Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot

Velocity tracking is one of the important objectives of vehicle, machines and mobile robots. A two wheeled inverted pendulum (TWIP) is a class of mobile robot that is open loop unstable with high nonlinearities which makes it difficult to control its velocity because of its nature of pitch falling if left unattended. In this work, three soft computing techniques were proposed to track a desired velocity of the TWIP. Fuzzy Logic Control (FLC), Neural Network Inverse Model control (NN) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) were designed and simulated on the TWIP model. All the three controllers have shown practically good performance in tracking the desired speed and keeping the robot in upright position and ANFIS has shown slightly better performance than FLC, while NN consumes more energy

Backstepping Controller for Mobile Robot in Presence of Disturbances and Uncertainties

The objective of this work is to devise an effective control system for addressing the trajectory tracking challenge in nonholonomic mobile robots. Two primary control approaches, namely kinematic and dynamic strategies, are explored to achieve this goal. In the kinematic control domain, a backstepping controller (BSC) is introduced as the core element of the control system. The BSC is utilized to guide the mobile robot along the desired trajectory, leveraging the robot’s kinematic model. To address the limitations of the kinematic control approach, a dynamic control strategy is proposed, incorporating the dynamic parameters of the robot. This dynamic control ensures real-time control of the mobile robot. To ensure the stability of the control system, the Lyapunov stability theory is employed, providing a rigorous framework for analyzing and proving stability. Additionally, to optimize the performance of the control system, a genetic algorithm is employed to design an optimal control law. The effectiveness of the developed control approach is demonstrated through simulation results. These results showcase the enhanced performance and efficiency achieved by the proposed control strategies. Overall, this study presents a comprehensive and robust approach for trajectory tracking in nonholonomic mobile robots, combining kinematic and dynamic control strategies while ensuring stability and performance optimization

Efficient PID Controller based Hexapod Wall Following Robot

This paper presents a design of wall followingbehaviour for hexapod robot based on PID controller. PIDcontroller is proposed here because of its ability to controlmany cases of non-linear systems. In this case, we proposed aPID controller to improve the speed and stability of hexapodrobot movement while following the wall. In this paper, PIDcontroller is used to control the robot legs, by adjusting thevalue of swing angle during forward or backward movement tomaintain the distance between the robot and the wall. Theexperimental result was verified by implementing the proposedcontrol method into actual prototype of hexapod robot

Navigation of Automatic Vehicle using AI Techniques

In the field of mobile robot navigation have been studied as important task for the new generation of mobile robot i.e. Corobot. For this mobile robot navigation has been viewed for unknown environment. We consider the 4-wheeled vehicle (Corobot) for Path Planning, an autonomous robot and an obstacle and collision avoidance to be used in sensor based robot. We propose that the predefined distance from the robot to target and make the robot follow the target at this distance and improve the trajectory tracking characteristics. The robot will then navigate among these obstacles without hitting them and reach the specified goal point. For these goal achieving we use different techniques radial basis function and back-propagation algorithm under the study of neural network. In this Corobot a robotic arm are assembled and the kinematic analyses of Corobot arm and help of Phidget Control Panel a wheeled to be moved in both forward and reverse direction by 2-motor controller have to be done. Under kinematic analysis propose the relationships between the positions and orientation of the links of a manipulator. In these studies an artificial techniques and their control strategy are shown with potential applications in the fields of industry, security, defense, investigation, and others. Here finally, the simulation result using the webot neural network has been done and this result is compared with experimental data for different training pattern

An Analysis Review: Optimal Trajectory for 6-DOF-based Intelligent Controller in Biomedical Application

With technological advancements and the development of robots have begun to be utilized in numerous sectors, including industrial, agricultural, and medical. Optimizing the path planning of robot manipulators is a fundamental aspect of robot research with promising future prospects. The precise robot manipulator tracks can enhance the efficacy of a variety of robot duties, such as workshop operations, crop harvesting, and medical procedures, among others. Trajectory planning for robot manipulators is one of the fundamental robot technologies, and manipulator trajectory accuracy can be enhanced by the design of their controllers. However, the majority of controllers devised up to this point were incapable of effectively resolving the nonlinearity and uncertainty issues of high-degree freedom manipulators in order to overcome these issues and enhance the track performance of high-degree freedom manipulators. Developing practical path-planning algorithms to efficiently complete robot functions in autonomous robotics is critical. In addition, designing a collision-free path in conjunction with the physical limitations of the robot is a very challenging challenge due to the complex environment surrounding the dynamics and kinetics of robots with different degrees of freedom (DoF) and/or multiple arms. The advantages and disadvantages of current robot motion planning methods, incompleteness, scalability, safety, stability, smoothness, accuracy, optimization, and efficiency are examined in this paper

Obstacle Avoidance using Fuzzy Logic Controller on Wheeled Soccer Robot

The purpose of this study is to apply Fuzzy Logic Controller on a wheeled soccer robot to avoid the collision with other robots in the field. The robot equipped by an omnidirectional camera as a vision sensor, a mini-PC for the image processing device, a microcontroller to handle I/O system, and three wheel's omnidirectional mover system. Omni-camera produces four input-values, namely: X coordinate ball position, Y coordinate ball position, distance and angle from obstacle to the point of interest in the camera frame. These inputs processed by a mini-PC and then forward to a microcontroller to calculate the output using Fuzzy Logic Controller. The output variables are the movement rate of the robot in the X, and Y coordinate.  These outputs will be used by the kinematics controller to manage the speed of three Omni-wheels driven by 24 volts DC motors. The experiment shows a good result with the percentage of the success of the robot catching the ball is around 70% and 80% in avoiding the obstacle. In time performance, the soccer robot with Fuzzy Logic Controller is superior by 4.67 seconds compared to the robot without this method

Efficient PID Controller based Hexapod Wall Following Robot

This paper presents a design of wall following behaviour for hexapod robot based on PID controller. PID controller is proposed here because of its ability to control many cases of non-linear systems. In this case, we proposed a PID controller to improve the speed and stability of hexapod robot movement while following the wall. In this paper, PID controller is used to control the robot legs, by adjusting the value of swing angle during forward or backward movement to maintain the distance between the robot and the wall. The experimental result was verified by implementing the proposed control method into actual prototype of hexapod robot

Feedforward model with cascading proportional derivative active force control for an articulated arm mobile manipulator

This thesis presents an approach for controlling a mobile manipulator (MM) using a two degree of freedom (DOF) controller which essentially comprises a cascading proportional-derivative (CPD) control and feedforward active force control (FAFC). MM possesses both features of mobile platform and industrial arm manipulator. This has greatly improved the performance of MM with increased workspace capacity and better operation dexterity. The added mobility advantage to a MM, however, has increased the complexity of the MM dynamic system. A robust controller that can deal with the added complexity of the MM dynamic system was therefore needed. The AFC which can be considered as one of the novelties in the research creates a torque feedback within the dynamic system to allow for the compensation of sudden disturbances in the dynamic system. AFC also allows faster computational performance by using a fixed value of the estimated inertia matrix (IN) of the system. A feedforward of the dynamic system was also implemented to complement the IN for a better trajectory tracking performance. A localisation technique using Kalman filter (KF) was also incorporated into the CPD-FAFC scheme to solve some MM navigation problems. A simulation and experimental studies were performed to validate the effectiveness of the MM controller. Simulation was performed using a co-simulation technique which combined the simultaneous execution of the MSC Adams and MATLAB/Simulink software. The experimental study was carried out using a custom built MM experimental rig (MMer) which was developed based on the mechatronic approach. A comparative studies between the proposed CPD-FAFC with other type of controllers was also performed to further strengthen the outcome of the system. The experimental results affirmed the effectiveness of the proposed AFC-based controller and were in good agreement with the simulation counterpart, thereby verifying and validating the proposed research concepts and models