Design of a Fuzzy Logic Controller for Skid Steer Mobile Robot

The control problem of four-wheeled skid steering mobile robots is quite challenging mainly because the skid steering system is an underactuated system and its mathematical model is highly uncertain. Skid steering configurations employ a differential-drive technique in which the wheels rotation is limited to around one axis and the lack of a steering wheel causes the navigation to be determined by the change of speed in either side of the robot for turning. Equal speed in both sides causes a straight-line motion. However, the implementation of the dead reckoning technique on skid-steer mobile robots will limit the precision of current robot’s position because skid-steer configuration intentionally relies on wheel slippage for normal operation and this possesses some difficulties when implementing motion control using the odometric system. The thesis describes the design of a fuzzy logic controller to compensate the dead reckoning limitation and implementation on a skid-steer mobile robot. The fuzzy controller has two inputs (angle error and distance), two outputs (translational and rotational speed) and 14 rules. These inputs are computed from the dead-reckoning method that is totally reliant on the odometry readings and data are fuzzified to be the inputs of the fuzzy controller. The outputs are the analogue voltages to the left and right motors, which drive the mobile robot. For simplicity, membership functions consisting of triangular and trapezoid shapes have been adopted. The membership functions of the fuzzy sets are chosen by trial-and-error based on experimentation. The heuristic rules control the orientation of the robot according to the information about the distances from the desired positions. The crisp output values from the fuzzy logic controller are decoded and fed into a decision module where the ratios of both sides motor voltage are determined for every smooth change in speed of the motors. To facilitate the implementation of control system, real-time execution is done in an indoor environment. Data acquisition is done in a LABVIEW and a MATLAB control algorithm is called in LABVIEW. A real mobile robot, PUTRABOT2 was used to conduct the experiment. Performance evaluation is observed from the accumulated error in orientation and its trajectory obtained after mapping the information gathered from the real world via odometry sensors. Few features such as the rise time, settling time and peak time of the output responses are analyzed. Comparisons are made between fuzzy logic and PD controllers. Comparative results among these two controllers indicate the superiority of the fuzzy approach with the ability to minimize the position and orientation errors. Moreover, the trajectory accuracy is very high and more reliable in the presence of unreliable odometry readings

Proceedings of the 4th field robot event 2006, Stuttgart/Hohenheim, Germany, 23-24th June 2006

Zeer uitgebreid verslag van het 4e Fieldrobotevent, dat gehouden werd op 23 en 24 juni 2006 in Stuttgart/Hohenhei

Path Tracking on Autonomous Vehicle for Severe Maneuvre

Autonomous vehicle consists self-learning process consists recognizing environment, real time localization, path planning and motion tracking control. Path tracking is an important aspect on autonomous vehicle. The main purpose path tracking is the autonomous vehicle have an ability to follow the predefined path with zero steady state error. The non-linearity of the vehicle dynamic cause some difficulties in path tracking problems. This paper proposes a path tracking control for autonomous vehicle. The controller consists of a relationship between lateral error, longitudinal velocity, the heading error and the reference yaw rate. In addition, the yaw rate controller developed based on the vehicle and tyre model. The effectiveness of the proposed controller is demonstrated by a simulation

Design, analysis and fabrication of an articulated mobile manipulator

The process involved in designing, fabricating and analysing a mobile robotic manipulator to carry out pick and place task in a dynamic and unknown environment has been explained here. The manipulator designed and fabricated has a 5 – axis articulated arm for pick and place application but also can be reconfigured to do other tasks. The manipulator is built with its driving or power means fitted at the bottom to distribute the load effectively and also make handling easier. The mobile platform employs a novel suspension system which helps in relatively distributing the load equally to all wheels regardless of the wheels position giving the mobile platform better control and stability. With reference to many available manipulators and mobile platforms in the market, a practical design is perceived using designing tools and a fully functional prototype is fabricated. The kinematic model determining the end effector’s position and orientation is analysed systematically and presented. Navigational controls are built using fuzzy logic and genetic algorithm with the help of the sensors’ information so that the robot can negotiate obstacle while carrying out various tasks in an unknown environment. The path tracking for pick-and-place application is the overall target of this industrial manipulator

Modelling, Simulation and Mechatronics Design of a Wireless Automatic Fire Fighting Surveillance Robot

The aim of this study is to design and develop an autonomous fire proof rescue robot. The robot is designed in such a way, that it can traverse through fire and hazardous situations. Further, it will sense and communicate information regarding these situations in real time with the server. The robot is fixed with multi-sensors and further, a driver circuit has been integrated for communication in these hazardous situations through Zigbee and a data acquisition system (DAQ). In mechanical design first, a 3D solid model is generated using Solid works software to understand the basic structure of robot which provides information regarding robotic platform, size and location of various components. The developed fire fighting robot is a predominately outdoor ground-based mobile robotic system with onboard subdual systems that can traverse autonomously in the hazardous environment. The robot is designed such that it can traverse into the fire and send information regarding the fire behaviour and also the images of the victim’s location by using a camera. Further, a mathematical model which describes the kinematics and dynamic behaviour of robot motion are done. V-REP is used to create the simulation of the robot in a fire simulated fire environment. Finally, for the path planning, various techniques are discussed such as V-REPs inbuilt path planning module, A*, Fuzzy logic and artificial potential fields

Preliminary laboratory test on navigation accuracy of an autonomous robot for measuring air quality in livestock buildings

Air quality in many poultry buildings is less than desirable. However, the measurement of concentrations of airborne pollutants in livestock buildings is generally quite difficult. To counter this, the development of an autonomous robot that could collect key environmental data continuously in livestock buildings was initiated. This research presents a specific part of the larger study that focused on the preliminary laboratory test for evaluating the navigation precision of the robot being developed under the different ground surface conditions and different localization algorithm according internal sensors. The construction of the robot was such that each wheel of the robot was driven by an independent DC motor with four odometers fixed on each motor. The inertial measurement unit (IMU) was rigidly fixed on the robot vehicle platform. The research focused on using the internal sensors to calculate the robot position (x, y, θ) through three different methods. The first method relied only on odometer dead reckoning (ODR), the second method was the combination of odometer and gyroscope data dead reckoning (OGDR) and the last method was based on Kalman filter data fusion algorithm (KFDF). A series of tests were completed to generate the robot’s trajectory and analyse the localisation accuracy. These tests were conducted on different types of surfaces and path profiles. The results proved that the ODR calculation of the position of the robot is inaccurate due to the cumulative errors and the large deviation of the heading angle estimate. However, improved use of the gyroscope data of the IMU sensor improved the accuracy of the robot heading angle estimate. The KFDF calculation resulted in a better heading angle estimate than the ODR or OGDR calculations. The ground type was also found to be an influencing factor of localisation errors

Trajectory Tracking Control of Skid-Steering Mobile Robots with Slip and Skid Compensation using Sliding-Mode Control and Deep Learning

Slip and skid compensation is crucial for mobile robots' navigation in outdoor environments and uneven terrains. In addition to the general slipping and skidding hazards for mobile robots in outdoor environments, slip and skid cause uncertainty for the trajectory tracking system and put the validity of stability analysis at risk. Despite research in this field, having a real-world feasible online slip and skid compensation is still challenging due to the complexity of wheel-terrain interaction in outdoor environments. This paper presents a novel trajectory tracking technique with real-world feasible online slip and skid compensation at the vehicle-level for skid-steering mobile robots in outdoor environments. The sliding mode control technique is utilized to design a robust trajectory tracking system to be able to consider the parameter uncertainty of this type of robot. Two previously developed deep learning models [1], [2] are integrated into the control feedback loop to estimate the robot's slipping and undesired skidding and feed the compensator in a real-time manner. The main advantages of the proposed technique are (1) considering two slip-related parameters rather than the conventional three slip parameters at the wheel-level, and (2) having an online real-world feasible slip and skid compensator to be able to reduce the tracking errors in unforeseen environments. The experimental results show that the proposed controller with the slip and skid compensator improves the performance of the trajectory tracking system by more than 27%