Building general-purpose robots that operate seamlessly in any environment, with any
object, and utilizing various skills to complete diverse tasks has been a long-standing goal in …

Pushing and grasping are fundamental actions in robotic manipulation, applicable across
diverse fields ranging from industrial automation to assistive robotics. Robotic arm faces …

In this work, we present methods for using human-robot dialog to improve language
understanding for a mobile robot agent. The agent parses natural language to underlying …

Humans leverage multiple sensor modalities when interacting with objects and discovering
their intrinsic properties. Using the visual modality alone is insufficient for deriving intuition …

A holistic understanding of object properties across diverse sensory modalities (eg, visual,
audio, and haptic) is essential for tasks ranging from object categorization to complex …

Humans learn about objects via interaction and using multiple perceptions, such as vision,
sound, and touch. While vision can provide information about an object's appearance, non …

From an early age, humans learn to develop an intuition for the physical nature of the
objects around them by using exploratory behaviors. Such exploration provides …

Humans learn about object properties using multiple modes of perception. Recent advances
show that robots can use non-visual sensory modalities (ie, haptic and tactile sensory data) …

The basis for robotics skill learning is an adequate representation of manipulation tasks
based on their physical properties. As manipulation tasks are inherently invariant to the …

Predicting future sensory states is crucial for learning agents such as robots, drones, and
autonomous vehicles. In this paper, we couple multiple sensory modalities with exploratory …