Hugo Jiménez-Hernández

LIDAR Velodyne HDL-64E Calibration Using Pattern Planes

This work describes a method for calibration of the Velodyne HDL-64E scanning LIDAR system. The principal contribution was expressed by a pattern calibration signature, the mathematical model and the numerical algorithm for computing the calibration parameters of the LIDAR. In this calibration pattern the main objective is to minimize systematic errors due to geometric calibration factor. It describes an algorithm for solution of the intrinsic and extrinsic parameters. Finally, its uncertainty was calculated from the standard deviation of calibration result errors.

Background Subtraction Approach Based on Independent Component Analysis

In this work, a new approach to background subtraction based on independent component analysis is presented. This approach assumes that background and foreground information are mixed in a given sequence of images. Then, foreground and background components are identified, if their probability density functions are separable from a mixed space. Afterwards, the components estimation process consists in calculating an unmixed matrix. The estimation of an unmixed matrix is based on a fast ICA algorithm, which is estimated as a Newton-Raphson maximization approach. Next, the motion components are represented by the mid-significant eigenvalues from the unmixed matrix. Finally, the results show the approach capabilities to detect efficiently motion in outdoors and indoors scenarios. The results show that the approach is robust to luminance conditions changes at scene.

A New Adaptive Self-Tuning Fourier Coefficients Algorithm for Periodic Torque Ripple Minimization in Permanent Magnet Synchronous Motors (PMSM)

Torque ripple occurs in Permanent Magnet Synchronous Motors (PMSMs) due to the non-sinusoidal flux density distribution around the air-gap and variable magnetic reluctance of the air-gap due to the stator slots distribution. These torque ripples change periodically with rotor position and are apparent as speed variations, which degrade the PMSM drive performance, particularly at low speeds, because of low inertial filtering. In this paper, a new self-tuning algorithm is developed for determining the Fourier Series Controller coefficients with the aim of reducing the torque ripple in a PMSM, thus allowing for a smoother operation. This algorithm adjusts the controller parameters based on the components harmonic distortion in time domain of the compensation signal. Experimental evaluation is performed on a DSP-controlled PMSM evaluation platform. Test results obtained validate the effectiveness of the proposed self-tuning algorithm, with the Fourier series expansion scheme, in reducing the torque ripple.

Detecting abnormal vehicular dynamics at intersections based on an unsupervised learning approach and a stochastic model.

This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems.

A multiple camera calibration and point cloud fusion tool for Kinect V2

Abstract This paper introduces a tool for calibrating multiple Kinect V2 sensors. To achieve the calibration, at least three acquisitions are needed from each camera. The method uses the Kinects coordinate mapping capabilities between the sensors to register data between camera, depth, and color spaces. The method uses a novel approach where it obtains multiple 3D points matches between adjacent sensors, and use them to estimating the camera parameters. Once the cameras are calibrated, the tool can perform point cloud fusion transforming all the 3D points to a single reference. We tested the system with a network of four Kinect V2 sensors and present calibration results. The tool is implemented in MATLAB using the Kinect for Windows SDK 2.0.

Higher order sliding mode based impedance control for dual-user bilateral teleoperation under unknown constant time delay

This paper presents a dual-user teleoperation scheme to perform a collaborative task using n-DOF nonlinear manipulators as masters and slave. Impedance controllers for the manipulators are implemented in order to achieve a desired dynamic behavior depending on the users necessities. Furthermore, a sliding mode controller is introduced to cope with the time delay in the communication channels and the uncertainty in the slave. Since the slave teleoperator is in contact with a rigid environment, the slave controller requires a free of chattering control strategy, which makes first order sliding mode teleoperation control unsuitable. Then a higher order sliding mode based impedance controller is proposed to guarantee robust impedance tracking under constant, but unknown time delay. Therefore, a position scaling factor is incorporated to deal with the different workspaces among masters and slave. The validity of the proposed control scheme is demonstrated via experimentation on a 3-DOF dual-user teleoperation system. While the haptic devices Phantom Premium 1.0A and a Phantom Omni are used as masters, a virtual industrial manipulator Catalyst-5 is used as slave. The dual-user system is tested not only in presence of constant unknown time delay in each of the communication channels but also in free and constrained motion regime.

Design and Construction of a Didactic 3-DOF Parallel Links Robot Station with a 1-DOF Gripper

The main objective of the construction of a robot station presented in this article is to allow the students to design andproduce a feasible-to-build mechatronic device using robust, low-cost components. It is a tool for students to gainexperience integrating different mechatronic fields of knowledge, as well as practicing the procedures needed tosuccessfully accomplish their own design. The project starts by describing the target requirements to be achieved bythe prototype robot, these requirements will serve as the guideline for the design and further manufacture and testingof the system. The sub-assemblies of the mechanism are analyzed, main technical areas and their processes arediscussed individually emphasizing the methods and materials used, then results are presented along with somepractical recommendations to extend the scope of the project and improve the performance of the prototype robot. Ithas been especially important to maintain the didactical approach and design the platform with affordable componentsthat can be easily obtained; this is also true for the tools and software used. The article is also intended to introducethe student to industrial design methodology, allowing for different manufacturing processes and robot architectures tobe incorporated for the specific scope of the project and the available tools and facilities.

A Probabilistic Measure of Circularity

The circle is a useful morphological structure: in many situations, the importance is focused on the measuring of the similarity of a perfect circle against the object of interest. Traditionally, the well-known geometrical structures are employed as useful geometrical descriptors, but an adequate characterization and recognition are deeply affected by scenarios and physical limitations (such as resolution and noise acquisition, among others). Hence, this work proposes a new circularity measure which offers several advantages: it is not affected by the overlapping, incompleteness of borders, invariance of the resolution, or accuracy of the border detection. The propounded approach deals with the problem as a stochastic non-parametric task; the maximization of the likelihood of the evidence is used to discover the true border of the data that represent the circle. In order to validate the effectiveness of our proposal, we compared it with two recently effective measures: the mean roundness and the radius ratio.

A double layer background model to detect unusual events

A double layer background representation to detect novelty in image sequences is shown. The model is capable of handling non-stationary scenarios, such as vehicle intersections. In the first layer, an adaptive pixel appearance background model is computed. Its subtraction with respect to the current image results in a blob description of moving objects. In the second layer, motion direction analysis is performed by a Mixture of Gaussians on the blobs. We have used both layers for representing the usual space of activities and for detecting unusual activity. Our experiments clearly showed that the proposed scheme is able to detect activities such as vehicles running on red light or making forbidden turns.

Transparent Higher Order Sliding Mode Control for Nonlinear Master-slave Systems without Velocity Measurement

Transparency has been a major objective in bilateral teleoperation systems, even in the absence of time delay induced by the communication channel, since a high degree of transparency would allow humans to drive the remote teleoperator as if he or she were directly interacting with the remote environment, with the remote teleoperator as a physical and sensorial extension of the operator. When fast convergence of position and force tracking errors are ensured by the control system, then complete transparency is obtained, which would ideally guarantee humans to be tightly kinaesthetically coupled. In this paper a model-free Cartesian second order sliding mode (SOSM) PD control scheme for nonlinear master-slave systems is presented. The proposed scheme does not rely on velocity measurements and attains very fast convergence of position trajectories, with bounded tracking of force trajectories, rendering a high degree of transparency with lesser knowledge of the system. The degree of transparency can easily be improved by tuning a feedback gain in the force loop. A unique energy storage function is introduced; such that a similar Cartesian-based controller is implemented in the master and slave sides. The resulting properties of the Cartesian control structure allows the human operator to input directly Cartesian variables, which makes clearer the kinaesthetic coupling, thus the proposed controller becomes a suitable candidate for practical implementation. The performance of the proposed scheme is evaluated in a semi-experimental setup.