A driver model with supervision aspects

Human driver compensatory reactions -- Driver intelligence and Path Tracking (supervision) -- From human decision making to design of control level -- Vehicle models -- History of driver models -- Controller for car-like mobile robots -- Control problems of vehicle cartesian coordiantes -- Independent speed control with geometric lateral-offset tracking -- Kinematics dynamics and control of a car-like mobile robot -- Looking ahead path tracking of a car-like mobile robot -- Geometric lateral-offset tracking and speed control of a car-like mobile robot -- Equations of motion of a car-like robot using autolev programming

Vision-based Global Path Planning and Trajectory Generation for Robotic Applications in Hazardous Environments

The aim of this study is to find an efficient global path planning algorithm and trajectory generation method using a vision system. Path planning is part of the more generic navigation function of mobile robots that consists of establishing an obstacle-free path, starting from the initial pose to the target pose in the robot workspace.In this thesis, special emphasis is placed on robotic applications in industrial and scientific infrastructure environments that are hazardous and inaccessible to humans, such as nuclear power plants and ITER1 and CERN2 LHC3 tunnel. Nuclear radiation can cause deadly damage to the human body, but we have to depend on nuclear energy to meet our great demands for energy resources. Therefore, the research and development of automatic transfer robots and manipulations under nuclear environment are regarded as a key technology by many countries in the world. Robotic applications in radiation environments minimize the danger of radiation exposure to humans. However, the robots themselves are also vulnerable to radiation. Mobility and maneuverability in such environments are essential to task success. Therefore, an efficient obstacle-free path and trajectory generation method are necessary for finding a safe path with maximum bounded velocities in radiation environments. High degree of freedom manipulators and maneuverable mobile robots with steerable wheels, such as non-holonomic omni-directional mobile robots make them suitable for inspection and maintenance tasks where the camera is the only source of visual feedback.In this thesis, a novel vision-based path planning method is presented by utilizing the artificial potential field, the visual servoing concepts and the CAD-based recognition method to deal with the problem of path and trajectory planning. Unlike the majority of conventional trajectory planning methods that consider a robot as only one point, the entire shape of a mobile robot is considered by taking into account all of the robot’s desired points to avoid obstacles. The vision-based algorithm generates synchronized trajectories for all of the wheels on omni-directional mobile robot. It provides the robot’s kinematic variables to plan maximum allowable velocities so that at least one of the actuators is always working at maximum velocity. The advantage of generated synchronized trajectories is to avoid slippage and misalignment in translation and rotation movement. The proposed method is further developed to propose a new vision-based path coordination method for multiple mobile robots with independently steerable wheels to avoid mutual collisions as well as stationary obstacles. The results of this research have been published to propose a new solution for path and trajectory generation in hazardous and inaccessible to human environments where the one camera is the only source of visual feedback

MPC-based path following control of an omnidirectional mobile robot with consideration of robot constraints

In this paper, the path following problem of an omnidirectional mobile robot (OMR) has been studied. Unlike nonholonomic mobile robots, translational and rotational movements of OMRs can be controlled simultaneously and independently. However the constraints of translational and rotational velocities are coupled through the OMR's orientation angle. Therefore, a combination of a virtual-vehicle concept and a model predictive control (MPC) strategy is proposed in this work to handle both robot constraints and the path following problem. Our proposed control scheme allows the OMR to follow the reference path successfully and safely, as illustrated in simulation experiments. The forward velocity is close to the desired one and the desired orientation angle is achieved at a given point on the path, while the robot's wheel velocities are maintained within boundaries

Control of Outdoor Robots at Higher Speeds on Challenging Terrain

This thesis studies the motion control of wheeled mobile robots. Its focus is set on high speed control on challenging terrain. Additionally, it deals with the general problem of path following, as well as path planning and obstacle avoidance in difficult conditions. First, it proposes a heuristic longitudinal control for any wheeled mobile robot, and evaluates it on different kinematic configurations and in different conditions, including laboratory experiments and participation in a robotic competition. Being the focus of the thesis, high speed control on uneven terrain is thoroughly studied, and a novel control law is proposed, based on a new model representation of skid-steered vehicles, and comprising of nonlinear lateral and longitudinal control. The lateral control part is based on the Lyapunov theory, and the convergence of the vehicle to the geometric reference path is proven. The longitudinal control is designed for high speeds, taking actuator saturation and the vehicle properties into account. The complete solution is experimentally tested on two different vehicles on several different terrain types, reaching the speeds of ca. 6 m/s, and compared against two state-of-the-art algorithms. Furthermore, a novel path planning and obstacle avoidance system is proposed, together with an extension of the proposed high speed control, which builds up a navigation system capable of autonomous outdoor person following. This system is experimentally compared against two classical obstacle avoidance methods, and evaluated by following a human jogger in outdoor environments, with both static and dynamic obstacles. All the proposed methods, together with various different state-of-the-art control approaches, are unified into one framework. The proposed framework can be used to control any wheeled mobile robot, both indoors and outdoors, at low or high speeds, avoiding all the obstacles on the way. The entire work is released as open-source software

Control of Real Mobile Robot Using Artificial Intelligence Technique

An eventual objective of mobile robotics research is to bestow the robot with high cerebral skill, of which navigation in an unfamiliar environment can be succeeded by using on‐line sensory information, which is essentially starved of humanoid intermediation. This research emphases on mechanical design of real mobile robot, its kinematic & dynamic model analysis and selection of AI technique based on perception, cognition, sensor fusion, path scheduling and analysis, which has to be implemented in robot for achieving integration of different preliminary robotic behaviors (e.g. obstacle avoidance, wall and edge following, escaping dead end and target seeking). Navigational paths as well as time taken during navigation by the mobile robot can be expressed as an optimization problem and thus can be analyzed and solved using AI techniques. The optimization of path as well as time taken is based on the kinematic stability and the intelligence of the robot controller. A set of linguistic fuzzy rules are developed to implement expert knowledge under various situations. Both of Mamdani and Takagi-Sugeno fuzzy model are employed in control algorithm for experimental purpose. Neural network has also been used to enhance and optimize the outcome of controller, e.g. by introducing a learning ability. The cohesive framework combining both fuzzy inference system and neural network enabled mobile robot to generate reasonable trajectories towards the target. An authenticity checking has been done by performing simulation as well as experimental results which showed that the mobile robot is capable of avoiding stationary obstacles, escaping traps, and reaching the goal efficiently

Design and Development of an Automated Mobile Manipulator for Industrial Applications

This thesis presents the modeling, control and coordination of an automated mobile manipulator. A mobile manipulator in this investigation consists of a robotic manipulator and a mobile platform resulting in a hybrid mechanism that includes a mobile platform for locomotion and a manipulator arm for manipulation. The structural complexity of a mobile manipulator is the main challenging issue because it includes several problems like adapting a manipulator and a redundancy mobile platform at non-holonomic constraints. The objective of the thesis is to fabricate an automated mobile manipulator and develop control algorithms that effectively coordinate the arm manipulation and mobility of mobile platform. The research work starts with deriving the motion equations of mobile manipulators. The derivation introduced here makes use of motion equations of robot manipulators and mobile platforms separately, and then integrated them as one entity. The kinematic analysis is performed in two ways namely forward & inverse kinematics. The motion analysis is performed for various WMPs such as, Omnidirectional WMP, Differential three WMP, Three wheeled omni-steer WMP, Tricycle WMP and Two steer WMP. From the obtained motion analysis results, Differential three WMP is chosen as the mobile platform for the developed mobile manipulator. Later motion analysis is carried out for 4-axis articulated arm. Danvit-Hartenberg representation is implemented to perform forward kinematic analysis. Because of this representation, one can easily understand the kinematic equation for a robotic arm. From the obtained arm equation, Inverse kinematic model for the 4-axis robotic manipulator is developed. Motion planning of an intelligent mobile robot is one of the most vital issues in the field of robotics, which includes the generation of optimal collision free trajectories within its work space and finally reaches its target position. For solving this problem, two evolutionary algorithms namely Particle Swarm Optimization (PSO) and Artificial Immune System (AIS) are introduced to move the mobile platform in intelligent manner. The developed algorithms are effective in avoiding obstacles, trap situations and generating optimal paths within its unknown environments. Once the robot reaches its goal (within the work space of the manipulator), the manipulator will generate its trajectories according to task assigned by the user. Simulation analyses are performed using MATLAB-2010 in order to validate the feasibility of the developed methodologies in various unknown environments. Additionally, experiments are carried out on an automated mobile manipulator. ATmega16 Microcontrollers are used to enable the entire robot system movement in desired trajectories by means of robot interface application program. The control program is developed in robot software (Keil) to control the mobile manipulator servomotors via a serial connection through a personal computer. To support the proposed control algorithms both simulation and experimental results are presented. Moreover, validation of the developed methodologies has been made with the ER-400 mobile platform

Research on a semiautonomous mobile robot for loosely structured environments focused on transporting mail trolleys

In this thesis is presented a novel approach to model, control, and planning the motion of a nonholonomic wheeled mobile robot that applies stable pushes and pulls to a nonholonomic cart (York mail trolley) in a loosely structured environment. The method is based on grasping and ungrasping the nonholonomic cart, as a result, the robot changes its kinematics properties. In consequence, two robot configurations are produced by the task of grasping and ungrasping the load, they are: the single-robot configuration and the robot-trolley configuration. Furthermore, in order to comply with the general planar motion law of rigid bodies and the kinematic constraints imposed by the robot wheels for each configuration, the robot has been provided with two motorized steerable wheels in order to have a flexible platform able to adapt to these restrictions. [Continues.