Abstract Behavior Trees (BTs) were invented as a tool to enable modular AI in computer
games, but have received an increasing amount of attention in the robotics community in the …

Locomotion has seen dramatic progress for walking or running across challenging terrains.
However, robotic quadrupeds are still far behind their biological counterparts, such as dogs …

Robots are expected to play an important role in future construction work. However, they are
not yet widely adopted by the industry because it is difficult and expensive to program robots …

For robots to seamlessly interact with humans, we first need to make sure that humans and
robots understand one another. Diverse algorithms have been developed to enable robots …

Modern industrial applications require robots to operate in unpredictable environments, and
programs to be created with a minimal effort, to accommodate frequent changes to the task …

As autonomous robots continue to be deployed near people, robots need to be able to
explain their actions. In this article, we focus on organizing and representing complex tasks …

We address the problem of learning Hierarchical Task Networks (HTNs) from unannotated
task demonstrations, while retaining action execution preferences present in the …

The increased popularity of Behavior Trees (BTs) in different fields of robotics requires
efficient methods for learning BTs from data instead of tediously handcrafting them. Recent …

Recent advancements in physics-based character animation leverage deep learning to
generate agile and natural motion, enabling characters to execute movements such as …

This paper develops an automatic online Behavior Tree (BT) synthesis and execution
technique to guide an autonomous agent to accomplish a series of missions expressed in …