ZMP-Based Trajectory Generation for Bipedal Robots Using Quadratic Programming

In this chapter, the problem of trajectory generation for bipedal walking robots is considered. A number of modern techniques are discussed, and their limitations are shown. The chapter focuses on zero-moment point methods for trajectory generation, where the desired trajectory of that point can be used to allow the robot to keep vertical stability if followed, and presents an instrument to calculate the desired trajectory for the center of mass for the robot. The chapter presents an algorithm based on quadratic programming, with an introduction of a slack variable to make the problem feasible and a change of variables to improve the numeric properties of the resulting optimization problem. Modern optimization tools allow one to solve such problems in real time, making it a viable solution for trajectory planning for the walking robots. The chapter shows a few results from the numerical simulation made for the algorithm, demonstrating its properties.

Obstacle Classification Based on Laser Scanner for Intelligent Vehicle Systems

In the field of advanced driver-assistance and autonomous vehicle systems, understanding the surrounding vehicles plays a vital role to ensure a robust and safe navigation. To solve detection and classification problem, an obstacle classification strategy based on laser sensor is presented. Objects are classified according the geometry, distance range, reflectance, and disorder of each of the detected object. In order to define the best number of features that allows the algorithm to classify these objects, a feature analysis is performed. To do this, the set of features were divided into four groups based on the characteristic, distance, reflectance, and the entropy of the object. Finally, the classification task is performed using the support vector machines (SVM) and adaptive boosting (AdaBoost) algorithms. The evaluation indicates that the method proposes a feasible solution for intelligent vehicle applications, achieving a detection rate of 87.96% at 48.32 ms for the SVM and 98.19% at 79.18ms for the AdaBoost.

Digital Control Theory Application and Signal Processing in a Laser Scanning System Applied for Mobile Robotics

Positioning technologies are useful in a great number of applications, which are oriented for pick and place robots, manipulation of machine tools, especially on machines oriented for artificial vision and detection systems, such as vision-guided robotic systems and object existence in a limited environment. Due to the high demand of those applications, this chapter presents digital control theory application using a laser positioner, which obtains 3D coordinates in a defined field of view. Using the LM629N-8 motion controller, representing the main digital controller for the motion task of the laser positioner as an active element, which is analyzed via modeling and simulation using Matlab-Simulink. Additionally, this chapter focuses on some of the principal sources of uncertainties that exist in a laser scanning system and mainly on the receptive part of such system, which is driven by a brushed DC motor. The processed signal will be analyzed in different environmental conditions to analyze how it is affected by the instability characteristics of this main actuator.

Matrix Models of Cryptographic Transformations of Video Images Transmitted From Aerial-Mobile Robotic Systems

In this chapter, the authors consider the need and relevance of cryptographic transformation of images and video files that are transmitted from unmanned aircraft, airborne robots. The authors propose and consider new multifunctional matrix-algebraic models of cryptographic image transformations, the variety of matrix models, including block parametrical and matrix affine permutation ciphers. The authors show the advantages of the cryptographic models, such as adaptability to various formats, multi-functionality, ease of implementation on matrix parallel structures, interchangeability of iterative procedures and matrix exponentiation modulo, ease of selection, and control of cryptographic transformation parameters. The simulation results of the proposed algorithms and procedures for the direct and inverse transformation of images with the aim of masking them during transmission are demonstrated and discussed in this chapter. The authors evaluate the effectiveness and implementation reliability of matrix-algebraic models of cryptographic image transformations.

Application of the Principle of Rational Approximations for Measuring Dynamic Frequency Values Generated by an IMU

In most aerial vehicles, accurate information about critical parameters like position, velocity, and altitude is critical. In these systems, such information is acquired through an inertial measurement unit. Parameters like acceleration, velocity, and position are obtained after processing data from sensors; some of them are the accelerometers. In this case, the signal generated by the accelerometer has a frequency that depends from the acceleration experienced by the sensor. Since the time available for frequency estimation is critical in an aerial device, the frequency measurement algorithm is critical. This chapter proposes the principle of rational approximations for measuring the frequency from accelerometer-generated signals. In addition, the effect of different measurement parameters is shown, discussed, and evaluated.

Image Compression Technique Based on Some Principal Components Periodicity

In this chapter, the almost periodicity of the first principal components is used to carry out the reconstruction of images. First, the principal component analysis technique is applied to an image. Then, the periodicity of its principal components is analyzed. Next, this periodicity is used to build periodic vectors of the same length of the original principal components, and finally, these periodic vectors are used to reconstruct the original image. The proposed method was compared against the JPEG (Joint Photographic Experts Group) compression technique. The mean square error and peak signal-to-noise ratio were used to perform the above-mentioned comparison. The experimental results showed that the proposed method performed better than JPEG, when the original image was reconstructed using the principal components modified by periodicity.

Design of a Garbage Collection Robot

The Arduino is programmed to control the robot navigation. The Garbage Collection Robot is designed to collect solid waste at public places (schools, workplaces, and parks) and residential areas. The design of the robot is such that when it starts, it maneuvers as per programmed route. The Garbage Collector can sense by means of capacitive proximity sensors if the obstacle is living (for example, a human being) or non-living (for example, vehicle) and then gives appropriate warning signals like flashing light, hoot, or voice commands. The robot is equipped with vision capabilities in order for it to detect colors, namely green, red, yellow, blue, and black for organics, plastic, metal, paper, and glass, respectively. When the GCR sees a particular color code on garbage container, it picks up the bin, carries it in its carriage, then offloads it at a desired station to wait for recycling or final dumping.

Approaches to Development of Mechanical Design and Jumping Motion for a Wheeled Jumping Robot

This chapter is dedicated to tackling the issues related to the design and locomotion control of a hybrid wheeled jumping monitoring platform. The studied robot consists of a body mounted on a wheeled platform and of a jump acceleration module. An approach to making design decisions regarding the structure of the investigated robot is proposed. To select the kinematic structure of the robot, classifications of possible variants of hybrid jumping platforms and accelerating modules are presented. Methods for controlling the function of the accelerating modules and the analysis of their work is carried out. Various implementations of jumping motion are discussed; these implementations are characterized by different combinations of relative links movements during various stages of motion. Each of the proposed jump motion types requires the development of a control system, which is also discussed in this chapter.

Determination of Mobile Machine Wheel Dynamics

To determine the wheel dynamics of the mobile machine, a sensor has been developed, which consists of a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetometer. The sensor is connected to the microcontroller, which transmits the data received via the 2.4 GHz channel. It is attached coaxially to the center of the wheel. In the first step of processing data from the accelerometer and gyroscope, their values are corrected. The corrected acceleration signal and angular velocities are processed using a Butterworth filter. Madgwick filter determines the angles of orientation of the sensor in space. In the next step, the authors deduct the centrifugal component from accelerations. Further, the gravitational component is subtracted from the accelerations to get its real value. The wheel speed is obtained by integrating accelerations. Angular wheel speed and accelerations are processed with a Kalman filter. The outcomes of experimental studies of the proposed method and sensor to determine the wheel dynamics on the tractors with 4x4 wheel formula have been analyzed.