8 citations · 23 across the 11 of their papers we have counts for
13 papers
Seamless Outdoor-Indoor Pedestrian Positioning System with GNSS/UWB/IMU Fusion: A Comparison of EKF, FGO, and PF
Jiaqiang Zhang, Xianjia Yu, Sier Ha +5
Accurate and continuous pedestrian positioning across outdoor-indoor environments remains challenging because GNSS, UWB, and inertial PDR are complementary yet individually fragile…
Follow-Me in Micro-Mobility with End-to-End Imitation Learning
Sahar Salimpour, Iacopo Catalano, Tomi Westerlund +2
Autonomous micro-mobility platforms face challenges from the perspective of the typical deployment environment: large indoor spaces or urban areas that are potentially crowded and…
ROSBag MCP Server: Analyzing Robot Data with LLMs for Agentic Embodied AI Applications
Lei Fu, Sahar Salimpour, Leonardo Militano +3
Agentic AI systems and Physical or Embodied AI systems have been two key research verticals at the forefront of Artificial Intelligence and Robotics, with Model Context Protocol (M…
Towards Embodied Agentic AI: Review and Classification of LLM- and VLM-Driven Robot Autonomy and Interaction
Sahar Salimpour, Lei Fu, Kajetan Rachwał +8
Foundation models, including large language models (LLMs) and vision-language models (VLMs), have recently enabled novel approaches to robot autonomy and human-robot interfaces. In…
Sim-to-Real Transfer for Mobile Robots with Reinforcement Learning: from NVIDIA Isaac Sim to Gazebo and Real ROS 2 Robots
Sahar Salimpour, Jorge Peña-Queralta, Diego Paez-Granados +2
Unprecedented agility and dexterous manipulation have been demonstrated with controllers based on deep reinforcement learning (RL), with a significant impact on legged and humanoid…
Benchmarking ML Approaches to UWB-Based Range-Only Posture Recognition for Human Robot-Interaction
Salma Salimi, Sahar Salimpour, Jorge Peña Queralta +2
Human pose estimation involves detecting and tracking the positions of various body parts using input data from sources such as images, videos, or motion and inertial sensors. This…
Exploiting Local Observations for Robust Robot Learning
Wenshuai Zhao, Eetu-Aleksi Rantala, Sahar Salimpour +3
While many robotic tasks can be addressed using either centralized single-agent control with full state observation or decentralized multi-agent control, clear criteria for choosin…
Benchmarking UWB-Based Infrastructure-Free Positioning and Multi-Robot Relative Localization: Dataset and Characterization
Paola Torrico Morón, Sahar Salimpour, Lei Fu +3
Ultra-wideband (UWB) positioning has emerged as a low-cost and dependable localization solution for multiple use cases, from mobile robots to asset tracking within the Industrial I…
Fusing Odometry, UWB Ranging, and Spatial Detections for Relative Multi-Robot Localization
Xianjia Yu, Iacopo Catalano, Paola Torrico Morón +3
This letter presents a cooperative relative multi-robot localization design and experimental study. We propose a flexible Monte Carlo approach leveraging a particle filter to estim…
Exploiting Redundancy for UWB Anomaly Detection in Infrastructure-Free Multi-Robot Relative Localization
Sahar Salimpour, Paola Torrico Morón, Xianjia Yu +2
Ultra-wideband (UWB) localization methods have emerged as a cost-effective and accurate solution for GNSS-denied environments. There is a significant amount of previous research in…
Decentralized Vision-Based Byzantine Agent Detection in Multi-Robot Systems with IOTA Smart Contracts
Sahar Salimpour, Farhad Keramat, Jorge Peña Queralta +1
Multiple opportunities lie at the intersection of multi-robot systems and distributed ledger technologies (DLTs). In this work, we investigate the potential of new DLT solutions su…
Self-Calibrating Anomaly and Change Detection for Autonomous Inspection Robots
Sahar Salimpour, Jorge Peña Queralta, Tomi Westerlund
Automatic detection of visual anomalies and changes in the environment has been a topic of recurrent attention in the fields of machine learning and computer vision over the past d…
Analyzing General-Purpose Deep-Learning Detection and Segmentation Models with Images from a Lidar as a Camera Sensor
Yu Xianjia, Sahar Salimpour, Jorge Peña Queralta +1
Over the last decade, robotic perception algorithms have significantly benefited from the rapid advances in deep learning (DL). Indeed, a significant amount of the autonomy stack o…