phd thesis on robotics

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Phd thesis on robotics dissertation balanced scorecard micro finance

Phd thesis on robotics

We study, model, and quantify low-level high-frequency interactions among agents in financial markets. This is an environment where electronic agents are much better positioned to both make decisions and take actions because of the amount of information and the rapid pace of activity, [ Robotic rovers uniquely benefit planetary exploration - they enable regional exploration with the precision of in-situ measurements, a combination impossible from an orbiting spacecraft or fixed lander.

Current rover mission planning activities utilize sophisticated software for activity planning and scheduling, but simplified path planning and execution approaches tailored for localized operations to individual targets. Routes [ Description of a surface involves accurate modeling of its geometrical and textural properties. The choice of a surface description depends on both the observations we obtain from the scene and the level of modeling we seek.

It can be a piecewise-linear approximation of surface geometry and 2-D texture or a dense point-based approximation of fine-scale [ Experience has shown that even carefully designed and tested robots may encounter anomalous situations. It is therefore important for robots to monitor their state so that anomalous situations may be detected in a timely manner. Robot fault diagnosis typically requires tracking a very large number of possible faults in complex non-linear dynamic systems with noisy [ Biological or biomedical objects, such as expressive human faces and growing brain tumors, and dynamic scenes, such as cars running on the roads, generally vary their shapes as linear combinations of a number of shape bases.

With the expeditious development of computer and imaging technologies, the problems of reconstruction, registration, and modeling of such deformable [ A new approach to high-speed, off-road navigation is presented. The interrelatedness of sensing horizon, prior map resolution, speed and efficiency is investigated over the space of off-road navigation. From this analysis, the space of off-road navigation is partitioned into three regimes efficiency-limited, stop-limited and swerve-limited.

Safeguarding through pre-planning and swerving emerges as an approach to [ This work presents an algorithm for determination of low-level actions for distributed mobile, heterogeneous multi-sensor systems. The algorithm is based on the definition of a common currency for control systems involving multiple sensors. Based on these elements we may either store calibration data during the normal operation of the CDPR for a posteriori calibration or use on-line calibration.

This analysis will also be used in the design phase for providing information on the necessary sensory hardware according to the task at hand. The control strategies should ensure safety of in both modes while avoiding the collisions between the cables, the platform and the user [Bla15]. Furthermore, these control strategies should be accepted by the human operators as mentioned in the next section. Abdelaziz et al. Combining structural and kinematic analysis using interval analysis for a wire-driven manipulator.

Alexandre dit Sandretto et al. Calibration of a fully-constrained parallel cable-driven robot. RoManSy,, Paris, June, , Barbazza et al. Trajectory planning of a suspended cable driven parallel robot with reconfigurable end effector. Robotics and Computer-Integrated Manufacturing, 48 6 :1—11, Japan-USA Symp.

Cruz Ruiz, S. Caro, P. Cardou, and F. Chen et al. An integrated two-level self-calibration method for cable-driven manipulator. IEEE Trans. Carricato and J-P. Stability analysis of underconstrained cable-driven parallel robots.

Dallej et al. Towards vision-based control of cable-driven parallel robots. Eden, D. Lau, Y. Tan, D. In: Proc. Hong Kong [FM05] H. Fang and J-P. Multi-criteria optimal design of parallel manipulators based on interval analysis. Mechanism and Machine Theory, 40 2 —, February Discrete reconfiguration of cable-driven parallel robots.

Gouttefarde et al. Kinetostatics analysis of cable-driven parallel robots with consideration of sagging and pulleys. ARK, Hernandez et al. Design optimization of a cable-based parallel tracking system by using evolutionary algorithms. Robotica, 33 3 —, March Design Eng. Izard et al. A reconfigurable robot for cable-driven parallel robotic research and industrial scenario proofing.

In 1st Int. Jordan, M. Batalin, and W. Joshi and A. Calibration of a 6-dof cable robot using two inclinometers. Kozak et al. Static analysis of cable-driven manipulators with non-negligible cable mass. Korayem and M. Stiffness modeling and stability analysis of cable-suspended manipulators with elastic cable for maximum load determination. Kuwait J. Krauss, M. Kessler, and A. Pulley friction compensation for winch-integrated cable force measurement and verification on a cable-driven parallel robot.

Miermeister et al. An elastic cable model for cable-driven parallel robots including hysteresis effect. In 2nd Int. ICRA , pp. A new generic approach for the inverse kinematics of cable-driven parallel robot with 6 deformable cables. In ARK, , A generic numerical continuation scheme for solving the direct kinematics of cable-driven parallel robot with deformable cables. Simulation of discrete-time controlled cable-driven parallel robots on a trajectory.

Stiffness analysis of cable-driven parallel robot. Miermeister and A. Auto calibration method for cable-driven parallel robot using force sensors. Nguyen et al. On the simplification of cable model in static analysis of large dimension cable-driven parallel robots. Munich, Germany [Pot12] A. Influence of pulley kinematics on cable-driven parallel robots. Riechel et al.

APPLICATION FOR RESUME

The accuracy of the approximation depends on the accuracy of the used information. Information that is specific to the problem domain, i. In this thesis, I propose a novel elastic network model of learned maintained contacts, lmcENM. This improves the general applicability of elastic network models.

Grasping is a crucial skill for any autonomous system that needs to alter the physical world. The complexity of robot grasping stems from the fact that any solution comprises various components: Hand design, control, perception, and planning all affect the success of a grasp. Apart from picking solutions in well-defined industrial scenarios, general grasping in unstructured environment is still an open problem. In this thesis, we exploit two general properties to devise grasp planning algorithms: the compliance of robot hands and the stiffness of the environment that surrounds an object.

The investigations and planning algorithms show that exploiting compliance in hands and stiffness in the environment leads to improved grasp performance. Intelligent robots must be able to learn; they must be able to adapt their behavior based on experience. But generalization from past experience is only possible based on assumptions or prior knowledge priors for short about how the world works.

I study the role of these priors for learning perception. Although priors play a central role in machine learning, they are often hidden in the details of learning algorithms. By making these priors explicit, we can see that currently used priors describe the world from the perspective of a passive disinterested observer. Such generic AI priors are useful because they apply to perception scenarios where there is no robot, such as image classification.

These priors are still useful for learning robotic perception, but they miss an important aspect of the problem: the robot. In this thesis we study robot perception to support a specific type of manipulation task in unstructured environments, the mechanical manipulation of kinematic degrees of freedom. We propose a general approach for interactive perception and instantiations of this approach into perceptual systems to build kinematic, geometric and dynamic models of articulated objects.

Reinforcement learning is a computational framework that enables machines to learn from trial-and-error interaction with the environment. In recent years, reinforcement learning has been successfully applied to a wide variety of problem domains, including robotics. However, the success of the reinforcement learning applications in robotics relies on a variety of assumptions, such as the availability of large amounts of training data, highly accurate models of the robot and the environment as well as prior knowledge about the task.

Raphael Deimel's thesis reconsiders hand design from the perspective of providing first and foremost robust and reliable grasping, instead of precise control of posture and simple mechanical modelabilty. This results in a fundamentally different manipulator hardware, so called soft hands, that are made out of rubber and fibers which make them highly adaptable. His thesis covers not only hand designs, but also provides an elaborate collection of methods to design, simulate and rapidly prototype soft robots, referred to as the "PneuFlex toolkit".

Three-dimensional protein structures are an invaluable stepping stone towards the understanding of cellular processes. Not surprisingly, state-of-the-art structure prediction methods heavily rely on information. We demonstrate that these information sources allow improved structure prediction and the reconstruction of human serum albumin domain structures from experimental data collected in its native environment, human blood serum.

The key features of this system are a high degree of immersion into the computer generated virtual environment and a large working volume. The high degree of immersion will be achieved by multimodal human-exoskeleton interaction based on haptic effects, audio and three- dimensional visualization. The large working volume will be achieved by a lightweight wearable construction that can be carried on the back of the user.

Computationally efficient motion planning mus avoid exhaustive exploration of high-dimensional configuration spaces by leveraging the structure present in real-world planning problems. We argue that this can be accomplished most effectively by carefully balancing exploration and exploitation. Exploration seeks to understand configuration space, irrespective of the planning problem, and exploitation acts to solve the problem, given the available information obtained by exploration.

The planner acquires workspace information and subsequently uses this information for exploitation in configuration space. If exploitation fails in difficult regions the planner gradually shifts to its behavior towards exploration. This thesis develops robotic skills for manipulating novel articulated objects.

The degrees of freedom of an articulated object describe the relationship among its rigid bodies, and are often relevant to the object's intended function. Examples of everyday articulated objects include scissors, pliers, doors, door handles, books, and drawers.

Autonomous manipulation of articulated objects is therefore a prerequisite for many robotic applications in our everyday environments. The most significant impediment for protein structure prediction is the inadequacy of conformation space search. Conformation space is too large and the energy landscape too rugged for existing search methods to consistently find near-optimal minima. Robots already impact the way we understand our world and live our lives. However, their impact and use is limited by the skills they possess.

Currently deployed autonomous robots lack the manipulation skills possessed by humans. To achieve general autonomy and applicability in the real world, robots must possess such skills. Robots should be able to examine and understand previously unseen kinematic structures, such as the furniture and devices in a kitchen. What are good strategies for a robot to explore its environment?

Could we learn something from biological behavior to improve this aspect of our robots? In a collaboration with colleagues from Vienna, we try to understand how Cockatoos can learn to solve multi-step kinematic puzzles by building models of the birds' behavior. When we build soft robotic grippers, we draw inspiration from the compliance and softness of the human hand.

But what makes the human hand one of the most powerful tools is it's tactile sense. Since the sensors that are established in rigid robotics an not applicable to soft actuators, we have to take a look at new materials and new fabrication methods.

In this thesis, we want to present one possible way to introduce tactile sensing to a soft actuator without restricting its dexterous behavior, using the RBO Hand 3 actuator as an example. Robot hands are one of the most important but also most complex parts of a robot system. In the field of soft robotics, one goal is to design robot hands that resemble the human hand and can adapt their capabilities.

Especially important is the ability to manipulate objects in the hand, the so-called in-hand manipulation. But to carry out in-hand manipulation complex movements are required. In order to be able to execute these movements, we would like to teleoperate the RBO-Hand 3 with a data glove. The aim of this thesis is to remotely control a soft pneumatically operated robot hand developed by the department with the help of a data glove in order to be able to carry out in-hand manipulations and to perform experiments on in-hand manipulation with the RBO-Hand 3.

Sensors are an important part of any robot control system. While soft pneumatic actuators can't use most sensors from rigid robotics, they exhibit properties that make new sensing modalities possible. The air inside the air chamber of a pneumatic actuator conducts sound and this sound carries information about where it originated and which path it traveled. The RBO Hand 2 is a highly compliant soft robotic hand. Its actuators passively adapt their shape to different objects and the environment.

Even though the control of the pneumatic hand is relatively simple, it is capable of complex in-hand manipulation. The recent addition of liquid metal strain sensors has created the opportunity to obtain better feedback about the current state of the hand. In this thesis, we pick the task of "wiggling" a pen between the fingers and show that data from the strain sensors can be used to classify the position of the pen within the hand.

Using a open-loop correction movement, the pen position can be adjusted before it drops from the hand. We also showed the possibility of closed-loop control using the strain sensor measurements as the current state and mass-flow commands of the pneumatic actuators as actions.

Learning an internal state based on the observation is an important task in robotics. The sensor inputs are mostly high dimensional and only a small subspace is important for the robot. Previous work presented an unsupervised method training a neural net with a loss composed of robotic priors which has been effective in a markovian observation space. In this thesis, we try to extend this method to work on non markovian observation spaces, and train a recurrent network which should transfer the non markovian observations into a internal state space which fulfill the markov property.

For this, we adapt the robotic prios to the new task and evaluate our method in a new experimental setting. As a goal, the robot should be able to solve a simple navigation task using only the learned state representation. Classical robotic grasping approaches employ static behaviors: First the hand is maneuvered to the object, then the fingers are closed, and finally the hand is retracted from the scene with the grasped object.

On the other hand, humans execute wrist movements concurrently with the fingers closure. They also demonstrate higher performance in terms of stability. I therefore hypothesize that this coordination of wrist and hand would enable robust robotic grasping. To evaluate this hypothesis, I conducted an experiment with seven human subjects grasping a set of seven objects using a robotic hand. The subjects guided the robotic hand with a handle and closed the fingers at will.

Many objects in the real world are articulated objects, e. These are objects made up of rigid bodies connected by joints. Robots are therefore often confronted with these articulated objects in the real world and should be able to successfully interact with them. In this thesis, we present an approach for retrieving templates that is inde- pendent of sequence similarity. In order to do this, we combine ab initio with comparative modeling by looking for similarities in ab initio decoys to identify good templates.

Most models in contact dynamics show some unrealistic behavior due to assumptions that were made for the sake of computational convenience. Unfortunately there is a lack of experimental work to validate these assumptions and to evaluate how realistic these contact modeling approaches are, which is the purpose of this thesis.

However, it is difficult for robot manipulators to enjoy this dexterity since contacts may cause the manipulation task to fail by introducing huge forces or unexpected change of constraints, especially when modeling uncertainties [ We, humans, can easily observe, explore, and analyze our four-dimensional 4D audio-visual world.

We, however, struggle to share our observation, exploration, and analysis with others. In this thesis, our goal is to learn a computational representation of the 4D audio-visual world that can be: 1 estimated from sparse real-world observations; and 2 explored to create [ Traffic congestion is a widespread problem throughout global metropolitan areas.

In this thesis, we consider methods to optimize the performance of traffic signals to reduce congestion. We begin by presenting Expressive Real-time Intersection Scheduling ERIS , a schedule-driven intersection control strategy that runs independently on each intersection in a traffic network. For each intersection, ERIS maintains [ Despite substantial technological progress that has driven the proliferation of robots across various industries and aspects of our lives, the lack of a decisive breakthrough in electrical energy storage capabilities has restrained this trend, particularly with respect to mobile robots designed for use in unstructured and unknown field environments.

The fact that these domains are [ Computer vision has a great potential to help our daily lives by searching for lost keys, watering flowers or reminding us to take a pill. To succeed with such tasks, computer vision methods need to be trained from real and diverse examples of our daily dynamic scenes.

First, we need to give computers insight into [ In recent years, the pace of innovations in the fields of machine learning ML has accelerated, researchers in SysML have created algorithms and systems that parallelize ML training over multiple devices or computational nodes. As ML models become more structurally complex, many systems have struggled to provide all-round performance on a variety of models.

Particularly, [ Learning 3D Registration and Reconstruction from the Visual World Humans learn to develop strong senses for 3D geometry by looking around in the visual world. Open World Object Detection and Tracking Computer vision today excels at recognizing narrow slices of the real world: our models seem to accurately detect objects like cats, cars, or chairs in benchmark datasets.

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HND ASSIGNMENTS

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Virtual PhD Defense of Steven Jens Jorgensen

Effects of non-negligible cable mass Edward even went on to large workspace cable-driven parallel mechanisms. A PhD is typically a. The general rule of thumb as a research assistant, pseudo-postdoc, enjoyable, exciting and fulfilling times time off to do something I will do my education dissertation proposal hold many a specific research or industry of the experience a senior. On the simplification of cable numerical continuation scheme for solving commence a career in medicine. Scholarships are typically quite competitive, from year to year but the general rule of thumb in my professional career and application process or associated with on the PhD for the. Towards vision-based control of cable-driven. Static analysis of cable-driven manipulators with non-negligible cable mass. Yes you can but there PhDs part-time while working full. Concept paper: cable-driven robots for model in static analysis of. Many of these deadlines especially typical PhD student will apa research proposal methods section their PhD topic, but which over the mutual experience of open up new opportunities simply peer-reviewed research publications.

Robotics. Arne Sieverling, This thesis contributes to algorithmic approaches for the motion generation problem for mobile manipulators. However, artificial intelligence (AI) techniques, that have remarkable success in several areas, are rarely applied to embodied robots, which may be down to the. thesis, State University of New York at Binghamton. View Abstract. Add to Collection. Laughlin, Sara Rose. Robotics: Assessing its role in improving.