Josep Tornero

Fast Ego-motion Estimation with Multi-rate Fusion of Inertial and Vision

This paper presents a tracking system for ego-motion estimation which fuses vision and inertial measurements using EKF and UKF (Extended and Unscented Kalman Filters), where a comparison of their performance has been done. It also considers the multi-rate nature of the sensors: inertial sensing is sampled at a fast sampling frequency while the sampling frequency of vision is lower. the proposed approach uses a constant linear acceleration model and constant angular velocity model based on quaternions, which yields a non-linear model for states and a linear model in measurement equations. Results show that a significant improvement is obtained on the estimation when fusing both measurements with respect to just vision or just inertial measurements. It is also shown that the proposed system can estimate fast-motions even when vision system fails. Moreover, a study of the influence of the noise covariance is also performed, which aims to select their appropriate values at the tuning process. The setup is an end-effector mounted camera, which allow us to pre-define basic rotational and translational motions for validating results.

Brief paper: Dual-rate adaptive control

An operator, called the dual-rate transfer function, describing a dual-rate discretized continuous-time system is presented. It can be easily related to single-rate transfer functions of the same system, and its parameters can be experimentally estimated. Based on these models, two adaptive control strategies are outlined, and some results are illustrated by a simple example.

Multi-rate fusion with vision and inertial sensors

This work presents a multi-rate fusion model, which exploits the complimentary properties of visual and inertial sensors for egomotion estimation in applications such as robot navigation and augmented reality. The sampling of these two sensors is described with size-varying input and output equations without assumed synchronicity and periodicity of measurements. Data fusion is performed with two different multi-rate (MR) filter models, an extended (EKF) and an unscented Kalman filter (UKF). A complete dynamic model for the 6D-tracking task is given together with a method to calculate the dependencies of the covariance matrices. It is further shown that a centripetal acceleration model and the precise description of quaternion prediction for a constant velocity model highly improve the estimation error for rotary motions. The comparison demonstrates that the MR-UKF provides better estimation results at higher computational costs.

Analysis of multi-rate discrete equivalent of continuous controller

The paper is concerned with the analysis of multi-rate controllers, which update the controller output faster than the measurement sampling frequency by a factor of N. The controlled system is continuous, and the discrete time controller is obtained as its zero order hold equivalent. After deriving a set of equations necessary for analysis and design of multi-rate systems, the open loop characteristics of the multi-rate controller and the closed loop characteristics are examined. Several physical meanings can be derived from the formulation of the multi-rate controller.

Efficient distance calculation using the spherically-extended polytope (S-tope) model

An object representation scheme which allows fast Euclidean distance calculation is presented. The object model extends the polytope model by representing objects as the convex hull of a finite set of spheres. Objects with rounded surfaces can be represented with far fewer vertices than would be required with the polytope model. An algorithm for calculating distances between objects is developed which is linear in the total number of spheres specifying the two objects. To determine the efficiency of the distance computation algorithms, a program was written and tested using randomly generated objects with varying numbers of vertices.<<ETX>>

Hough transform for distance computation and collision avoidance

A new technique for collision detection based on the application of the Hough transform is presented in this paper. As a consequence of applying this technique, a method for computing the minimum translational distance (MTD) between two spherically extended polytopes is introduced. This distance algorithm is based on the Gilbert-Johnson-Keerthi (GJK) algorithm. Parameters returned by the MTD algorithm hold collision-free configurations that avoid a predicted collision.

Digital redesign of continuous time controller by multirate sampling and high order holds

This paper presents the digital redesign of continuous time controller when the measurement sampling period is relatively large and standard discretization methods are most likely not able to provide a suitable digital controller from either stability or performance point of view. An analysis tool is provided to improve the performance of digital control systems by the following two measures: 1) update the controller output N times faster than the measurement sampling frequency; and 2) utilize past sampled outputs to predict the evolution of the output error between two consecutive sampling instances. The analysis tool is developed by regarding the overall system as a multirate sampled data system. An illustrative example is given to show the utilization of the developed analysis tool.

Collision prediction and avoidance amidst moving objects for trajectory planning applications

A methodology for computing a collision-free trajectory for mobile robots amidst moving objects is presented. This planner is based on a technique for computing the minimum translational distance between two mobile objects. This distance is then used for predicting and avoiding a collision. The computation of this distance is based on the application of the GJK algorithm to a particular subset of the Minkowski difference set of the involved objects. This subset states the separation or penetration distance between two objects along their given motions. When a collision is predicted, a collision-free intermediate temporal-position is generated avoiding such a collision.

Trajectory Generation based on Rational Bezier Curves as Clothoids

This paper explains a fast overtaking algorithm for IVHS based on clothoidal trajectories. In spite of the fact that clothoidal trajectory generation requires complicated computation of Fresnel integrals, in this paper, an on-line clothoidal path is obtained just by scaling a general parametric curve. This is based on a general offline approximation of the Fresnel integrals into rational Bezier curves (RBC) which are later used in the generation of on-line clothoidal paths. In addition, in order to obtain a fast algorithm, a new methodology to approximate the Fresnel integrals into RBC is proposed. This approach guarantees that the resulting curve has the same behavior than the clothoid. In particular for overtaking maneuvers, a clothoidal path composed of two equal elementary paths is generated. Each one constructed joining two piecewise identical clothoids. A 3D simulation environment has been used for testing the trajectory generation algorithm described in the paper. As can be seen, the obstacle avoidance module generates free-collision intermediate positions which are reached by clothoidal paths.

SLAM based on Kalman filter for multi-rate fusion of laser and encoder measurements

In this paper, extended Kalman and unscented Kalman filters are developed for multi-rate systems in the context of the SLAM problem. These multi-rate filters have been extensively compared and tested with experimental data taken from a parking lot. Both multi-rate filters have improved the estimation with respect to the conventional single-rate Kalman filter. A performance index is introduced, showing that EKF gives better performance than UKF. In order to complete the SLAM solution, well-known techniques for feature extraction, data association and map building have been also implemented.