of acquiring, elaborating, and exchanging data and, often, dynamically adapting to the environment. Along this line, this work proposes a novel distributed solution that guarantees the real-time monitoring of 3D indoor structured areas and also the tracking of multiple targets, by employing a heterogeneous visual sensor network composed of both fixed and Pan-Tilt-Zoom (PTZ) cameras. The fulfillment of the twofold mentioned goal was ensured through the implementation of a distributed game-theory-based algorithm, aiming at optimizing the controllable parameters of the PTZ devices. The proposed solution is able to deal with the possible conflicting requirements of high tracking precision and maximum coverage of the surveilled area. Extensive numerical simulations in realistic scenarios validated the effectiveness of the outlined strategy.

In this paper, a novel online trajectory planning strategy for a satellite equipped with a robotic arm is presented. This problem is tackled using a nonlinear model predictive control approach, and the result is a flexible trajectory generation strategy that is able to adapt in real time to unseen scenarios and time-varying mission objectives. First, the kinematic and dynamic equations of the system are derived with particular attention with respect to representation singularities and computational efficiency. Then, the trajectory generation problem is written in the form of a constrained optimization problem taking into account actuators saturation and potential collisions with itself and the target object to be grasped. In the last part, multiple simulation scenarios are analyzed to verify the performance and effectiveness of the proposed solution.

In this work, a distributed indirect adaptive controller is designed for a group of robotic agents cooperatively manipulating a common payload. Uncertainty on the model of the manipulated object and the limited actuation capabilities of the single agents can significantly impact the overall behavior of the control system. An indirect adaptive control scheme is proposed in this article to address these shortcomings. In particular, model uncertainty and loss of effectiveness of the actuators are handled in a unifying fashion by an adaptive control architecture that preserves physical consistency of the estimated inertial parameters of the manipulated object, while simultaneously providing an antiwindup mechanism for the estimated inertial parameters in case of actuator saturation. In addition, a dynamic input allocation strategy is proposed to distribute the control effort among the agents in such a way that the intrinsic input redundancy of the overall setup is exploited for dynamic optimization of additional performance criteria, including optimization of the control efforts on each agent. The stability of the closed-loop system is proven theoretically, and the performance and robustness of the control system are validated by means of comparative simulations with respect to a baseline state-of-the-art controller.

The work considers the design of an indirect adaptive controller for a satellite equipped with a robotic arm manipulating an object. Uncertainty on the manipulated object can considerably impact the overall behavior of the system. In addition, the dynamics of the actuators of the base satellite are non-linear and can be affected by malfunctioning. Neglecting these two phenomena may lead to excessive control effort or degrade performance. An indirect adaptive control approach is pursued, which allows consideration of relevant features of the actuators dynamics, such as loss of effectiveness. Furthermore, an adaptive law that preserves the physical consistency of the inertial parameters of the various rigid bodies comprising the system is employed. The performance and robustness of the controller are first analyzed and then validated in simulation.