Comparison of Control Algorithms by Simulating Power Consumption of Differential Drive Mobile Robot Motion Control in Vineyard Row

The paper deals with comparing electricity power consumption of various control algorithms by simulating differential mobile robot motion control in a vineyard row. In field of autonomous mobile robotics, the quality of control is a crucial aspect. Besides the precision of control, the energy consumption for motion is becoming an increasingly demanding characteristic of a controller due to the increasing costs of fossil fuels and electricity. A simulation model of a differential drive mobile robot motion in a vineyard row was created, including robot dynamics for evaluating motion consumption, and there were implemented commonly used PID, Fuzzy, and LQ control algorithms, the task of which was to navigate the robot through the centre of vineyard row section by measuring distances from trellises on both robot sides. The comparison was carried out using Matlab software and the best results in terms of both power consumption and control accuracy were achieved by LQI controller. The designed model for navigating the robot through the vineyard row centre and optimized controllers were implemented in a real robot and tested under real conditions.

Design of an Embedded Energy Management System for Li–Po Batteries Based on a DCC-EKF Approach for Use in Mobile Robots

In mobile robotics, since no requirements have been defined regarding accuracy for Battery Management Systems (BMS), standard approaches such as Open Circuit Voltage (OCV) and Coulomb Counting (CC) are usually applied, mostly due to the fact that employing more complicated estimation algorithms requires higher computing power; thus, the most advanced BMS algorithms reported in the literature are developed and verified by laboratory experiments using PC-based software. The objective of this paper is to describe the design of an autonomous and versatile embedded system based on an 8-bit microcontroller, where a Dual Coulomb Counting Extended Kalman Filter (DCC-EKF) algorithm for State of Charge (SOC) estimation is implemented; the developed prototype meets most of the constraints for BMSs reported in the literature, with an energy efficiency of 94% and an error of SOC accuracy that varies between 2% and 8% based on low-cost components.

Algorithm and design improvements for indirect time of flight range imaging cameras

<p>This thesis describes the development of a compact and modularised indirect time of flight range imaging camera. These cameras commonly use the Amplitude Modulated Continuous Wave (AMCW) technique. For this technique, an entire scene is illuminated with light modulated at a high frequency. An image sensor is also modulated and the phase shift introduced between the two modulation signals, due to the transit time of the light reflecting off objects in the scene and returning to the camera, is used to measure the distance. The system constructed for this thesis is controlled by a Cyclone III FPGA and is capable of producing full field of view range images in real time with no additional computational resources. A PMD19K-2 sensor is used as the modulatable image sensor, and is capable of modulation frequencies up to 40 MHz. One significant issue identified with this range imaging technology is that the precision of the range measurements are often dependent on the properties of the object being measured. The dynamic range of the camera is therefore very important when imaging high contrast scenes. Variable Frame Rate Imaging is a novel technique that is developed as part of this thesis and is shown to have promise for addressing this issue. Traditional theory for indirect time of flight cameras is expanded to describe this technique and is experimentally verified. A comparison is made between this technique and traditional High Dynamic Range Imaging. Furthermore, this technique is extended to provide a constant precision measurement of a scene, regardless of the properties of the objects in the scene. It is shown that the replacement of the standard phase detection algorithm with a different algorithm can both reduce the linearity error in the phase measurements caused by harmonics in the correlation waveform and ameliorate axial motion error caused by relative motion of the camera and the object being measured. The new algorithm requires a trivial increase in computational power over the standard algorithm and can be implemented without any significant changes to the standard hardware used in indirect time of flight cameras. Finally, the complete system is evaluated in a number of real world scenarios. Applications in both 3D modelling and mobile robotics are demonstrated and tests are performed for a variety of scenarios including dynamic scenes using a Pioneer 2 robot.</p>

Algorithm and design improvements for indirect time of flight range imaging cameras

<p>This thesis describes the development of a compact and modularised indirect time of flight range imaging camera. These cameras commonly use the Amplitude Modulated Continuous Wave (AMCW) technique. For this technique, an entire scene is illuminated with light modulated at a high frequency. An image sensor is also modulated and the phase shift introduced between the two modulation signals, due to the transit time of the light reflecting off objects in the scene and returning to the camera, is used to measure the distance. The system constructed for this thesis is controlled by a Cyclone III FPGA and is capable of producing full field of view range images in real time with no additional computational resources. A PMD19K-2 sensor is used as the modulatable image sensor, and is capable of modulation frequencies up to 40 MHz. One significant issue identified with this range imaging technology is that the precision of the range measurements are often dependent on the properties of the object being measured. The dynamic range of the camera is therefore very important when imaging high contrast scenes. Variable Frame Rate Imaging is a novel technique that is developed as part of this thesis and is shown to have promise for addressing this issue. Traditional theory for indirect time of flight cameras is expanded to describe this technique and is experimentally verified. A comparison is made between this technique and traditional High Dynamic Range Imaging. Furthermore, this technique is extended to provide a constant precision measurement of a scene, regardless of the properties of the objects in the scene. It is shown that the replacement of the standard phase detection algorithm with a different algorithm can both reduce the linearity error in the phase measurements caused by harmonics in the correlation waveform and ameliorate axial motion error caused by relative motion of the camera and the object being measured. The new algorithm requires a trivial increase in computational power over the standard algorithm and can be implemented without any significant changes to the standard hardware used in indirect time of flight cameras. Finally, the complete system is evaluated in a number of real world scenarios. Applications in both 3D modelling and mobile robotics are demonstrated and tests are performed for a variety of scenarios including dynamic scenes using a Pioneer 2 robot.</p>

Multi-Level Control System for an Intelligent Robot that is Part of a Group

The article is devoted to the application of a group of robotic complexes for military purposes. The current state of control systems of single robotic complexes does not allow solving all the tasks assigned to the robot. The analysis of methods of controlling a group of robots in combat conditions is carried out. The necessity of using a multi-level control system for an intelligent combat robot is justified. A multi-level control system for an intelligent robot is proposed. Such a system assumes the possibility of controlling the robot in one of four modes: remote, supervisory, autonomous and group. Moreover, each robot, depending on the external conditions and its condition, can be in any control mode. The application of the technique is shown by the example of the movement of a group of robots with an interval along the front. The problem of the movement of slave robots behind the leader is considered. When forming the robot control algorithm, the method of finite automata was used. The algorithm controls the movement of the RTK in various operating modes: group control mode and autonomous movement mode. In the group control mode, the task is implemented: movement for the leader. For the state of "Movement in formation", an algorithm for forming the trajectory of the movement of guided robots was implemented. An algorithm for approximating the Bezier curve was used. It allows you to build a trajectory for the slave robot. On the basis of the obtained trajectory, the angular and linear velocity were calculated. In the autonomous control mode, two tasks are solved: moving to a given point and avoiding obstacles. Vector Field Histogram was used as an algorithm for detouring an obstacle, which determines the direction of movement without obstacles. The state of "Movement to a given point" is based on Pure Pursuit as a simple and reliable algorithm for solving such problems. A computer model of the movement of a group of robots was developed. The model is implemented in the MATLAB program using the Simulink and Mobile Robotics Simulation Toolbox libraries. Several different variants of the movement of the RTK group are modeled, which differ from each other in the initial location of the robots and the position of obstacles. The conducted computer simulation showed the efficiency and effectiveness of the proposed method of RTC control.

Comparison of Energy Prediction Algorithms for Differential and Skid-Steer Drive Mobile Robots on Different Ground Surfaces

A detailed literature analysis depicts that artificial neural networks are rarely used for the power consumption estimation in the mobile robotics field. Instead, researchers prefer to develop analytical models of investigated robots. This manuscript presents a comparison of mathematical models and non-complex artificial neural networks in energy prediction tasks for differential and skid-steer drive robots which move over various types of surfaces. The results show that both methods could be used interchangeably but AI methods are more universal, do not depend on the kinematic structure of a robot and are tolerant for designers not having a complex knowledge about the system.