76 citations · 101 across the 13 of their papers we have counts for
14 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…
NeMo-map: Neural Implicit Flow Fields for Spatio-Temporal Motion Mapping
Yufei Zhu, Shih-Min Yang, Andrey Rudenko +3
Safe and efficient robot operation in complex human environments can benefit from good models of site-specific motion patterns. Maps of Dynamics (MoDs) provide such models by encod…
Discrete Contrastive Learning for Diffusion Policies in Autonomous Driving
Kalle Kujanpää, Daulet Baimukashev, Farzeen Munir +4
Learning to perform accurate and rich simulations of human driving behaviors from data for autonomous vehicle testing remains challenging due to human driving styles' high diversit…
Context-aware Multi-task Learning for Pedestrian Intent and Trajectory Prediction
Farzeen Munir, Tomasz Piotr Kucner
The advancement of socially-aware autonomous vehicles hinges on precise modeling of human behavior. Within this broad paradigm, the specific challenge lies in accurately predicting…
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…
Radar-Lidar Fusion for Object Detection by Designing Effective Convolution Networks
Farzeen Munir, Shoaib Azam, Tomasz Kucner +2
Object detection is a core component of perception systems, providing the ego vehicle with information about its surroundings to ensure safe route planning. While cameras and Lidar…
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…
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…
Exploring Contextual Representation and Multi-Modality for End-to-End Autonomous Driving
Shoaib Azam, Farzeen Munir, Ville Kyrki +2
Learning contextual and spatial environmental representations enhances autonomous vehicle's hazard anticipation and decision-making in complex scenarios. Recent perception systems…
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…
Robust Frequency-Based Structure Extraction
Tomasz Piotr Kucner, Matteo Luperto, Stephanie Lowry +2
State of the art mapping algorithms can produce high-quality maps. However, they are still vulnerable to clutter and outliers which can affect map quality and in consequence hinder…
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…
A Next-Best-Smell Approach for Remote Gas Detection with a Mobile Robot
Riccardo Polvara, Marco Trabattoni, Tomasz Piotr Kucner +3
The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. Using mobile robots for gas detecti…