# User Study Exploring the Role of Explanation of Failures by Robots in Human Robot Collaboration Tasks

arXiv: https://arxiv.org/abs/2303.16010 · HTML: https://mlsanity.com/paper/2303.16010/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Mar 2023.

## Built on by (most cited first, 6 of 6)

- [REFLECT: Summarizing Robot Experiences for Failure Explanation and Correction](https://mlsanity.com/paper/2306.15724/) (2023)
- [I-FailSense: Towards General Robotic Failure Detection with Vision-Language Models](https://mlsanity.com/paper/2509.16072/) (2025)
- [LaGEA: Language Guided Embodied Agents for Robotic Manipulation](https://mlsanity.com/paper/2509.23155/) (2025)
- [KITE: Keyframe-Indexed Tokenized Evidence for VLM-Based Robot Failure Analysis](https://mlsanity.com/paper/2604.07034/) (2026)
- [Safe Embodied AI for Long-horizon Tasks: A Cross-layer Analysis of Robotic Manipulation](https://mlsanity.com/paper/2606.05660/) (2026)
- [Adapting Robot's Explanation for Failures Based on Observed Human Behavior in Human-Robot Collaboration](https://mlsanity.com/paper/2504.09717/) (2025)

## Abstract (arXiv)

Despite great advances in what robots can do, they still experience failures in human-robot collaborative tasks due to high randomness in unstructured human environments. Moreover, a human's unfamiliarity with a robot and its abilities can cause such failures to repeat. This makes the ability to failure explanation very important for a robot. In this work, we describe a user study that incorporated different robotic failures in a human-robot collaboration (HRC) task aimed at filling a shelf. We included different types of failures and repeated occurrences of such failures in a prolonged interaction between humans and robots. The failure resolution involved human intervention in form of human-robot bidirectional handovers. Through such studies, we aim to test different explanation types and explanation progression in the interaction and record humans.