9 accepted papers
As robots become more integrated into shared work environments, effective communication must balance clear task directives with social engagement to support both efficiency and user satisfaction. This letter examines how people perceive task-oriented versus social dialogue during human–robot collabo
For effective human-robot collaboration, a robot must align its actions with human goals, even as they change mid-task. Prior approaches often assume fixed goals, reducing goal prediction to a one-time inference. However, in real-world scenarios, humans frequently shift goals, making it challenging
We present SEAN 2.0, an open-source system designed to advance social navigation via the training and benchmarking of navigation policies in varied social contexts. A key limitation of current social navigation research is that policies are often trained and evaluated considering only a few social c
Evaluation of social robot navigation inherently requires human input due to its qualitative nature. Motivated by the need to scale human evaluation, we propose a general method for deploying interactive, rich-client robotic simulations on the web. Prior approaches implement specific web- compatible…
We study human perception of gaze rendered by popular semi-virtual robotic heads, which use a screen to render a robot's face. It is known that when these heads are stationary, the screen may induce the Mona Lisa gaze effect, which widens the robot's apparent cone of direct gaze. But how do people p…
We propose a method to facilitate robot navigation relative to sketched maps of human environments. Our main contribution centers around using thin plate splines for registering the robot's LIDAR observation with the hand-drawn maps. Thin plate splines are particularly effective for this task becaus…
We present a navigation system that combines ideas from hierarchical planning and machine learning. The system uses a traditional global planner to compute optimal paths towards a goal, and a deep local trajectory planner and velocity controller to compute motion commands. The latter components of t…
We present semi-supervised deep learning approaches for traversability estimation from fisheye images. Our method, GONet, and the proposed extensions leverage Generative Adversarial Networks (GANs) to effectively predict whether the area seen in the input image(s) is safe for a robot to traverse. Th…
Appropriate robot behavior in public, open spaces cannot occur without the ability to automatically detect conversational groups of free-standing people. To this end, we propose an alternating optimization procedure that estimates lower body orientations and detects groups of interacting people. The…