To facilitate automated bin picking when parts cannot be grasped, pushing actions have the
potential to separate objects and move them away from bin walls and corners. In the context …

Creating robots that can act autonomously in dynamic unstructured environments requires
dealing with novel objects. Thus, an offline learning phase is not sufficient for recognizing …

We propose a novel method for a robot to separate and segment objects in a cluttered
tabletop environment. The method leverages the fact that external object boundaries …

Creating robots that can act autonomously in dynamic, unstructured environments is a major
challenge. In such environments, learning to recognize and manipulate novel objects is an …

Robots usually carry out object segmentation and modeling passively. Sensors such as
cameras are actuated by a robot without disturbing objects in the scene. In this paper, we …

This paper describes a robotic system that learns visual models of symmetric objects
autonomously. Our robot learns by physically interacting with an object using its end effector …

Recognition and manipulation of novel objects in human environments are a prerequisite for
many tasks of robots. Since objects often occur in clutter, such robots should be capable of …

When operating in unstructured and semi-structured environments such as warehouses,
homes, and retail centers, robots are frequently required to interactively search for and …

The ability of robots to perform tasks in human environments has largely been limited to
rather simple and specific tasks, such as lawn mowing and vacuum cleaning. As such …

The goal of this dissertation is to enhance the ability of robots to learn how to manipulate
objects with which they may have no prior experience. Specifically we desire robots to …