The problem of performing complex maneuvers in challenging terrains is crucial to the advancement of legged robots and assistive devices, yet little progress has been made in exploring practical solutions to operate in these environments. In this thesis, we tackle the problem by developing strategies to predict a robot's center of mass (CoM) behavior based on contact constraints, and any arbitrary CoM path for situations in which the system has single or multiple points of contact through which external reaction forces may be applied. Our method consists of first leveraging previous work on multi-contact dynamics to derive reaction force behavior from internal tension force profiles and kinematic CoM trajectories. We then study the nonlinear dynamics of single contact phases along arbitrary paths and employ numerical integration to derive state-space approximations of CoM behavior. We use this theoretical framework to synthesize complex maneuvers in various terrains by means of a motion planner in which we determine step transition sequences for continuous motions involving contact profiles which vary with time. Furthermore, we validate our strategy through several comparative case studies, examining the motion of a human subject performing a difficult maneuver in an aggressive terrain. We then seed our motion planning algorithm with a limited set of parameters chosen to match those of a human subject and predict CoM behavior for the same motion pattern. These case studies show that the estimated CoM behaviors generated from our planning algorithm closely resemble the behavior of the human subject and therefore validate our methods. / text

When a robotic system executes a task, there are a number of responsibilities that belong to either the operator and/or the robot. A more autonomous system has more responsibilities in the completion of a task and must possess the decision making skills necessary to adequately deal with these responsibilities. The system must also handle environmental constraints that limit the region of operability and complicate the execution of tasks. There are decisions about the robot’s internal configuration and how the manipulator should move through space, avoid obstacles, and grasp objects. These motions usually have limits and performance requirements associated with them. Successful completion of tasks in a given environment is aided by knowledge of the robot’s capabilities in its workspace. This not only indicates if a task is possible but can suggest how a task should be completed. In this work, we develop a grasping strategy for selecting and attaining grasp configurations for flexible tasks in environments containing obstacles. This is done by sampling for valid grasping configurations at locations throughout the workspace to generate a task plane. Locations in the task plane that contain more valid configurations are stipulated to have higher dexterity and thus provide greater manipulability of targets. For valid configurations found in the plane, we develop a strategy for selecting which configurations to choose when grasping and/or placing an object at a given location in the workspace. These workspace task planes can also be utilized as a design tool to configure the system around the manipulator’s capabilities. We determine the quality of manipulator positioning in the workspace based on manipulability and locate the best location of targets for manipulation. The knowledge of valid manipulator configurations throughout the workspace can be used to extend the application of task planes to motion planning between grasping configurations. This guides the end-effector through more dexterous workspace regions and to configurations that move the arm away from obstacles. The task plane technique employed here accurately captures a manipulator’s capabilities. Initial tests for exploiting these capabilities for system design and operation were successful, thus demonstrating this method as a viable starting point for incrementally increasing system autonomy. / text

The purpose of this study is to compare short-term surgical outcomes of robotic and abdominal myomectomy and to analyze the factors affecting the total operative time, estimated blood loss and length of hospital stay from a retrospective study of a consecutive case series of 122 pa-tients with symptomatic leiomyomata. Wilcoxon, t tests, multiple linear and logistic regressions analyses were performed. Patients in abdominal group had larger number of leiomyomata, larger tumor size and BMI. The operative time was longer in robotic group and was affected by the size and number of tumors, parity and interaction between parity and BMI. Estimated blood loss was lower in robotic group and was affected by the size and number of tumors .The pre-dicted odds of staying one day or less in the hospital for robotic group was 193.5 times the odds for abdominal group and was affected by the size and number of tumors.

Nežinomo ploto dengimas yra aktuali ir paplitusi problema. NPD sprendimas realiuose robotuose susiduria su daviklių ir mechanizmų netikslumu. Atliktame darbe yra pateiktas „Bouncing“ NPD algoritmo sprendimas robotui, turinčiam mažo tikslumo daviklius ir neprecizinius valdiklius. Taip pat atliktas darbas parodė sudėtingus roboto kūrimo aspektus ir galimus sprendimus. Sukurtas robotas dėl pigumo ir nesudėtingos realizacijos gali būti naudojamas kaip platforma kitokių algoritmų tyrimui. / The problem of unknown area coverage with mobile robots has received considerable attention over the past years. This problem is a common challenge in many applications, including automatic lawn mowing and vacuum cleaning. However, most of the approaches find difficult to implement in real life because of problems of environment data reading. In this paper we consider the problem of robust area covering algorithm implementation in mobile robot. The chosen approach is based on simple and robust algorithm for uncertain environment and simple robot platform. The results showed robustness, reliability of chosen method of control. The constructed robot has shown simplicity, cheapness of creation and possibility for different algorithm testing. The significance of this paper lies in the practical solution for robust mobile robot area coverage, suitable for noisy environment and low precisions robot sensors.

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With the rapid increase in adoption of consumer technologies, including inexpensive but powerful hardware, robotics appears poised at the cusp of widespread deployment in human environments. A key barrier that still prevents this is the machine understanding and interpretation of human activity, through a perceptual medium such as computer vision, or RBG-D sensing such as with the Microsoft Kinect sensor. This thesis contributes novel video-based methods for activity recognition. Specifically, the focus is on activities that involve interactions between the human user and objects in the environment. Based on streams of poses and object tracking, machine learning models are provided to recognize various of these interactions. The thesis main contributions are (1) a new model for interactions that explicitly learns the human-object relationships through a latent distributed representation, (2) a practical framework for labeling chains of manipulation actions in temporally extended activities and (3) an unsupervised sequence segmentation technique that relies on slow feature analysis and spectral clustering. These techniques are validated by experiments with publicly available data sets, such as the Cornell CAD-120 activity corpus which is one of the most extensive publicly available such data sets that is also annotated with ground truth information. Our experiments demonstrate the advantages of the proposed methods, over and above state of the art alternatives from the recent literature on sequence classifiers.

Intelligent Transportation Systems and supporting technologies have been an active area of research for some time. Human drivers exhibit slower response times and errors in judgment that can have serious adverse affects on traffic flow. These types of errors can be reduced or eliminated from the driving experience by introducing computer control systems into the automotive arena. The purpose of this research was to develop a scale model platform for the rapid prototyping and testing of ITS systems and technologies. Specifically, this body of work was concerned with the development of an automatic headway control system that utilized ultrasonic sensors. This control system was intended to automatically maintain headway distance in an effort to create an adaptive cruise control system for this scale model vehicle. Implementation of such systems could conceivably reduce driver fatigue by removing the burden of maintaining safe following distance from the driver. System dynamics of car-like robots with nonholonomic constraints were employed in this research to create a controller for an autonomous path following vehicle. The application of a working kinematic model describing car-like robotic systems allowed the development of a simple first order controller, as well as a sliding mode controller. Following the development and simulation of these two control laws, the system was applied to the FLASH project scale model vehicle to assess the practical use of the system on a mock highway. A satisfactory result is produced after testing was completed, and the application of such systems to scale model platforms is feasible. / Master of Science

It is increasingly common for people to work alongside robots in a variety of situations. When a robot is completing a task, the handler of the robot may be present. It is important to know how people interact with the robot when the handler is next to the robot. Our study focuses on whether handler’s presence can affect human’s behavior toward the robot. Our experiment targets two different scenarios (handler present and handler absent) in order to find out human’s behavior change toward the robot. Results show that in the handler present scenario, people are less willing to interact with the robot. However, when people do interact with the robot, they tend to interact with both the handler and the robot. This suggests that researchers should consider the presence of a handler when designing for human-robot interactions.

Nurses who provide care in robotic surgery must have sufficient special training in the operation of the da Vinci robot to perform their roles with knowledge and confidence that can yield optimal patient outcomes. The local nursing practice problem in the project facility, and the focus of this doctoral project, was the lack of an evidenced-based robotics education program for registered nurses who participate in robotic surgery. The gap in practice was nurses' lack of knowledge, which interfered with the care provided to the robotic surgical population. The purpose of this project was to develop a staff robotics education program in order to answer the question if the implementation of an evidence-based robotics education program would improve nurses' knowledge in the practice of robotic surgery. The education program was developed using Knowles adult learning theory and information obtained from a comprehensive literature search. A planning team, consisting of local clinicians with expertise in robotic surgery, provided feedback and assisted with the development of the education program and accompanying competency checklist. Ten nurses received the education, and 90-100% of the nurses reported increased knowledge and confidence regarding practice in the specialty of robotic surgery following the education. Leadership at the project site have decided to require surgical nurses receive the robotic education upon their employment and annually thereafter. The social change resulting from the use of this evidence-based robotics education program could include increased nursing performance and therefore, decreased complications for patients undergoing robotic surgery.

The main task of this master thesis is design of robotic deburring workcell. The thesis informs about basic requests of object deburring using industrial robots. From layout variants, the one most suitable is picked. Chosen variant contains proper clamping solution as well as deburring tool and safety requirements. The concept design of robotic deburring cell in 3D visualization is the result of this diploma thesis.