This results in a fundamentally different manipulator hardware, so called soft hands, that are made out of rubber and fibers which Thesis robotics them highly adaptable. Examples of everyday articulated objects include scissors, pliers, doors, door handles, books, and drawers.
Learning robotic perception through prior knowledge Rico Jonschkowski, Intelligent robots must be able to learn; they must be able to adapt their behavior based on experience.
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.
The planner acquires workspace information and subsequently uses this information for exploitation in configuration space.
We argue Thesis robotics this can be accomplished most effectively by carefully balancing exploration and exploitation. The large working volume will be achieved by a lightweight wearable construction that can be carried on the back of the user.
In recent years, reinforcement learning has been successfully applied to a wide variety of problem domains, including robotics. In this thesis, we study several of these assumptions and investigate how to Thesis robotics them.
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". Leveraging Novel Information Sources for Protein Structure Prediction Michael Bohlke-Schneider, Three-dimensional protein Thesis Thesis robotics are an invaluable stepping stone towards the understanding of cellular processes.
Conformation space is too large and the energy landscape too rugged for existing search methods to consistently find near-optimal minima. Autonomous manipulation of articulated objects is therefore a prerequisite for many robotic applications in our everyday environments.
On the one hand, we study them in two concrete applications of reinforcement learning in robotics: To that end, we look at these assumptions from different angles. Currently deployed autonomous robots lack the manipulation skills possessed by humans. These priors are still useful for learning robotic perception, but they miss an important aspect of the problem: Multimodal human computer interaction in virtual realities based on an exoskeleton Ingo Kossyk, The key features of this system are a high degree of immersion into the computer generated virtual environment and a large working volume.
This thesis aims to leverage new information sources: But generalization from past experience is only possible based on assumptions or prior knowledge priors for short about how the world works.
If exploitation fails in difficult regions the planner gradually shifts to its behavior towards exploration. 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.
On the other hand, we develop an abstract explanatory framework that relates the assumptions to the decomposability of problems and solutions. 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.
However, their impact and use is limited by the skills they possess. Interactive Perception of Articulated Objects for Autonomous Manipulation Dov Katz, This thesis develops robotic skills for manipulating novel articulated objects.
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 high degree of immersion will be achieved by multimodal human-exoskeleton interaction based on haptic effects, audio and three- dimensional visualization.
Such generic AI priors are useful because they apply to perception scenarios where there is no robot, such as image classification. Adaptive Balancing of Exploitation with Exploration to Improve Protein Structure Prediction TJ Brunette, The most significant impediment for protein structure prediction is the inadequacy of conformation space search.
I study the role of these priors for learning perception. To achieve general autonomy and applicability in the real world, robots must possess such skills.
Efficient Motion Planning for Intuitive Task Execution in Modular Manipulation Systems Markus Rickert, Mai Computationally efficient motion planning mus avoid exhaustive exploration of high-dimensional configuration spaces by leveraging the structure present in real-world planning problems. Not surprisingly, state-of-the-art structure prediction methods heavily rely on information.
By making these priors explicit, we can see that currently used priors describe the world from the perspective of a passive disinterested observer.
Although priors play a central role in machine learning, they are often hidden in the details of learning algorithms.
Taken together, the concrete case studies and the abstract explanatory framework enable us to make suggestions on how to relax the previously stated assumptions and how to design more effective solutions to robot reinforcement learning problems.Natalie Freed, “This is the fluffy robot that only speaks french”: Language use between preschoolers, their families, and a social robot while sharing virtual toys.
S. M. Media Arts and Sciences, MIT. Adam Setapen, Creating Robotic Characters for Long-Term Interaction., S. M. Media Arts and Sciences, MIT. This thesis will examine the effectiveness of an after school robotics workshop in promoting a deeper understanding of science and engineering, while allowing for its participants to make concrete constructions based on personal interest.
Robotics is a vast field and it is not fair to assume a particular project is cool or more interesting than other.
The projects to develop space robotics is equally interesting as. 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.
H. Grimmett, “Introspective Classification for Robot Perception and Decision Making,” PhD Thesis, Oxford, United Kingdom, Thesis "Path Planning and Obstacle Avoidance in Mobile Robots," Thesis by Saurabh Sarkar "A Heuristic Flight Path Planner for a Small AGV," by Manohar Balapa.Download