Recently, mirage pose estimation method was proposed for multi‐camera systems. Multi‐camera mirage analytically solves a system of linear equations for six pose parameters in O( n ) time. Mirage promises to execute in real time with high accuracy and shows lower rotational and translational errors compared to eight other well‐known perspective‐n‐points (PnP) methods. However, the simulated tests and real experiments showed that, in case of a single camera, the analytical system of linear equations is not solvable due to the reduced rank of the linear system that is obtained by the formulation. In this study, an important revision to mirage is proposed to support single camera systems properly. The results of simulations and real experiments demonstrate smaller pose estimation errors compared to a group of eight well‐known state‐of‐the‐art PnP methods.

Unmanned vehicles are autonomous robotic systems that are fully or partially controlled by an operator remotely from a station. In the last two decades, massive amount of advancements have been observed regarding unmanned vehicles for both military and civilian purposes. Today majority of these vehicles require human guidance even for basic missions, thus, minimising the human intervention on such systems is one of the emerging research topics. To serve this purpose, this study proposes a new trajectory tracking algorithm using Mirage pose estimation method. Mirage employs target pixel errors in two‐dimensional image plane and analytically calculates the robot's pose in three‐dimensional Euclidean space. Therefore, complex computations are not needed and undesirable Euclidean trajectories are avoided since the vehicle's pose is directly controlled. Both simulations and real experiments were performed to verify the effectiveness of the method. The results show that the proposed method is a feasible alternative for vision‐based Euclidean trajectory tracking with high accuracy and low complexity.

This paper presents a GPU based image registration algorithm that utilizes Hough Transform and Least Square Optimization to calculate the transformation between two images. In our approach, we calculate the transformation parameters of all possible combination solutions of matched feature points by exploiting parallel processing power of the GPU. We applied our algorithm on a variety of images including the problem of mosaic image generation. Experimental results show that our method is robust to the outliers (incorrect matches) and it can achieve very accurate registration (numeric and visual) results with much faster (up to 20 times) than CPU implementation.

Sliding-mode control laws for controlling multiple unmanned surface vessels in arbitrary formations are proposed. The presented formation control method uses local information as well as the planned gross motion of the formation to achieve mesh stability. A three-degree-of-freedom dynamic model has been used for the surface vessels. It is assumed that each vessel only has two actuators and the vessels are underactuated. Mesh stability and parameter uncertainty in the dynamic model and wave disturbance are considered in designing the controllers. It is shown that the internal dynamics of the underactuated system is also stable. The effectiveness and robustness of these control laws in the presence of parameter uncertainty in the dynamic model and wave disturbances and the mesh stability of the formation are demonstrated by computer simulation.

A new and efficient kinematic position and velocity solution scheme for spatial hyper-redundant manipulators is presented. The manipulator's arm has discrete links and universal joints. Backbone curve concepts and a modal approach are used to resolve the manipulator's redundancy. The effects of the mode shapes and the slope of the backbone curve at the starting point on the workspace are studied. It is shown that the usage of conventional mode shapes limits the workspace of the hyper-redundant arm. By introducing new mode shapes, an improved workspace is obtained. A simple and efficient recursive fitting method is introduced to avoid complications involved with solving systems of nonlinear algebraic equations. This method also guarantees the existence of solutions for the inverse kinematic problem at the velocity level. Velocity properties of the backbone curve are investigated and the inverse velocity propagation is solved for the spatial hyper-redundant arm. The velocity propagation scheme is recursive and is efficiently applicable to any number of links.