This project is carried out in the field of motion planning of AGVs for the company AGVE with the aim to automate the obstacle free trajectory generation process. The process of manually generating splines in AutoCAD to achieve obstacle avoidance is replaced by the automatic generation of paths by running a python script. Artificial potential field algorithm is implemented in the python script to achieve obstacle avoidance. Clothoid curve is used to create feasible trajectories for obtaining obstacle free paths. The developed program is tested and proved suitable on three scenarios including a real-life problem encountered by the company. The output obstacle free path can be manipulated using three factors which are alpha, moving the neighbours and manipulating the scaling factor for potential fields in the APF algorithm.

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Many mobility impaired users are unable to operate a powered wheelchair safely, without causing harm to themselves, others, and the environment. Smart wheelchairs that assist or replace user control have been developed to cater for these users, utilising systems and algorithms from autonomous robots. Despite a sustained period of research and development of robotic wheelchairs, there are very few available commercially. This thesis describes work towards developing a navigation system that is aimed at being retro-fitted to powered wheelchairs. The navigation system developed takes a systems engineering approach, integrating many existing open-source software projects to deliver a system that would otherwise not be possible in the time frame of a master's thesis. The navigation system introduced in this thesis is aimed at operating in an unstructured indoor environment, and requires no a priori information about the environment. The key components in the system are: obstacle avoidance, map building, localisation, path planning, and autonomously travelling towards a goal. The test electric wheelchair was instrumented with the following: a laptop, a laser scanner, wheel encoders, camera, and a variety of user input methods. The user interfaces that have been implemented and tested include a touch screen friendly graphical user interface, keyboard and joystick.

Navigation and guidance of mobile robots towards steady or maneuvering objects (targets) is one of the most important areas of robotics that has attracted a lot of attention in recent decades. However, in most of the existing methods, both the line-of-sight angle (bearing) and the relative distance (range) are assumed to be available for navigation and guidance algorithms. There is also a relatively large body of research on navigation and guidance with bearings-only measurements. In contrast, only a few results on navigation and guidance towards an unknown target using range-only measurements have been published. Various problems of navigation, guidance, location estimation and target tracking based on range-only measurements often arise in new wireless networks related applications. Recent advances in these applications allow us to use inexpensive transponders and receivers for range-only measurements which provide information in dynamic and noisy environments without the necessity of line-of-sight. To take advantage of these sensors, algorithms must be developed for range-only navigation. The main part of this thesis is concerned with the problem of real-time navigation and guidance of Wheeled Mobile Robots (WMRs) towards an unknown stationary or moving target using range-only measurements. The range can be estimated using the signal strength and the robust extended Kalman filtering. Several similar algorithms for navigation and guidance termed Equiangular Navigation and Guidance (ENG) laws are proposed and mathematically rigorous proofs of convergence and stability of the proposed guidance laws are given. The experimental investigation into the use of range data for a WMR navigation is documented and the results and discussions on the performance of the proposed guidance strategies are presented, where a wheeled robot successfully approach a stationary or follow a maneuvering target. In order to safely navigate and reliably operate in populated environments, ENG is then modified into Augmented-ENG (AENG), which enables the robot to approach a stationary target or follow an unpredictable maneuvering object in an unknown environment, while keeping a safe distance from the target, and simultaneously preserving a safety margin from the obstacles. Furthermore, we propose and experimentally investigate a new biologically inspired method for local obstacle avoidance and give the mathematically rigorous proof of the idea. In order for the robot to avoid collision and bypass the enroute obstacles in this method, the angle between the instantaneous moving direction of the robot and a reference point on the surface of the obstacle is kept constant. The proposed idea is combined with the ENG law, which leads to a reliable and fast long-range navigation. The performance of both navigation strategy and local obstacle avoidance techniques are confirmed with computer simulations and several experiments with ActivMedia Pioneer 3-DX wheeled robots. The second part of the thesis investigates some challenging problems in the area of wheeled robot navigation. We first address the problem of bearing-only guidance of an autonomous vehicle following a moving target with smaller minimum turning radius compared to that of the follower and propose a simple and constructive navigation law. In compliance with the increasing research on decentralized control laws for groups of mobile autonomous robots, we consider the problems of decentralized navigation of network of WMRs with limited communication and decentralized stabilization of formation of WMRs. New control laws are presented and simulation results are provided to illustrate the control laws and their applications.

<p>This thesis describes an ongoing project of which the purpose is designing and developing techniques and algorithms for autonomous off-road vehicles. The focus is on some of the components necessary to accomplish autonomous navigation, which involves sensing and moving safely along a user-defined path in a dynamic forest environment. The work is part of a long-term vision in the forest industry of developing an unmanned shuttle that transports timber from the felling area to the main roads for further transportation. A new path-tracking algorithm is introduced and demonstrated as superior to standard algorithms, such as Follow the Carrot and Pure Pursuit. This is accomplished by using recorded data from a path-learning phase. By using the recorded steering angle, the curvature of the path is automatically included in the final steering command. Localization is accomplished by a neural network that fuses data from a Real-Time Kinematic Differential GPS/GLONASS, a gyro, and wheel odometry. Test results are presented for path tracking and localization accuracy from runs conducted on a full-sized forest machine. A large part of the work has been design and implementation of a general software platform for research in autonomous vehicles. The developed algorithms and software have been implemented and tested on a full-size forest machine supplied by our industrial partner Komatsu Forest AB. Results from successful field tests with autonomous path tracking, including obstacle avoidance, are presented.</p>

The ability to navigate with limited vision is a skill that is often employed in our daily lives. Navigating without vision to a remembered target has previously been studied. However, not much is known about the attention required to perform blind navigation. We examined the effect of aging and presence of obstacles on the attentional demands of blind navigation. We evaluated reaction time, navigation errors and average walking speed in an 8 meter walking path, with or without obstacles, in the absence of vision. Results showed that older participants had increased reaction time and increased linear distance travelled as opposed to young participants, that obstacles increased reaction time and decreased average walking speed in all participants, and that emitting the reaction time stimulus early in the trial increased the linear distance travelled. Interpretation of the results suggests that aging and presence of obstacles augments the attentional demands of blind navigation.

The goal of this thesis is to implement the control and design of an intelligent vehicle based on an embedded DSP platform (eZdspTM F2812). The overall system including steering wheel AC serve motor, brake actuator, throttle driving circuit and the sensors is equipped in a golf car as a platform. Otherwise, digital image processing technology is used to realize the autonomous driving system which can achieve multi-mode of lane-keeping, lane-change and obstacle-avoidance. In the lane-keeping control, the road information can be provided by the vision system. According to the offset and displacement of angle as input signal, a fuzzy controller is used to compute the desired steering wheel angle and let the golf car can cross road safely. In lane-change, a smooth trajectory can be generated by IMU, IMU is used to collect the information data of yaw rate and yaw angle when human-driving. That makes autonomous driving system become more humanlike and to achieve an open-loop lane-change maneuver. In obstacle-avoidance, we use a laser range scanner to detect the distance of a front obstacle. When the distance is lower than safety distance, double lane-change will be activated to avoid the front obstacle. The overall system has been examined on NSYSU campus roads.

In daily life, there are a lot of inconveniences for the vision disabled people, even thought there are few equipments for them to use. However, there has no equipment to guide the vision disabled people on the pedestrian crossing, it will cause them being a dangerous situation while through the pedestrian crossing. To design an intelligent vehicle to help vision disabled people through the pedestrian crossing safely is an important topic. This thesis presents an autonomous transportation robot in intersections to provide older and vision disabled people to through the pedestrian crossing safely. This robot is based on a commercial wheelchair which equipped with cameras, inertial measurement unit, encoder, GPS module, hearts rate sensor, etc. In this study, by using the camera settled in the top of the robot to capture the picture, it could detect the region of pedestrian crossing and find the obstacles and pedestrian on the pedestrian crossing with image processing techniques. Then using the fuzzy controller to do the obstacle avoidance or people following. This robot can make the automatic parking after through the pedestrian crossing and transmit the position of the robot and the user¡¦s heart rate to the remote monitor system.

Independent mobility is critical to quality of life for people of all ages, and impaired mobility leaves one with both physical and mental disadvantages. Unfortunately, there are some individuals unable to operate an electric wheelchair due to physical, perceptual, or cognitive deficits. The prime objective of this research was to develop a prototype system which can provide mobility assistant to individuals who would otherwise find it difficult or impossible to operate a power wheelchair. To accomplish this goal, a prototype system consisting of several components including an embedded microcontroller and multiple sensors has been designed which can be added to a standard power wheelchair and make it smart. The control system algorithm designed for this prototype model is based on the fuzzy logic control theory and its main purpose is to augment the user ability to navigate the wheelchair and will provide a safe and comfortable journey to the user.

The ability to navigate with limited vision is a skill that is often employed in our daily lives. Navigating without vision to a remembered target has previously been studied. However, not much is known about the attention required to perform blind navigation. We examined the effect of aging and presence of obstacles on the attentional demands of blind navigation. We evaluated reaction time, navigation errors and average walking speed in an 8 meter walking path, with or without obstacles, in the absence of vision. Results showed that older participants had increased reaction time and increased linear distance travelled as opposed to young participants, that obstacles increased reaction time and decreased average walking speed in all participants, and that emitting the reaction time stimulus early in the trial increased the linear distance travelled. Interpretation of the results suggests that aging and presence of obstacles augments the attentional demands of blind navigation.