656 citations · 773 across the 17 of their papers we have counts for
17 papers
Trajectory prediction for heterogeneous agents: A performance analysis on small and imbalanced datasets
Tiago Rodrigues de Almeida, Yufei Zhu, Andrey Rudenko +4
Robots and other intelligent systems navigating in complex dynamic environments should predict future actions and intentions of surrounding agents to reach their goals efficiently…
Long-Term Human Motion Prediction Using Spatio-Temporal Maps of Dynamics
Yufei Zhu, Andrey Rudenko, Tomasz P. Kucner +2
Long-term human motion prediction (LHMP) is important for the safe and efficient operation of autonomous robots and vehicles in environments shared with humans. Accurate prediction…
Context-Aware Human Behavior Prediction Using Multimodal Large Language Models: Challenges and Insights
Yuchen Liu, Lino Lerch, Luigi Palmieri +4
Predicting human behavior in shared environments is crucial for safe and efficient human-robot interaction. Traditional data-driven methods to that end are pre-trained on domain-sp…
Fast Online Learning of CLiFF-maps in Changing Environments
Yufei Zhu, Andrey Rudenko, Luigi Palmieri +3
Maps of dynamics are effective representations of motion patterns learned from prior observations, with recent research demonstrating their ability to enhance various downstream ta…
Human Gaze and Head Rotation during Navigation, Exploration and Object Manipulation in Shared Environments with Robots
Tim Schreiter, Andrey Rudenko, Martin Magnusson +1
The human gaze is an important cue to signal intention, attention, distraction, and the regions of interest in the immediate surroundings. Gaze tracking can transform how robots pe…
LaCE-LHMP: Airflow Modelling-Inspired Long-Term Human Motion Prediction By Enhancing Laminar Characteristics in Human Flow
Yufei Zhu, Han Fan, Andrey Rudenko +3
Long-term human motion prediction (LHMP) is essential for safely operating autonomous robots and vehicles in populated environments. It is fundamental for various applications, inc…
THÖR-MAGNI: A Large-scale Indoor Motion Capture Recording of Human Movement and Robot Interaction
Tim Schreiter, Tiago Rodrigues de Almeida, Yufei Zhu +7
We present a new large dataset of indoor human and robot navigation and interaction, called THÖR-MAGNI, that is designed to facilitate research on social navigation: e.g., modellin…
CLiFF-LHMP: Using Spatial Dynamics Patterns for Long-Term Human Motion Prediction
Yufei Zhu, Andrey Rudenko, Tomasz P. Kucner +4
Human motion prediction is important for mobile service robots and intelligent vehicles to operate safely and smoothly around people. The more accurate predictions are, particularl…
Advantages of Multimodal versus Verbal-Only Robot-to-Human Communication with an Anthropomorphic Robotic Mock Driver
Tim Schreiter, Lucas Morillo-Mendez, Ravi T. Chadalavada +5
Robots are increasingly used in shared environments with humans, making effective communication a necessity for successful human-robot interaction. In our work, we study a crucial…
A Data-Efficient Approach for Long-Term Human Motion Prediction Using Maps of Dynamics
Yufei Zhu, Andrey Rudenko, Tomasz P. Kucner +2
Human motion prediction is essential for the safe and smooth operation of mobile service robots and intelligent vehicles around people. Commonly used neural network-based approache…
The Effect of Anthropomorphism on Trust in an Industrial Human-Robot Interaction
Tim Schreiter, Lucas Morillo-Mendez, Ravi T. Chadalavada +3
Robots are increasingly deployed in spaces shared with humans, including home settings and industrial environments. In these environments, the interaction between humans and robots…
The Magni Human Motion Dataset: Accurate, Complex, Multi-Modal, Natural, Semantically-Rich and Contextualized
Tim Schreiter, Tiago Rodrigues de Almeida, Yufei Zhu +9
Rapid development of social robots stimulates active research in human motion modeling, interpretation and prediction, proactive collision avoidance, human-robot interaction and co…
The Atlas Benchmark: an Automated Evaluation Framework for Human Motion Prediction
Andrey Rudenko, Luigi Palmieri, Wanting Huang +2
Human motion trajectory prediction, an essential task for autonomous systems in many domains, has been on the rise in recent years. With a multitude of new methods proposed by diff…
Learning Occupancy Priors of Human Motion from Semantic Maps of Urban Environments
Andrey Rudenko, Luigi Palmieri, Johannes Doellinger +2
Understanding and anticipating human activity is an important capability for intelligent systems in mobile robotics, autonomous driving, and video surveillance. While learning from…
THÖR: Human-Robot Navigation Data Collection and Accurate Motion Trajectories Dataset
Andrey Rudenko, Tomasz P. Kucner, Chittaranjan S. Swaminathan +3
Understanding human behavior is key for robots and intelligent systems that share a space with people. Accordingly, research that enables such systems to perceive, track, learn and…
Human Motion Trajectory Prediction: A Survey
Andrey Rudenko, Luigi Palmieri, Michael Herman +3
With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly…
A Fast Randomized Method to Find Homotopy Classes for Socially-Aware Navigation
Luigi Palmieri, Andrey Rudenko, Kai O. Arras
We introduce and show preliminary results of a fast randomized method that finds a set of K paths lying in distinct homotopy classes. We frame the path planning task as a graph sea…