This paper is concerned with the problem of leaderfollower formation control for a group of underactuated surface vessels (USV) with partially known control input functions. In the proposed scheme, the problem is formulated as an adaptive feedback control problem for a line-of- sight based formation configuration of a leader and a follower. To account for lineof- sight and bearing angle time-varying constraints, asymmetric Barrier Lyapunov Functions (ABLFs) are incorporated with the control design. Furthermore, in order to alleviate required velocity information on the leader a reconstruction module is designed to estimate the vector velocity of the leader. This reconstruction is accomplished in finite time with zero error which allows to inject accurate estimation to the formation controller. The controller is then developed under the framework of backstepping technique with the parametric uncertainties and the unknown gains being estimated by a novel structure identifer. The overall closed-loop system, is proved to be semi-globally uniformly ultimately bounded by Lyapunov stability theory. Furthermore we show under the proposed control scheme that the constraints requirement on the LOS range and bearing angle tracking errors are not violated during the formation process. Finally, the effectiveness and the robustness of the proposed strategy are exhibited through simulations.

In this paper, we address the design of a navigation control algorithm for the autonomous landing of a quadrotor on a moving mobile platform. The quadrotor's velocity is unknown, and we assume that it is equipped with an on-board downward-looking single camera for determining its position relative to the target. The proposed autonomous landing operation proceeds in three phases: the search phase, the homing phase, and the landing phase. To prepare for these phases, a safety sphere with a desired radius having the target position as its center is constructed along with a virtual target point that can move on its surface. During the docking procedure, the quadrotor is first commanded to reach the virtual target point; as it approaches this target point, a second stage is initiated to provide the quadrotor with more precise guidance to land safely on the mobile platform. The core design of the landing algorithm is proposed based on a concise adaptive tracking control scheme using backstepping and dynamic surface control. Simulations are carried out to validate the effectiveness of the proposed guidance landing control approach.

Searching and containing dynamic target like oil spillage in the ocean is a challenging task due to the natural time variance of the spread of the oil. The use of cooperative multi-marine vehicle systems in a cluttered environment for this purpose poses difficulties in sustaining formation pattern to pursue and contain the leakage. In this article, in order to provide realistic setup for the industrial applications of multi-marine vehicles systems, we present a novel approach for collision-free distributed formation control for a network of underactuated surface vessels (USVs). The proposed approach comprises two layers: A distributed coordination layer and a local fixed-time neural network control layer. In the first layer, formation leaders accomplish a specified formation configuration while tracking a desired trajectory from a tracking leader. The second control layer is to robustly drive the real USVs with parametric and nonparametric uncertainties to track their corresponding formation leaders. Because only parts of the formation leaders can acquire the states of the tracking leader, a distributed fixed-time estimator is proposed to obtain accurate estimations of the desired information for each USV in the network. Next, in order to effectively maneuver in cluttered environment, local path replanning-based repulsive potential function technique is proposed for each USV in the group formation to act on the formation leaders trajectories. Further, redesigned adaptive neural networks are integrated to compensate the model uncertainties. The stability of the proposed controller is verified by the Lyapunov direct method. Simulation studies of a hexagon formation are presented to illustrate the effectiveness of the proposed approach.

Connectivity and autonomy are considered two of the most promising technologies to improve mobility, fuel consumption, travel time, and traffic safety in the automated transportation industry. These benefits can be realized through vehicle platooning. A vehicle platoon is composed of a group of connected automated vehicles (CAVs) traveling together at consensual speed, following the leading vehicle (leader) while maintaining a prespecified inter-vehicle distance. This paper reviews the different existing control techniques associated with the transitional platoon maneuvers such as merge/split and lane change. Different longitudinal and lateral vehicle dynamics that are mainly used in the transitional platoon maneuvers are discussed. The most used control algorithms for both longitudinal and lateral control used for transitional platoon maneuvers are reviewed and the advantages and limitations of each control strategy are discussed. The most recent articles on platoon control maneuvers have been analyzed based on the proposed control algorithm, homogeneously or heterogeneously of platoon members, type of platoon maneuver, the aim of control problem, type of implementation, and used simulation tools. This paper also discusses different trajectory planning techniques used in lateral motion control and studies the most recent research related to trajectory planning for automated vehicles and summarizes them based on the used trajectory planning technique, platoon or/and lane change, the type of traffic, and the cost functions. Finally, this paper explores the open issues and directions for future research.

In this paper, a new robust adaptive controller is investigated to force an underactuated surface marine vessel to follow a predefined parameterised path at a desired speed, despite actuator saturation and the presence of model uncertainties as well as environmental disturbances induced by waves, wind and sea-currents. To ensure robustness of the path-following controller, time-varying constraint on the off-track error (i.e. the maximal distance from the ship to the reference path) is considered. To address the off-track error constraint the tan-barrier Lyapunov function is incorporated with the control scheme, where the idea of auxiliary design system introduced in Chen, Sam, and Ren (2011) is adopted and its states are used in combination with backstepping and Lyapunov synthesis to adaptive tracking control design with guaranteed stability. Furthermore, the command filters are adopted to implement physical constraints on the virtual control laws so that analytic differentiation of the virtual control laws is avoided. We show that the proposed robust adaptive control law is able to guarantee semi-global uniform ultimate bounded stability of the closed-loop system. Numerical simulations and experimental results are carried out to demonstrate the effectiveness of the proposed algorithm.

Being an emerging technology, robotic manipulation has encountered tremendous advancements due to technological developments starting from using sensors to artificial intelligence. Over the decades, robotic manipulation has advanced in terms of the versatility and flexibility of mobile robot platforms. Thus, robots are now capable of interacting with the world around them. To interact with the real world, robots require various sensory inputs from their surroundings, and the use of vision is rapidly increasing nowadays, as vision is unquestionably a rich source of information for a robotic system. In recent years, robotic manipulators have made significant progress towards achieving human-like abilities. There is still a large gap between human and robot dexterity, especially when it comes to executing complex and long-lasting manipulations. This paper comprehensively investigates the state-of-the-art development of vision-based robotic application, which includes the current state, components, and approaches used along with the algorithms with respect to the control and application of robots. Furthermore, a comprehensive analysis of those vision-based applied algorithms, their effectiveness, and their complexity has been enlightened here. To conclude, there is a discussion over the constraints while performing the research and potential solutions to develop a robust and accurate vision-based robot manipulation.