HRI 2024
Expertise Robot Task Representation
Behavior Trees (BTs)
THRI, 2023
Communicating Missing Causal Information to Explain a Robot’s Past Behavior
Robots need to explain their behavior to gain trust. Existing research has focused on explaining a robot’s current behavior, yet it remains unknown yet challenging how to provide explanations of past actions in an environment that might change after a robot’s actions, leading to critical missing causal information due to moved objects. We conducted… Continue reading Communicating Missing Causal Information to Explain a Robot’s Past Behavior
AI-HRI 2022
Mixed-Reality Robot Behavior Replay: A System Implementation
As robots become increasingly complex, they must explain their behaviors to gain trust and acceptance. However, it may be difficult through verbal explanation alone to fully convey information about past behavior, especially regarding objects no longer present due to robots’ or humans’ actions. Humans often try to physically mimic past movements to accompany verbal… Continue reading Mixed-Reality Robot Behavior Replay: A System Implementation
WYSD 2022
“Why Didn’t I Do It?” A Study Design to Evaluate Robot Explanations
As robot systems are becoming ubiquitous in more complex tasks, there is a pressing need for robots to be able to explain their behaviors in order to gain trust and acceptance. In this paper, we discuss our plan for an online human subjects study to evaluate our new system for explanation generation. Specifically, the… Continue reading “Why Didn’t I Do It?” A Study Design to Evaluate Robot Explanations
THRI, 2021
Building The Foundation of Robot Explanation Generation Using Behavior Trees
As autonomous robots continue to be deployed near people, robots need to be able to explain their actions. In this paper, we focus on organizing and representing complex tasks in a way that makes them readily explainable. Many actions consist of sub-actions, each of which may have several sub-actions of their own, and the… Continue reading Building The Foundation of Robot Explanation Generation Using Behavior Trees