Dana Kulić
Biographic Data
| ID | 1680472 |
|---|---|
| NAME | Dana Kulić |
| GIVEN NAMES | Dana |
| FAMILY NAME | Kulić |
| SIGNATURE | KULIĆ D |
| AFFILIATIONS | Monash University |
| ORCID | 0000-0002-4169-2141 |
| VERIFIED | Yes |
| TOTAL WORKS | 17 |
| TOTAL CITATIONS | 469 |
| WORKS AS AUTHOR | 17 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2008 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 4 |
Consistency Matters
Learning from Demonstration (LfD) empowers robots to acquire new skills through human demonstrations, making it feasible for everyday users to teach robots. However, the success of learning and generalization heavily depends on the quality of these demonstrations. Consistency is often used to indicate quality in LfD, yet the factors that define this consistency remain underexplored. In this article, we evaluate a comprehensive set of motion data …
A Framework for Dynamic Situational Awareness in Human–Robot Teams
In human–robot teams, human situational awareness is the operator’s conscious knowledge of the team’s states, actions, plans and their environment. Appropriate human situational awareness is critical to successful human–robot collaboration. In human–robot teaming, it is often assumed that the best and required level of situational awareness is knowing everything at all times. This view is problematic, because what a human needs to know for optima…
From Novice to Skilled
Multi-task missions for unmanned aerial vehicles (UAVs) involving inspection and landing tasks are challenging for novice pilots due to the difficulties associated with depth perception and the control interface. We propose a shared autonomy system, alongside supplementary information displays, to assist pilots to successfully complete multi-task missions without any pilot training. Our approach comprises of three modules: (1) a perception module…
Human-Robot Team Performance Compared to Full Robot Autonomy in 16 Real-World Search and Rescue Missions
Human operators in human-robot teams are commonly perceived to be critical for mission success. To explore the direct and perceived impact of operator input on task success and team performance, 16 real-world missions (10 h) were conducted based on the DARPA Subterranean Challenge. Missions involved deploying a heterogeneous team of robots to locate and identify artefacts such as climbing rope, drills and a mannequin representing a human survivor…
How Can Everyday Users Efficiently Teach Robots by Demonstration
Learning from Demonstration (LfD) is a framework that allows lay users to easily program robots. However, the efficiency of robot learning and the robot’s ability to generalize to task variations hinge upon the quality and quantity of the provided demonstrations. Our objective is to guide human teachers to provide more effective demonstrations, thus facilitating efficient robot learning. To achieve this, we propose to use a measure of uncertainty…
Adapting a Teachable Robot’s Dialog Responses Using Reinforcement Learning
Teachable robots in education have the ability to increase student engagement and learning through personalised interactions and the use of social behaviours, such as speech, gaze and emotional expressions. Adaptation of these behaviours is motivated by an interest in tailoring the learning experience to an individual user and improving user outcomes. This work proposes an adaptive response-selection algorithm for a teachable robot which aims to …
Contingent autonomy
In this article, we develop a framework for robotic autonomy as contingent. We do so with an account of a series of online research workshops that asked people to design and test robot behaviours for a public space scenario of their choice, as a means to surface and discuss their understandings of robots. We show how, as people manipulated robots in a simulator, they came to understand the capacities and limits of robots in distinctive ways. Thin…
Robotic Vision for Human-Robot Interaction and Collaboration
Robotic vision, otherwise known as computer vision for robots, is a critical process for robots to collect and interpret detailed information related to human actions, goals, and preferences, enabling robots to provide more useful services to people. This survey and systematic review presents a comprehensive analysis on robotic vision in human-robot interaction and collaboration (HRI/C) over the past 10 years. From a detailed search of 3,850 arti…
The robotic production of spatiality
Robots are an increasing presence in our public spaces. Accordingly, in this paper, we make an argument for the importance of understanding how they produce spatiality by developing three robotic logics: predictability, partitioning, and connection. We show how the robotic bias towards orderly categories exists alongside processual accounts of spatiality, and how the forms of anticipatory knowability that robots require play out in the contingent…
Learning to Engage with Interactive Systems
Physical agents that can autonomously generate engaging, life-like behavior will lead to more responsive and user-friendly robots and other autonomous systems. Although many advances have been made for one-to-one interactions in well-controlled settings, physical agents should be capable of interacting with humans in natural settings, including group interaction. To generate engaging behaviors, the autonomous system must first be able to estimate…
Identifying Functions and Behaviours of Social Robots for In-Class Learning Activities
Imagining public space robots of the near-future
Curiosity Did Not Kill the Robot
Learning from human interaction data is a promising approach for developing robot interaction logic, but behaviors learned only from offline data simply represent the most frequent interaction patterns in the training data, without any adaptation for individual differences. We developed a robot that incorporates both data-driven and interactive learning. Our robot first learns high-level dialog and spatial behavior patterns from offline examples …
Robot Expressive Motions
Robots that have different forms and capabilities are used in a wide variety of situations; however, one common point to all robots interacting with humans is their ability to communicate with them. In addition to verbal communication or purely communicative movements, robots can also use their embodiment to generate expressive movements while achieving a task, to convey additional information to its human partner. This article surveys state-of-t…
Automated Rehabilitation System
In current physical rehabilitation protocols, patients typically perform exercises with intermittent feedback or guidance following the initial demonstrations from the physiotherapist. Although many patient-centered systems have been developed for home rehabilitation, few systems have been developed to aid the physiotherapist as well as patients in the rehabilitation clinic. This article proposes the Automated Rehabilitation System (ARS), a syste…
Perception and Generation of Affective Hand Movements
Measurement Instruments for the Anthropomorphism, Animacy, Likeability, Perceived Intelligence, and Perceived Safety of Robots
This study emphasizes the need for standardized measurement tools for human robot interaction (HRI). If we are to make progress in this field then we must be able to compare the results from different studies. A literature review has been performed on the measurements of five key concepts in HRI: anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety. The results have been distilled into five consistent questionnaire…
Measurement Instruments for the Anthropomorphism, Animacy, Likeability, Perceived Intelligence, and Perceived Safety of Robots
This study emphasizes the need for standardized measurement tools for human robot interaction (HRI). If we are to make progress in this field then we must be able to compare the results from different studies. A literature review has been performed on the measurements of five key concepts in HRI: anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety. The results have been distilled into five consistent questionnaire…
Imagining public space robots of the near-future
Robot Expressive Motions
Robots that have different forms and capabilities are used in a wide variety of situations; however, one common point to all robots interacting with humans is their ability to communicate with them. In addition to verbal communication or purely communicative movements, robots can also use their embodiment to generate expressive movements while achieving a task, to convey additional information to its human partner. This article surveys state-of-t…
The robotic production of spatiality
Robots are an increasing presence in our public spaces. Accordingly, in this paper, we make an argument for the importance of understanding how they produce spatiality by developing three robotic logics: predictability, partitioning, and connection. We show how the robotic bias towards orderly categories exists alongside processual accounts of spatiality, and how the forms of anticipatory knowability that robots require play out in the contingent…
Contingent autonomy
In this article, we develop a framework for robotic autonomy as contingent. We do so with an account of a series of online research workshops that asked people to design and test robot behaviours for a public space scenario of their choice, as a means to surface and discuss their understandings of robots. We show how, as people manipulated robots in a simulator, they came to understand the capacities and limits of robots in distinctive ways. Thin…
Identifying Functions and Behaviours of Social Robots for In-Class Learning Activities
Curiosity Did Not Kill the Robot
Learning from human interaction data is a promising approach for developing robot interaction logic, but behaviors learned only from offline data simply represent the most frequent interaction patterns in the training data, without any adaptation for individual differences. We developed a robot that incorporates both data-driven and interactive learning. Our robot first learns high-level dialog and spatial behavior patterns from offline examples …
Measurement Instruments for the Anthropomorphism, Animacy, Likeability, Perceived Intelligence, and Perceived Safety of Robots
This study emphasizes the need for standardized measurement tools for human robot interaction (HRI). If we are to make progress in this field then we must be able to compare the results from different studies. A literature review has been performed on the measurements of five key concepts in HRI: anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety. The results have been distilled into five consistent questionnaire…
Perception and Generation of Affective Hand Movements
Automated Rehabilitation System
In current physical rehabilitation protocols, patients typically perform exercises with intermittent feedback or guidance following the initial demonstrations from the physiotherapist. Although many patient-centered systems have been developed for home rehabilitation, few systems have been developed to aid the physiotherapist as well as patients in the rehabilitation clinic. This article proposes the Automated Rehabilitation System (ARS), a syste…
Curiosity Did Not Kill the Robot
Learning from human interaction data is a promising approach for developing robot interaction logic, but behaviors learned only from offline data simply represent the most frequent interaction patterns in the training data, without any adaptation for individual differences. We developed a robot that incorporates both data-driven and interactive learning. Our robot first learns high-level dialog and spatial behavior patterns from offline examples …
Robot Expressive Motions
Robots that have different forms and capabilities are used in a wide variety of situations; however, one common point to all robots interacting with humans is their ability to communicate with them. In addition to verbal communication or purely communicative movements, robots can also use their embodiment to generate expressive movements while achieving a task, to convey additional information to its human partner. This article surveys state-of-t…
Learning to Engage with Interactive Systems
Physical agents that can autonomously generate engaging, life-like behavior will lead to more responsive and user-friendly robots and other autonomous systems. Although many advances have been made for one-to-one interactions in well-controlled settings, physical agents should be capable of interacting with humans in natural settings, including group interaction. To generate engaging behaviors, the autonomous system must first be able to estimate…
Identifying Functions and Behaviours of Social Robots for In-Class Learning Activities
Imagining public space robots of the near-future
The robotic production of spatiality
Robots are an increasing presence in our public spaces. Accordingly, in this paper, we make an argument for the importance of understanding how they produce spatiality by developing three robotic logics: predictability, partitioning, and connection. We show how the robotic bias towards orderly categories exists alongside processual accounts of spatiality, and how the forms of anticipatory knowability that robots require play out in the contingent…
Robotic Vision for Human-Robot Interaction and Collaboration
Robotic vision, otherwise known as computer vision for robots, is a critical process for robots to collect and interpret detailed information related to human actions, goals, and preferences, enabling robots to provide more useful services to people. This survey and systematic review presents a comprehensive analysis on robotic vision in human-robot interaction and collaboration (HRI/C) over the past 10 years. From a detailed search of 3,850 arti…
Contingent autonomy
In this article, we develop a framework for robotic autonomy as contingent. We do so with an account of a series of online research workshops that asked people to design and test robot behaviours for a public space scenario of their choice, as a means to surface and discuss their understandings of robots. We show how, as people manipulated robots in a simulator, they came to understand the capacities and limits of robots in distinctive ways. Thin…
From Novice to Skilled
Multi-task missions for unmanned aerial vehicles (UAVs) involving inspection and landing tasks are challenging for novice pilots due to the difficulties associated with depth perception and the control interface. We propose a shared autonomy system, alongside supplementary information displays, to assist pilots to successfully complete multi-task missions without any pilot training. Our approach comprises of three modules: (1) a perception module…
Human-Robot Team Performance Compared to Full Robot Autonomy in 16 Real-World Search and Rescue Missions
Human operators in human-robot teams are commonly perceived to be critical for mission success. To explore the direct and perceived impact of operator input on task success and team performance, 16 real-world missions (10 h) were conducted based on the DARPA Subterranean Challenge. Missions involved deploying a heterogeneous team of robots to locate and identify artefacts such as climbing rope, drills and a mannequin representing a human survivor…
How Can Everyday Users Efficiently Teach Robots by Demonstration
Learning from Demonstration (LfD) is a framework that allows lay users to easily program robots. However, the efficiency of robot learning and the robot’s ability to generalize to task variations hinge upon the quality and quantity of the provided demonstrations. Our objective is to guide human teachers to provide more effective demonstrations, thus facilitating efficient robot learning. To achieve this, we propose to use a measure of uncertainty…
Adapting a Teachable Robot’s Dialog Responses Using Reinforcement Learning
Teachable robots in education have the ability to increase student engagement and learning through personalised interactions and the use of social behaviours, such as speech, gaze and emotional expressions. Adaptation of these behaviours is motivated by an interest in tailoring the learning experience to an individual user and improving user outcomes. This work proposes an adaptive response-selection algorithm for a teachable robot which aims to …
Consistency Matters
Learning from Demonstration (LfD) empowers robots to acquire new skills through human demonstrations, making it feasible for everyday users to teach robots. However, the success of learning and generalization heavily depends on the quality of these demonstrations. Consistency is often used to indicate quality in LfD, yet the factors that define this consistency remain underexplored. In this article, we evaluate a comprehensive set of motion data …
A Framework for Dynamic Situational Awareness in Human–Robot Teams
In human–robot teams, human situational awareness is the operator’s conscious knowledge of the team’s states, actions, plans and their environment. Appropriate human situational awareness is critical to successful human–robot collaboration. In human–robot teaming, it is often assumed that the best and required level of situational awareness is knowing everything at all times. This view is problematic, because what a human needs to know for optima…
Computer Science (15 works) · Artificial Intelligence (14 works) · Robot (14 works) · Human–computer interaction (11 works) · Psychology (10 works) · Social Robot Interaction and HRI (8 works) · Political science (5 works) · Robotics (5 works) · Engineering (4 works) · Human-Automation Interaction and Safety (4 works)