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Explanations constitute an important aspect of successful human robot interactions and can enhance robot understanding. To improve the understanding of the robot, we have developed four levels of explanation (LOE) based on two questions:…

Robotics · Computer Science 2025-01-22 Shikhar Kumar , Yael Edan

Human-robot interactive decision-making is increasingly becoming ubiquitous, and trust is an influential factor in determining the reliance on autonomy. However, it is not reasonable to trust systems that are beyond our comprehension, and…

Machine Learning · Computer Science 2021-08-16 Daoming Lyu , Fangkai Yang , Hugh Kwon , Wen Dong , Levent Yilmaz , Bo Liu

We develop a natural language interface for human robot interaction that implements reasoning about deep semantics in natural language. To realize the required deep analysis, we employ methods from cognitive linguistics, namely the modular…

Artificial Intelligence · Computer Science 2016-04-25 Manfred Eppe , Sean Trott , Jerome Feldman

Inspired by the increased cooperation between humans and autonomous systems, we present a new hybrid systems framework capturing the interconnected dynamics underlying these interactions. The framework accommodates models arising from both…

Robotics · Computer Science 2025-10-13 Daniel A. Williams , Airlie Chapman , Chris Manzie

For safe and effective operation of humanoid robots in human-populated environments, the problem of commanding a large number of Degrees of Freedom (DoF) while simultaneously considering dynamic obstacles and human proximity has still not…

Robotics · Computer Science 2024-12-12 Jakub Rozlivek , Alessandro Roncone , Ugo Pattacini , Matej Hoffmann

In this work, we present a domain-independent approach for adaptive scaffolding in robotic explanation generation to guide tasks in human-robot interaction. We present a method for incorporating interdisciplinary research results into a…

Human-Computer Interaction · Computer Science 2025-10-28 André Groß , Birte Richter , Britta Wrede

In human-robot collaboration (HRC), robots must adapt online to dynamic task constraints and evolving human intent. While physical corrections provide a natural, low-latency channel for operators to convey motion-level adjustments,…

Robotics · Computer Science 2026-03-13 Jiurun Song , Xiao Liang , Minghui Zheng

While autonomous multi-robots can achieve safe and coordinated navigation, they often struggle to adapt to unforeseen conditions and to capture operator-driven objectives in unstructured environments. We present a Virtual Reality (VR)-based…

This paper suggests an integrated navigation system for an unmanned ground vehicle operating in an unknown cluttered environment. The navigator supports time-critical mobility making it possible for a mobile robot to reach a target from the…

Robotics · Computer Science 2018-08-28 Ahmad A. Masoud , Ali Al-Shaikhi

This paper introduces a system designed to generate explanations for the actions performed by an autonomous robot in Human-Robot Interaction (HRI). Explainability in robotics, encapsulated within the concept of an eXplainable Autonomous…

For legged robots to perform agile, highly dynamic and contact-rich motions, whole-body trajectories computation of under-actuated complex systems subject to non-linear dynamics is required. In this work, we present hands-on applications of…

Robotics · Computer Science 2022-06-20 Francesco Ruscelli , Arturo Laurenzi , Nikos G. Tsagarakis , Enrico Mingo Hoffman

In human-robot collaboration, the objectives of the human are often unknown to the robot. Moreover, even assuming a known objective, the human behavior is also uncertain. In order to plan a robust robot behavior, a key preliminary question…

Robotics · Computer Science 2023-02-28 Yang You , Vincent Thomas , Francis Colas , Rachid Alami , Olivier Buffet

Effective collaboration between a robot and a person requires natural communication. When a robot travels with a human companion, the robot should be able to explain its navigation behavior in natural language. This paper explains how a…

Artificial Intelligence · Computer Science 2017-09-29 Raj Korpan , Susan L. Epstein , Anoop Aroor , Gil Dekel

Robots with a high level of autonomy are increasingly requested by smart industries. A way to reduce the workers' stress and effort is to optimize the working environment by taking advantage of autonomous collaborative robots. A typical…

As artificial intelligence systems increasingly operate in Real-world environments, the integration of multi-modal data sources such as vision, language, and audio presents both unprecedented opportunities and critical challenges for…

Machine Learning · Computer Science 2025-07-01 Sree Bhargavi Balija

Humans seamlessly fuse anticipatory planning with immediate feedback to perform successive mobile manipulation tasks without stopping, achieving both high efficiency and reliability. Replicating this fluid and reliable behavior in robots…

Explainability in AI and ML models is critical for fostering trust, ensuring accountability, and enabling informed decision making in high stakes domains. Yet this objective is often unmet in practice. This paper proposes a general purpose…

Statistical Finance · Quantitative Finance 2025-09-03 N. Jean , G. Le Pera

Humanoid robots have shown success in locomotion and manipulation. Despite these basic abilities, humanoids are still required to quickly understand human instructions and react based on human interaction signals to become valuable…

The current transformation towards smart manufacturing has led to a growing demand for human-robot collaboration (HRC) in the manufacturing process. Perceiving and understanding the human co-worker's behaviour introduces challenges for…

Robotics · Computer Science 2023-05-18 Zheyu Zhuang , Yizhak Ben-Shabat , Jiahao Zhang , Stephen Gould , Robert Mahony

We present Logical Robots, an interactive multi-agent simulation platform where autonomous robot behavior is specified declaratively in the logic programming language Logica. Robot behavior is defined by logical predicates that map…

Multiagent Systems · Computer Science 2026-04-09 Evgeny Skvortsov , Yilin Xia , Ojaswa Garg , Shawn Bowers , Bertram Ludäscher
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