6 accepted papers
Offroad mobile robot perception systems must be able to learn robust terrain classification models. Models built from computer vision often fail in their ability to generalize to new environments where appearance characteristics change. Sound and vibration signals from robot-terrain interaction can…
We propose a language-driven navigation approach for commanding mobile robots in outdoor environments. We consider unknown environments that contain previously unseen objects. The proposed approach aims at making interactions in human-robot teams natural. Robots receive from human teammates commands…
Robot perception is generally viewed as the interpretation of data from various types of sensors such as cameras. In this paper, we study indirect perception where a robot can perceive new information by making inferences from non-visual observations of human teammates. As a proof-of-concept study,…
A key challenge of developing robots that work closely with people is creating a user interface that allows a user to communicate complex instructions to a robot quickly and easily. We consider a walking logistics support robot, which is designed to carry heavy loads to locations that are too diffic…
Natural language offers an intuitive and flexible means for humans to communicate with the robots that we will increasingly work alongside in our homes and workplaces. Recent advancements have given rise to robots that are able to interpret natural language manipulation and navigation commands, but…
High-mobility walking robots offer unique capabilities in complex off-road environments where wheeled vehicles are not able to travel. However, these environments can also pose significant autonomous navigation challenges. Key steps in planning a safe path for the robot autonomously include estimati…