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The article presents a novel idea to construct a smooth navigation function for a wheeled robot based on grid-based search, that enables replanning in dynamic environments. Since the dynamic constraints of the robot are also considered, the navigation function is combined with the model predictive control (MPC) to guide the robot safely to the defined goal location. The main novelty of this work is the definition of this navigation function and its MPC application with guaranteed closed-loop convergence in finite time for a non-holonomic robot with speed and acceleration constraints. The navigation function consists of an interpolated potential function derived from the grid-based search and a term that guides the orientation of the robot on continuous gradients. The navigation function guarantees convergent trajectories to the desired goal, results in smooth motion between obstacles, has no local minima, and is computationally efficient. The proposed navigation is also suitable in dynamic environments, as confirmed by experiments with a Husky mobile robot. • Navigation function created from the grid-based search enables real-time replanning. • Continuous navigation function is obtained by interpolating discrete grid-based costs. • MPC-based navigation takes velocity and acceleration constraints into account. • MPC with the control sequence generation scheme allows fast on-line computation. • The navigation approach guarantees closed-loop convergence for unicycle-type robots. [ABSTRACT FROM AUTHOR]

Model-based predictive control approaches can be successfully applied to the trajectory tracking of wheeled mobile-robot applications if the process nonlinearity is considered, if real-time performance is achieved and if assumptions made in the control-law design are met when applied to a particular process. In this paper, continuous tracking-error model-based predictive control is presented. The controller’s optimal actions are obtained from an explicit solution of the optimization criteria, which enables fast real-time applications. Due to its design in continuous time, its usage is not limited to the uniform sampling restrictions of a host computer, as is usually the case in discrete time design. Therefore, better performance is obtained in applications with non-uniform sampling, which is natural in many situations due to imperfect sensors, mismatched clocks, nondeterministic control delays or because of the unknown time of the pre-processing. The controller-design parameters are insensitive to the sampling time period, which contributes to simpler applications and greater robustness of the controller. [ABSTRACT FROM AUTHOR]

Abstract: The strategy for the control of vehicle platooning is proposed and tested on different mobile robot platforms. The decentralized platooning is considered, i.e. a virtual train of vehicles where each vehicle is autonomous and decides on its motion based on its own perceptions. The following vehicle only has information about its distance and azimuth to the leading vehicle. Its position is determined using odometry. The reference position and the orientation of the following vehicle are determined by the estimated path of the leading vehicle in a parametric polynomial form. The parameters of the polynomials are determined using the least-squares method. This parametric reference path is also used to determine the feed-forward part and to suppress tracking errors by a feed-back part of the applied globally stable nonlinear control law. The results of the experiment and simulations demonstrate the applicability of the proposed algorithm for vehicle platoons. [ABSTRACT FROM AUTHOR]

Abstract: In this paper a new cooperative collision-avoidance method for multiple, nonholonomic robots based on Bernstein–Bézier curves is presented. The main contribution focuses on an optimal, cooperative, collision avoidance for a multi-robot system where the velocities and accelerations of the mobile robots are constrained and the start and the goal velocity are defined for each robot. The optimal path of each robot, from the start pose to the goal pose, is obtained by minimizing the penalty function, which takes into account the sum of all the path lengths subjected to the distances between the robots, which should be larger than the minimum distance defined as the safety distance, and subjected to the velocities and accelerations, which should be lower than the maximum allowed for each robot. The model-predictive trajectory tracking is used to drive the robots on the obtained reference paths. The results of the path planning, real experiments and some future work ideas are discussed. [Copyright &y& Elsevier]

In this paper, a model-predictive trajectory-tracking control applied to a mobile robot is presented. Linearized tracking-error dynamics is used to predict future system behavior and a control law is derived from a quadratic cost function penalizing the system tracking error and the control effort. Experimental results on a real mobile robot are presented and a comparison of the control obtained with that of a time-varying state-feedback controller is given. The proposed controller includes velocity and acceleration constraints to prevent the mobile robot from slipping and a Smith predictor is used to compensate for the vision-system dead-time. Some ideas for future work are also discussed. [Copyright &y& Elsevier]

In this paper some fundamentals and solutions to accompanying problems in vision system design for mobile robot tracking are presented. The main topics are correction of camera lens distortion and compensation of non-uniform illumination. Both correction methods contribute to vision system performance if implemented in the appropriate manner. Their applicability is demonstrated by applying them to vision for robot soccer. The lens correction method successfully corrects the distortion caused by the camera lens, thus achieving a more accurate and precise estimation of object position. The illumination compensation improves robustness to irregular and non-uniform illumination that is nearly always present in real conditions. [Copyright &y& Elsevier]

A robot path planning technique is proposed in the paper. It was developed for robots with differential drive, but with minor modifications it could be used for all types of nonholonomic robots. The path was planned in the way to minimise the time of reaching the end point in desired direction and with desired velocity, starting from the initial state described by the start point, initial direction and initial velocity. The limitation was the grip of the tires that results in the acceleration limits. The path is presented as a spline curve and was optimised by placing the control points through which the curve should pass. [Copyright &y& Elsevier]

This paper presents a new method for estimation of the homography up to similarity from observing a single point that is rotating at constant velocity around a single axis. The benefit of the proposed estimation approach is that it does not require measurement of the points in the world frame. The homography is estimated based on the known shape of the motion and in-image tracking of a single rotating point. The proposed method is compared to the two known methods: the direct approach based on point correspondences and a more recently proposed method based on conic properties. The main advantages of the proposed method are that it also estimates the angular velocity and that it requires only a single circle. The estimation is made directly from the measurements in the image. Because of the advantages of the proposed method over the other methods, the proposed method should be simple to implement for calibration of visually guided robotic systems. All the approaches were compared in the simulation environment in some non-ideal conditions and in the presence of disturbances, and a real experiment was made on a mobile robot. The experimental results confirm that the presented approach gives accurate results, even in some non-ideal conditions. [ABSTRACT FROM AUTHOR]