Iolanda Leite
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View article: Social 3D Scene Graphs: Modeling Human Actions and Relations for Interactive Service Robots
Social 3D Scene Graphs: Modeling Human Actions and Relations for Interactive Service Robots Open
Understanding how people interact with their surroundings and each other is essential for enabling robots to act in socially compliant and context-aware ways. While 3D Scene Graphs have emerged as a powerful semantic representation for sce…
View article: Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games Open
Reinforcement Learning (RL) in games has gained significant momentum in recent years, enabling the creation of different agent behaviors that can transform a player's gaming experience. However, deploying RL agents in production environmen…
View article: FLoRA: Sample-Efficient Preference-based RL via Low-Rank Style Adaptation of Reward Functions
FLoRA: Sample-Efficient Preference-based RL via Low-Rank Style Adaptation of Reward Functions Open
Preference-based reinforcement learning (PbRL) is a suitable approach for style adaptation of pre-trained robotic behavior: adapting the robot's policy to follow human user preferences while still being able to perform the original task. H…
View article: Expectations, Explanations, and Embodiment: Attempts at Robot Failure Recovery
Expectations, Explanations, and Embodiment: Attempts at Robot Failure Recovery Open
Expectations critically shape how people form judgments about robots, influencing whether they view failures as minor technical glitches or deal-breaking flaws. This work explores how high and low expectations, induced through brief video …
View article: BT-ACTION: A Test-Driven Approach for Modular Understanding of User Instruction Leveraging Behaviour Trees and LLMs
BT-ACTION: A Test-Driven Approach for Modular Understanding of User Instruction Leveraging Behaviour Trees and LLMs Open
Natural language instructions are often abstract and complex, requiring robots to execute multiple subtasks even for seemingly simple queries. For example, when a user asks a robot to prepare avocado toast, the task involves several sequen…
View article: Long-Term Planning Around Humans in Domestic Environments with 3D Scene Graphs
Long-Term Planning Around Humans in Domestic Environments with 3D Scene Graphs Open
Long-term planning for robots operating in domestic environments poses unique challenges due to the interactions between humans, objects, and spaces. Recent advancements in trajectory planning have leveraged vision-language models (VLMs) t…
View article: Humans Coexist, So Must Embodied Artificial Agents
Humans Coexist, So Must Embodied Artificial Agents Open
This paper introduces the concept of coexistence for embodied artificial agents and argues that it is a prerequisite for long-term, in-the-wild interaction with humans. Contemporary embodied artificial agents excel in static, predefined ta…
View article: What Can You Say to a Robot? Capability Communication Leads to More Natural Conversations
What Can You Say to a Robot? Capability Communication Leads to More Natural Conversations Open
When encountering a robot in the wild, it is not inherently clear to human users what the robot's capabilities are. When encountering misunderstandings or problems in spoken interaction, robots often just apologize and move on, without add…
View article: STREAK: Streaming Network for Continual Learning of Object Relocations under Household Context Drifts
STREAK: Streaming Network for Continual Learning of Object Relocations under Household Context Drifts Open
In real-world settings, robots are expected to assist humans across diverse tasks and still continuously adapt to dynamic changes over time. For example, in domestic environments, robots can proactively help users by fetching needed object…
View article: A Model-Agnostic Approach for Semantically Driven Disambiguation in Human-Robot Interaction
A Model-Agnostic Approach for Semantically Driven Disambiguation in Human-Robot Interaction Open
Ambiguities are inevitable in human-robot interaction, especially when a robot follows user instructions in a large, shared space. For example, if a user asks the robot to find an object in a home environment with underspecified instructio…
View article: The 1st InterAI Workshop: Interactive AI for Human-centered Robotics
The 1st InterAI Workshop: Interactive AI for Human-centered Robotics Open
The workshop is affiliated with 33nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN 2024) August 26~30, 2023 / Pasadena, CA, USA. It is designed as a half-day event, extending over four hours from 9:00 t…
View article: HRI Wasn’t Built In a Day: A Call To Action For Responsible HRI Research
HRI Wasn’t Built In a Day: A Call To Action For Responsible HRI Research Open
In recent years, the awareness of the academy around responsible research has notably increased. For instance, with advances in machine learning and artificial intelligence, recent efforts have been made to promote ethical, fair, and inclu…
View article: Let’s move on: Topic Change in Robot-Facilitated Group Discussions
Let’s move on: Topic Change in Robot-Facilitated Group Discussions Open
Robot-moderated group discussions have the potential to facilitate engaging and productive interactions among human participants. Previous work on topic management in conversational agents has predominantly focused on human engagement and …
View article: Join Me Here if You Will: Investigating Embodiment and Politeness Behaviors When Joining Small Groups of Humans, Robots, and Virtual Characters
Join Me Here if You Will: Investigating Embodiment and Politeness Behaviors When Joining Small Groups of Humans, Robots, and Virtual Characters Open
Politeness and embodiment are pivotal elements in human-agent interactions. While many previous works advocate the positive role of embodiment in enhancing these interactions, it remains unclear how embodiment and politeness affect individ…
View article: Drone Fail Me Now: How Drone Failures Affect Trust and Risk-Taking Decisions
Drone Fail Me Now: How Drone Failures Affect Trust and Risk-Taking Decisions Open
So far, research on drone failures has been mostly limited to understanding the technical causes of failures and recovery strategies. In contrast, there is little work looking at how failures of drones are perceived by users. To address th…
View article: PREDILECT: Preferences Delineated with Zero-Shot Language-based Reasoning in Reinforcement Learning
PREDILECT: Preferences Delineated with Zero-Shot Language-based Reasoning in Reinforcement Learning Open
Preference-based reinforcement learning (RL) has emerged as a new field in\nrobot learning, where humans play a pivotal role in shaping robot behavior by\nexpressing preferences on different sequences of state-action pairs. However,\nformu…
View article: Interaction-Shaping Robotics: Robots That Influence Interactions between Other Agents
Interaction-Shaping Robotics: Robots That Influence Interactions between Other Agents Open
Work in Human–Robot Interaction (HRI) has investigated interactions between one human and one robot as well as human–robot group interactions. Yet the field lacks a clear definition and understanding of the influence a robot can exert on i…
View article: How do Humans take an Object from a Robot: Behavior changes observed in a User Study
How do Humans take an Object from a Robot: Behavior changes observed in a User Study Open
To facilitate human-robot interaction and gain human trust, a robot should\nrecognize and adapt to changes in human behavior. This work documents different\nhuman behaviors observed while taking objects from an interactive robot in an\nexp…
View article: Multi-modal Affect Detection Using Thermal and Optical Imaging in a Gamified Robotic Exercise
Multi-modal Affect Detection Using Thermal and Optical Imaging in a Gamified Robotic Exercise Open
Affect recognition, or the ability to detect and interpret emotional states, has the potential to be a valuable tool in the field of healthcare. In particular, it can be useful in gamified therapy, which involves using gaming techniques to…
View article: Generating Scenarios from High-Level Specifications for Object Rearrangement Tasks
Generating Scenarios from High-Level Specifications for Object Rearrangement Tasks Open
Rearranging objects is an essential skill for robots. To quickly teach robots new rearrangements tasks, we would like to generate training scenarios from high-level specifications that define the relative placement of objects for the task …
View article: Persuasive Polite Robots in Free-Standing Conversational Groups
Persuasive Polite Robots in Free-Standing Conversational Groups Open
Politeness is at the core of the common set of behavioral norms that regulate human communication and is therefore of significant interest in the design of Human-Robot Interactions. In this paper, we investigate how the politeness behavior…
View article: Effects of Explanation Strategies to Resolve Failures in Human-Robot Collaboration
Effects of Explanation Strategies to Resolve Failures in Human-Robot Collaboration Open
Despite significant improvements in robot capabilities, they are likely to fail in human-robot collaborative tasks due to high unpredictability in human environments and varying human expectations. In this work, we explore the role of expl…
View article: A Systematic Review on Reproducibility in Child-Robot Interaction
A Systematic Review on Reproducibility in Child-Robot Interaction Open
Research reproducibility - i.e., rerunning analyses on original data to replicate the results - is paramount for guaranteeing scientific validity. However, reproducibility is often very challenging, especially in research fields where mult…
View article: Sounding Robots: Design and Evaluation of Auditory Displays for Unintentional Human-robot Interaction
Sounding Robots: Design and Evaluation of Auditory Displays for Unintentional Human-robot Interaction Open
Non-verbal communication is important in HRI, particularly when humans and robots do not need to actively engage in a task together, but rather they co-exist in a shared space. Robots might still need to communicate states such as urgency …
View article: Can the robot “see” what I see? Robot gaze drives attention depending on mental state attribution
Can the robot “see” what I see? Robot gaze drives attention depending on mental state attribution Open
Mentalizing, where humans infer the mental states of others, facilitates understanding and interaction in social situations. Humans also tend to adopt mentalizing strategies when interacting with robotic agents. There is an ongoing debate …
View article: Robotics: Science and Systems XIX
Robotics: Science and Systems XIX Open
We focus on correct-by-design robot task planning from finite Linear Temporal Logic (LTL f ) specifications with a human in the loop.Since provable guarantees are difficult to obtain unconditionally, we take an assume-guarantee perspective…
View article: Follow my Advice: Assume-Guarantee Approach to Task Planning with Human in the Loop
Follow my Advice: Assume-Guarantee Approach to Task Planning with Human in the Loop Open
We focus on correct-by-design robot task planning from finite Linear Temporal Logic (LTL f ) specifications with a human in the loop.Since provable guarantees are difficult to obtain unconditionally, we take an assume-guarantee perspective…
View article: Aligning Human Preferences with Baseline Objectives in Reinforcement Learning
Aligning Human Preferences with Baseline Objectives in Reinforcement Learning Open
Practical implementations of deep reinforcement learning (deep RL) have been challenging due to an amplitude of factors, such as designing reward functions that cover every possible interaction. To address the heavy burden of robot reward …
View article: User Study Exploring the Role of Explanation of Failures by Robots in Human Robot Collaboration Tasks
User Study Exploring the Role of Explanation of Failures by Robots in Human Robot Collaboration Tasks Open
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…
View article: Increasing Perceived Safety in Motion Planning for Human-Drone Interaction
Increasing Perceived Safety in Motion Planning for Human-Drone Interaction Open
Safety is crucial for autonomous drones to operate close to humans. Besides avoiding unwanted or harmful contact, people should also perceive the drone as safe. Existing safe motion planning approaches for autonomous robots, such as drones…