Expertise Explainable AI (XAI)

Robot Explanation

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

Published

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

Published

WYSD 2022

“Why Didn’t I Do It?” A Study Design to Evaluate Robot Explanations

The “detect screw” subtree with Assumption Checker nodes (prefixed C, green names) and Action nodes (prefixed A, white names). The root RetryUntilSuccessful node retries the subtree up to three times if a failure or assumption violation occurs. The ReactiveSequenceNode asynchronously runs all actions including “lift torso”, “look at table”, and “detect screw” while continuously checking the assumption, “check updated head3DCamera”. An example of pre and post-conditions can be seen before and after the “detect screw” action.

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

Published

AAAI-SSS 2022

Causal Robot Communication Inspired by Observational Learning Insights

Autonomous robots must communicate about their decisions to gain trust and acceptance. When doing so, robots must determine which actions are causal, i.e., which directly give rise to the desired outcome, so that these actions can be included in explanations. In behavior learning in psychology, this sort of reasoning during an action sequence has… Continue reading Causal Robot Communication Inspired by Observational Learning Insights

Published

HRI 2022

Teacher, Teammate, Subordinate, Friend: Generating Norm Violation Responses Grounded in Role-based Relational Norms

Robot ethics

Language-capable robots require moral competence, including representations and algorithms for moral reasoning and moral communication. We argue for an ethical pluralist approach to moral competence that leverages and combines disparate ethical frameworks, and specifically argue for an approach to moral competence that is grounded not only in Deontological norms (as is typical in the… Continue reading Teacher, Teammate, Subordinate, Friend: Generating Norm Violation Responses Grounded in Role-based Relational Norms

Published

Ph.D. Dissertation

Robot Explanations: Preferences, Generation, and Communication

Zhao Han's PhD dissertation defense presentation: first slide

During the last decade, robots have become increasingly ubiquitous. They have been moved outside of laboratories and deployed to environments where they have to interact with humans. Examples include public places such as warehouses, hotels, factories, retail stores, and streets, as well as the most anticipated places—private homes. In these increasingly unstructured environments, requirements… Continue reading Robot Explanations: Preferences, Generation, and Communication

Published

THRI, 2021

The Need for Verbal Robot Explanations and How People Would Like a Robot To Explain Itself

Robot explanation, robot failure

Although non-verbal cues such as arm movement and eye gaze can convey robot intention, they alone may not provide enough information for a human to fully understand a robot’s behavior. To better understand how to convey robot intention, we conducted an experiment (N = 366) investigating the need for robots to explain, and the… Continue reading The Need for Verbal Robot Explanations and How People Would Like a Robot To Explain Itself

Published

THRI, 2021

Building The Foundation of Robot Explanation Generation Using Behavior Trees

Behavior tree, robot task representation

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

Published

ICRA 2020 WS

Reasons People Want Explanations After Unrecoverable Pre-Handover Failures

Codes for explanation reasoning. Shown are those that appeared more than 12 times.

Most research on human-robot handovers focuses on the development of comfortable and efficient HRI; few have studied handover failures. If a failure occurs in the beginning of the interaction, it prevents the whole handover process and destroys trust. Here we analyze the underlying reasons why people want explanations in a handover scenario where a… Continue reading Reasons People Want Explanations After Unrecoverable Pre-Handover Failures

Published

AI-HRI 2019

Towards A Robot Explanation System: A Survey and Our Approach to State Summarization, Storage and Querying, and Human Interface

The workflow of the robot explanation system.

As robot systems become more ubiquitous, developing understandable robot systems becomes increasingly important in order to build trust. In this paper, we present an approach to developing a holistic robot explanation system, which consists of three interconnected components: state summarization, storage and querying, and human interface. To find trends towards and gaps in the… Continue reading Towards A Robot Explanation System: A Survey and Our Approach to State Summarization, Storage and Querying, and Human Interface

Published