Using robots to harvest sweet peppers in protected crop** environments has remained
unsolved despite considerable effort by the research community over several decades. In …

This paper introduces a method for learning the force response of heterogeneous,
deformable objects directly from robot sensor data without prior knowledge. The method …

A key challenge for haptically reaching in dense clutter is the frequent contact that can occur
between the robot's arm and the environment. We have previously used single-time-step …

When making contact with an object, a robot can use a tactile sensor consisting of a heating
element and a temperature sensor to recognize the object's material based on conductive …

When operating in human environments, such as homes, robots could use tactile sensing to
better perceive objects. A challenge that has not been sufficiently addressed is the influence …

For humans and robots to collaborate effectively as teammates in unstructured
environments, robots must be able to construct semantically rich models of the environment …

We present a controller that allows an armlike manipulator to navigate deformable cloth
garments in simulation through the use of haptic information. The main challenge of such a …

We address the problem of robot motion planning under uncertainty where the only
observations are through contact with the environment. Such problems are typically solved …

It is difficult for robots to retrieve objects in densely cluttered lateral access scenes with
movable objects as jamming against adjacent objects and walls can inhibit progress. We …

We address the problem of robot motion planning under uncertainty where the only
observations are through contact with the environment. Such problems are typically solved …