Browsing by Subject "Mobile robots."

Now showing 1 - 6 of 6

Open Access
3D dynamic modeling of spherical wheeled self-balancing mobile robot
(2012) İnal, Ali Nail
In recent years, dynamically stable platforms that move on spherical wheels, also known as BallBots, gained popularity in the robotics literature as an alternative locomotion method to statically stable wheeled mobile robots. In contrast to wheeled platforms which do not have to explicitly be concerned about their balance, BallBot platforms must be informed about their dynamics and actively try to maintain balance. Up until now, such platforms have been approximated by simple planar models, with extensions to three dimensions through the combination of decoupled models in orthogonal sagittal planes. However, even though capturing certain aspects of the robot’s motion is possible with such decoupled models, they cannot represent inherently spatial aspects of motion such as yaw rotation or coupled inertial effects due to the motion of the rigid body. In this thesis, we introduce a novel, fully-coupled 3D model for such spherical wheeled balancing platforms. We show that our novel model captures important spatial aspects of motion that have previously not been captured by planar models. Moreover, our new model provides a better basis for controllers that are informed by more expressive system dynamics. In order to establish the expressivity and accuracy of this new model, we present simulation studies in dynamically rich situations. We use circular paths to reveal the advantages of the new model for fast maneuvers. Additionally, we introduce new inverse-dynamics controllers for a better attitude control and investigate within simulations the capability of sustaining dynamic behaviors. We study the relation between circular motions in attitude angles and associated motions in positional variables for BallBot locomotion.
Open Access
A comparison of different approaches to target differentiation with sonar
(2001) Ayrulu (Erdem), Birsel
This study compares the performances of di erent classication schemes and fusion techniques for target di erentiation and localization of commonly encountered features in indoor robot environments using sonar sensing Di erentiation of such features is of interest for intelligent systems in a variety of applications such as system control based on acoustic signal detection and identication map building navigation obstacle avoidance and target tracking The classication schemes employed include the target di erentiation algorithm developed by Ayrulu and Barshan statistical pattern recognition techniques fuzzy c means clustering algorithm and articial neural networks The fusion techniques used are Dempster Shafer evidential reasoning and di erent voting schemes To solve the consistency problem arising in simple ma jority voting di erent voting schemes including preference ordering and reliability measures are proposed and veried experimentally To improve the performance of neural network classiers di erent input signal representations two di erent training algorithms and both modular and non modular network structures are considered The best classication and localization scheme is found to be the neural network classier trained with the wavelet transform of the sonar signals This method is applied to map building in mobile robot environments Physically di erent sensors such as infrared sensors and structured light systems besides sonar sensors are also considered to improve the performance in target classication and localization.
Open Access
Dynamic obstacle avoidance with a prototype mobile robot using acoustic, infrared and position sensing
(1997) Kurbay, Saner
In this study, a small mobile robot is designed and built which employs infrared and acoustic sensors for detecting obstacles in the environment and a computer mouse for position sensing* that is installed underneath the robot. The robot is suitably designed for many robotics and sensing applications. The design of the robot and the dynamic obstacle avoidance algorithm are discussed in this study. The mobile robot is used in a real time dynamic obstacle avoidance application successfully. Linear Kalman hlter is employed in the smoothing of the obstacle's measured coordinates and velocities. Full autonomous operation is possible by updating the EPROM of the robot such that the dynamic obstacle avoidance algorithm is on the robot itself, not on the computer.
Open Access
Improving visual SLAM by filtering outliers with the aid of optical flow
(2011) Özaslan, Tolga
Simultaneous Localization and Mapping (SLAM) for mobile robots has been one of the challenging problems for the robotics community. Extensive study of this problem in recent years has somewhat saturated the theoretical and practical background on this topic. Within last few years, researches on SLAM have been headed towards Visual SLAM, in which camera is used as the primary sensor. Superior to many SLAM application run with planar robots, VSLAM allows us to estimate the 3D model of the environment and 6-DOF pose of the robot. Being applied to robotics only recently, VSLAM still has a lot of room for improvement. In particular, a common issue both in normal and Visual SLAM algorithms is the data association problem. Wrong data association either disturbs stability or result in divergence of the SLAM process. In this study, we propose two outlier elimination methods which use predicted feature location error and optical flow field. The former method asserts estimated landmark projection and its measurement locations to be close. The latter accepts optical flow field as a reference and compares the vector formed by consecutive matched feature locations; eliminates matches contradicting with the local optical flow vector field. We have shown these two methods to be saving VSLAM from divergence and improving its overall performance. We have also described our new modular SLAM library, SLAM++.
Open Access
An USB-based real-time communication infrastructure for robotic platforms
(2009) Öztürk, Cihan
A typical robot operates by carrying out a sequence of tasks, usually consisting of acquisition of sensory data, interpretation of sensory inputs for making decisions, and application of commands on appropriate actuators. Since this cycle involves transmission of data among electro-mechanical components of the robot, high quality communication is a fundamental requirement. Besides being reliable, robust, extensible, and efficient, a high quality communication infrastructure should satisfy all additional communication requirements that are specific to the robot it is used within. To give an example, for a rapid moving autonomous robot with a reactive controller which is intended to be used in time critical situations, a real-time communication infrastructure which guarantees demanded response times is required. The Universal Robot Bus (URB) is a distributed communication framework based on the widely used I2C standard, intended to be used specifically within rapid autonomous robots. Real-time operation guarantees are provided by defining upper bounds in response times. URB facilitates exchange of information between a central controller and distributed sensory and actuator units. Adoption of a centralized topology by connecting distributed units directly to a central controller creates a bottleneck around the central unit, causing problems in scalability, noise and cabling. In order to overcome this problem, URB is physically realized such that gateways (bridges) are incorporated between the central and distributed units which offload the work of the central unit and master the underlying I2C bus. Connection between the central unit and the gateway, the uplink channel, can be established using any high bandwidth communication alternative which successfully satisfies communication requirements of the system. The main contribution of this thesis is the design and implementation of the URB uplink channel using the well known Universal Serial Bus (USB) protocol. Although true real-time operation is not feasible with USB due to its polling mechanism, USB frame scheduling of 1ms is acceptable for our application domain. In this thesis, hardware components used in the USB uplink implementation as well as our software implementation are covered in detail. These details include the firmware running on the gateway, a Linux based device driver and a client control software that uses a USB library running on central controller, and finally sub-protocols between the application-driver and driver-firmware layers. The thesis also includes our experiments to estimate the performance of the USB uplink in terms of its roundtrip latency, bandwidth, scalability, robustness, and reliability. Finally, this thesis also serves as a reference on distributed systems, device driver development, Linux kernel programming, communication protocols, USB and its usage in real-time applications.
Open Access
Using shape information from natural tree landmarks for improving SLAM performance
(2012) Turan, Bilal
Localization and mapping are crucial components for robotic autonomy. However, such robots must often function in remote, outdoor areas with no a-priori knowledge of the environment. Consequently, it becomes necessary for field robots to be able to construct their own maps based on exteroceptive sensor readings. To this end, visual sensing and mapping through naturally occurring landmarks have distinct advantages. With the availability of high bandwidth data provided by visual sensors, meaningful and uniquely identifiable objects can be detected. This improves the construction of maps consisting of natural landmarks that are meaningful for human readers as well. In this thesis, we focus on the use of trees in an outdoor environment as a suitable set of landmarks for Simultaneous Localization and Mapping (SLAM). Trees have a relatively simple, near vertical structure which makes them easily and consistently detectable. Furthermore, the thickness of a tree can be accurately determined from different viewpoints. Our primary contribution is the usage of the width of a tree trunk as an additional sensory reading, allowing us to include the radius of tree trunks on the map. To this end, we introduce a new sensor model that relates the width of a tree landmark on the image plane to the radius of its trunk. We provide a mathematical formulation of this model, derive associated Jacobians and incorporate our sensor model into a working EKF SLAM implementation. Through simulations we show that the use of this new sensory reading improves the accuracy of both the map and the trajectory estimates without additional sensor hardware other than a monocular camera.