Embedded system for motion control of an omnidirectional mobile robot

In this paper, an embedded system for motion control of omnidirectional mobile robots is presented. An omnidirectional mobile robot is a type of holonomic robots. It can move simultaneously and independently in translation and rotation. The RoboCup small-size league, a robotic soccer competition, is chosen as the research platform in this paper. The first part of this research is to design and implement an embedded system that can communicate with a remote server using a wireless link, and execute received commands. Second, a fuzzy-Tuned proportional-integral (PI) path planner and a related low-level controller are proposed to attain optimal input for driving a linear discrete dynamic model of the omnidirectional mobile robot. To fit the planning requirements and avoid slippage, velocity, and acceleration filters are also employed. In particular, low-level optimal controllers, such as a linear quadratic regulator (LQR) for multiple-input-multiple-output acceleration and deceleration of velocity are investigated, where an LQR controller is running on the robot with feedback from motor encoders or sensors. Simultaneously, a fuzzy adaptive PI is used as a high-level controller for position monitoring, where an appropriate vision system is used as a source of position feedback. A key contribution presented in this research is an improvement in the combined fuzzy-PI LQR controller over a traditional PI controller. Moreover, the efficiency of the proposed approach and PI controller are also discussed. Simulation and experimental evaluations are conducted with and without external disturbance. An optimal result to decrease the variances between the target trajectory and the actual output is delivered by the onboard regulator controller in this paper. The modeling and experimental results confirm the claim that utilizing the new approach in trajectory-planning controllers results in more precise motion of four-wheeled omnidirectional mobile robots. 2018 IEEE.Scopu

Design and Development of Fuzzy-PID Controller for Four-Wheeled Mobile Robotic Stability: A Case Study on the Uphill Road

Design intelligent control to maximize the performance of the Four-Wheeled Mobile Robot (FWMR) in case of uphill road problems. The variation of slope angle and load variation on the uphill road is applied to know the performance of the automatic control system on FWMR. The research is divided into three two covering, system identification, design system and simulation testing. The Rotary speed control system response with fuzzy-PID control method has a good performance by anticipating various tilt angle 5o. The system can through uphill with loads 11N with a steady time and fast travel time. The best travel time in the 5o tilt angle condition is 2 seconds with a 4m circuit length. This research concludes that fuzzy-PID control can be implemented and increase the dynamic response of the FWMR effectively on the uphill road problems

Enhancement of Motionability Based on Segregation of States for Holonomic Soccer Robot

One of the critical issues when navigating wheeled robot is the ability to move effectively. Omnidirectional robots might overcome these nonholonomic constraints. However, the motion planning and travel speed of the movement has been in continuous research. This study proposed segregation of states to improve the holonomic motion system with omnidirectional wheels, which is specially designed for soccer robots. The system used five separate defined states in order to move toward all directions by means of speed variations of each wheel, yielding both linear and curved trajectories. The controller received some parameter values from the main controller to generate robot motion according to the game algorithm. The results show that the robot is able to move in an omnidirectional way with the maximum linear speed of 3.2 m/s. The average error of movement direction is 4.3°, and the average error of facing direction is 4.8°. The shortest average time for a robot to make a rotational motion is 2.84 seconds without any displacement from the pivot point. Also, the robot can dribble the ball forward and backward successfully. In addition, the robot can change its facing direction while carrying the ball with a ball shift of less than 15 cm for 5 seconds. The results shows that state segregations improve the robots capability to conduct many variations of motions, while the ball-handling system is helpful to prevent the ball gets disengaged from the robot grip so the robot can dribble accordingly

PID Control Schematic Design for Omni-directional wheel mobile robot Cilacap State of Polytechnic

Omni-directional mobile robot (OMR) is a robot that can move in all directions with an additional wheel around the core wheel. This research presents a PID controller method at the OMR plant with the specific purpose of getting to the specified point. OMR uses three wheels with an angle difference of 120 degrees. The application of this method using MATLAB assistance from knowing the kinematics to the performance results from the application of the control method. The stages of this research are robot design, component selection, electrical design of the robot, determination of forward kinematic and reverse kinematic and determination of PID controller for positioning. Testing is done by determining the position and determining the point to be determined. Simulation time testing is when the state is at 3,6,9,12 and 15 seconds. The results of the simulation robot can follow the specified coordinates

Properties and environmental impact of the mosaic sludge incorporated into fired clay bricks

This paper presents fundamental information on the utlization of mosaic sludge waste from industrial mosaic activities into building materials. The study greatly benefits solid waste management and industries that produce waste with high heavy metal concentration by providing insights on ways to dispose waste by minimizing heavy metal leaching potential whilst providing a new formulation of low-cost and environmentally friendly building materials. Therefore, an alternative disposal method is to incorporate mosaic waste such as bodymill sludge (BS) and polishing sludge (PS) into fired clay brick. The bricks were incorporated with different percentages (0%, 1%, 5%, 10%, 20% and 30% by weight) of sludge waste and fired at 1050 �C (0.7 �C/min heating rates). The optimization results showed that the incorporation of up to 30% of mosaic sludge into fired clay bricks is capable of improving its physical and mechanical properties. Moreover, the incorporation of mosaic sludge waste into clay bricks has a positive effect on firing shrinkage, density and compressive strength. However, a decreased performance was reported for certain aspects. Hence, this study demonstrated that BS and PS can be alternative low-cost and environmentally friendly which can be used to improve the physical and mechanical properties of fired clay bricks

2D mapping using omni-directional mobile robot equipped with LiDAR

A room map in a robot environment is needed because it can facilitate localization, automatic navigation, and also object searching. In addition, when a room is difficult to reach, maps can provide information that is helpful to humans. In this study, an omni-directional mobile robot equipped with a LiDAR sensor has been developed for 2D mapping a room. The YDLiDAR X4 sensor is used as an indoor scanner. Raspberry Pi 3 B single board computer (SBC) is used to access LiDAR data and then send it to a computer wirelessly for processing into a map. This computer and SBC are integrated in robot operating system (ROS). The movement of the robot can use manual control or automatic navigation to explore the room. The Hector SLAM algorithm determines the position of the robot based on scan matching of the LiDAR data. The LiDAR data will be used to determine the obstacles encountered by the robot. These obstacles will be represented in occupancy grid mapping. The experimental results show that the robot is able to follow the wall using PID control. The robot can move automatically to construct maps of the actual room with an error rate of 4.59%

A vision-guided parallel parking system for a mobile robot using approximate policy iteration

Reinforcement Learning (RL) methods enable autonomous robots to learn skills from scratch by interacting with the environment. However, reinforcement learning can be very time consuming. This paper focuses on accelerating the reinforcement learning process on a mobile robot in an unknown environment. The presented algorithm is based on approximate policy iteration with a continuous state space and a fixed number of actions. The action-value function is represented by a weighted combination of basis functions. Furthermore, a complexity analysis is provided to show that the implemented approach is guaranteed to converge on an optimal policy with less computational time. A parallel parking task is selected for testing purposes. In the experiments, the efficiency of the proposed approach is demonstrated and analyzed through a set of simulated and real robot experiments, with comparison drawn from two well known algorithms (Dyna-Q and Q-learning)

Wheeled Mobile Robots: State of the Art Overview and Kinematic Comparison Among Three Omnidirectional Locomotion Strategies

In the last decades, mobile robotics has become a very interesting research topic in the feld of robotics, mainly because of population ageing and the recent pandemic emergency caused by Covid-19. Against this context, the paper presents an overview on wheeled mobile robot (WMR), which have a central role in nowadays scenario. In particular, the paper describes the most commonly adopted locomotion strategies, perception systems, control architectures and navigation approaches. After having analyzed the state of the art, this paper focuses on the kinematics of three omnidirectional platforms: a four mecanum wheels robot (4WD), a three omni wheel platform (3WD) and a two swerve-drive system (2SWD). Through a dimensionless approach, these three platforms are compared to understand how their mobility is afected by the wheel speed limitations that are present in every practical application. This original comparison has not been already presented by the literature and it can be used to improve our understanding of the kinematics of these mobile robots and to guide the selection of the most appropriate locomotion system according to the specifc application

Fuzzy-proportional-integral-derivative-based controller for object tracking in mobile robots

This paper aims at designing and implementing an intelligent controller for the orientation control of a two-wheeled mobile robot. The controller is designed in LabVIEW and based on analyzed image parameters from cameras. The image program calculates the distance and angle from the camera to the object. The fuzzy controller will get these parameters as crisp input data and send the calculated velocity as crisp output data to the right and left wheel motor for the robot tracking the target object. The results show that the controller gives a fast response and high reliability and quickly carries out data recovery from system faults. The system also works well in the uncertainties of process variables and without mathematical modeling