Showing papers by "Ivan Petrović published in 2014"

Real-time Approximation of Clothoids With Bounded Error for Path Planning Applications

Abstract: We present a method for real-time computation of clothoid coordinates that guarantees bounded approximation error over a wide range of clothoid parameters provided that the clothoid's orientation change and length areReal-time approximation bounded. It is shown that coordinates of clothoid with any parameters can be computed from those of a single clothoid (with fixed parameters), using appropriate geometrical transformations. A comprehensive analysis is given on how to determine a required set of clothoids and, based on this, how to sample a clothoid in a lookup table in order to achieve required approximation precision. The algorithm is computationally very efficient and therefore suitable for real-time path planning, as well as for other applications that benefit from fast clothoid computation.

Moving object detection, tracking and following using an omnidirectional camera on a mobile robot

Abstract: Equipping mobile robots with an omnidirectional camera is very advantageous in numerous applications as all information about the surrounding scene is stored in a single image frame. In the given context, the present paper is concerned with detection, tracking and following of a moving object with an omnidirectional camera. The camera calibration and image formation is based on the spherical unified projection model thus yielding a representation of the omnidirectional image on the unit sphere. Detection of moving objects is performed by calculating a sparse optical flow in the image and then lifting the flow vectors on the unit sphere where they are discriminated as dynamic or static by analytically calculating the distance of the terminal vector point to a great circle arc. The flow vectors are then clustered and the center of gravity is calculated to form the sensor measurement. Furthermore, the tracking is posed as a Bayesian estimation problem on the unit sphere and the solution based on the von Mises-Fisher distribution is utilized. Visual servoing is performed for the object following task where the control law calculation is based on the projection of a point on the unit sphere. Experimental results obtained by a camera with a fish-eye lens mounted on a differential drive mobile robot are presented and discussed.

Detection and tracking of dynamic objects using 3D laser range sensor on a mobile platform

Abstract: In this paper we present an algorithm for detection, extraction and tracking of moving objects using a 3D laser range sensor. First, ground extraction is performed using random sample consensus for model parameter estimation. Afterwards, to downsample the point cloud, a voxel grid filtering is executed and octree data structure is used. This data structure enables an efficient detection of differences between two consecutive point clouds, based on which clustering of dynamic parts of the cloud is performed. The obtained clusters are then expanded over the set of static voxels in order to cover entire objects. In order to account for ego-motion an iterative closest point registration technique with an initial transformation guess obtained by odometry of the platform is used. As the final step, we present a tracking algorithm based on joint probabilistic data association (JPDA) filter with variable process and measurement noise taking into account velocity and position of the tracked objects. However, JPDA filter assumes a constant and known number of objects in the scene, and therefore we use track management based on entropy. Experiments are performed using a setup consisting of a Velodyne HDL-32E mounted on top of a mobile platform in order to verify the developed algorithms.

Direction-only tracking of moving objects on the unit sphere via probabilistic data association

Abstract: Directional data can emerge in many scientific disciplines due to the nature of the observed phenomena or the working principles of a sensor. Such direction-only sensors can be used in applications with the aim of tracking multiple moving objects. One of the reasons why multiple moving object tracking can be challenging is because of the need to deal with the problem of pairing sensors measurements with tracked objects in the presence of clutter (the data association problem). In this paper we propose to approach the problem of multiple object tracking in clutter with direction-only data by setting it on the unit sphere, thus tracking the objects with a Bayesian estimator based on the von Mises-Fisher distribution and probabilistic data association. To achieve this goal we derive the probabilistic data association (PDA) filter and the joint probabilistic data association (JPDA) filter for the Bayesian von Mises-Fisher estimator on the unit sphere. The final PDA and JPDA filter equations are derived with respect to the Kullback-Leibler divergence by preserving the first moment of the spherical distribution. The performance of the proposed approach is demonstrated in experiments with synthetic data where moving object trajectories were simulated and noisy observations obtained along with the clutter simulated as a Poisson process on the unit sphere.

Bayesian Sensor Fusion Methods for Dynamic Object Tracking—A Comparative Study

Abstract: In this paper we study the problem of Bayesian sensor fusion for dynamic object tracking. The prospects of utilizing measurements from several sensors to infer about a system state are manyfold and...

Cooperative control of heterogeneous robotic systems

Abstract: Establishing a cooperative heterogeneous robotic system comprising autonomous vehicles operating in air, on ground and on/under water is a challenging task that can significantly contribute solving complex problems related to environmental monitoring (e.g. prediction, prevention and recovery from natural disasters) and security (e.g. border control, fight against terrorism). This paper presents a short overview of a project that involves cooperative control of heterogeneous robotic systems at the University of Zagreb Faculty of Electrical Engineering and Computing. An overview of the vehicles to be used in the heterogeneous systems is given and the envisioned scenario of neutralization of suspicious underwater objects is presented. Tasks of each vehicle are described and emphasis is placed on the actions and communication routes that are required to ensure cooperative behavior.