72 citations · 102 across the 7 of their papers we have counts for
6 papers · 1 filter
LeTS-Drive: Driving in a Crowd by Learning from Tree Search
Panpan Cai, Yuanfu Luo, Aseem Saxena +2
Autonomous driving in a crowded environment, e.g., a busy traffic intersection, is an unsolved challenge for robotics. The robot vehicle must contend with a dynamic and partially o…
Guided Exploration of Human Intentions for Human-Robot Interaction
Min Chen, David Hsu, Wee Sun Lee
Robot understanding of human intentions is essential for fluid human-robot interaction. Intentions, however, cannot be directly observed and must be inferred from behaviors. We lea…
Integrating Algorithmic Planning and Deep Learning for Partially Observable Navigation
Peter Karkus, David Hsu, Wee Sun Lee
We propose to take a novel approach to robot system design where each building block of a larger system is represented as a differentiable program, i.e. a deep neural network. This…
PORCA: Modeling and Planning for Autonomous Driving among Many Pedestrians
Yuanfu Luo, Panpan Cai, Aniket Bera +3
This paper presents a planning system for autonomous driving among many pedestrians. A key ingredient of our approach is PORCA, a pedestrian motion prediction model that accounts f…
Particle Filter Networks with Application to Visual Localization
Peter Karkus, David Hsu, Wee Sun Lee
Particle filtering is a powerful approach to sequential state estimation and finds application in many domains, including robot localization, object tracking, etc. To apply particl…
Learning Dynamic Robot-to-Human Object Handover from Human Feedback
Andras Kupcsik, David Hsu, Wee Sun Lee
Object handover is a basic, but essential capability for robots interacting with humans in many applications, e.g., caring for the elderly and assisting workers in manufacturing wo…