10 citations · 14 across the 13 of their papers we have counts for
11 papers · 1 filter
Chalito: An Extensible Library for Filtering-Based State Estimation in Quadruped Robots
Hilton Marques Souza Santana, João Carlos Virgolino Soares, Marco Antonio Meggiolaro +1
State estimation is essential for quadruped robots, enabling robust locomotion, navigation, and control. While many estimators have been proposed in the literature, existing implem…
Iterated Invariant EKF for 3D Landmark-Aided Inertial Navigation
Hilton Marques Souza Santana, João Carlos Virgolino Soares, Marco Antonio Meggiolaro
Inertial navigation systems aided by three-dimensional landmark measurements constitute a fundamental problem in robotic perception and state estimation. Classical SO(3)-based Exte…
A Proprioceptive-Only Benchmark for Quadruped State Estimation: ATE, RPE, and Runtime Trade-offs Between Filters and Smoothers
Ylenia Nisticò, João Carlos Virgolino Soares, Joan Solà +1
We compare three state-of-the-art proprioceptive state estimators for quadruped robots: MUSE [1], the Invariant Extended Kalman Filter (IEKF) [2], and the Invariant Smoother (IS) […
Iterated Invariant EKF for Quadruped Robot Odometry
Hilton Marques Souza Santana, João Carlos Virgolino Soares, Sven Goffin +4
Kalman filter-based algorithms are fundamental for mobile robots, as they provide a computationally efficient solution to the challenging problem of state estimation. However, they…
VAR-SLAM: Visual Adaptive and Robust SLAM for Dynamic Environments
João Carlos Virgolino Soares, Gabriel Fischer Abati, Claudio Semini
Visual SLAM in dynamic environments remains challenging, as several existing methods rely on semantic filtering that only handles known object classes, or use fixed robust kernels…
Proprioceptive Image: An Image Representation of Proprioceptive Data from Quadruped Robots for Contact Estimation Learning
Gabriel Fischer Abati, João Carlos Virgolino Soares, Giulio Turrisi +2
This paper presents a novel approach for representing proprioceptive time-series data from quadruped robots as structured two-dimensional images, enabling the use of convolutional…
Multi-Sensor Fusion for Quadruped Robot State Estimation using Invariant Filtering and Smoothing
Ylenia Nisticò, Hajun Kim, João Carlos Virgolino Soares +3
This letter introduces two multi-sensor state estimation frameworks for quadruped robots, built on the Invariant Extended Kalman Filter (InEKF) and Invariant Smoother (IS). The pro…
MUSE: A Real-Time Multi-Sensor State Estimator for Quadruped Robots
Ylenia Nisticò, João Carlos Virgolino Soares, Lorenzo Amatucci +2
This paper introduces an innovative state estimator, MUSE (MUlti-sensor State Estimator), designed to enhance state estimation's accuracy and real-time performance in quadruped rob…
Proprioceptive State Estimation for Quadruped Robots using Invariant Kalman Filtering and Scale-Variant Robust Cost Functions
Hilton Marques Souza Santana, João Carlos Virgolino Soares, Ylenia Nisticò +2
Accurate state estimation is crucial for legged robot locomotion, as it provides the necessary information to allow control and navigation. However, it is also challenging, especia…
Panoptic-SLAM: Visual SLAM in Dynamic Environments using Panoptic Segmentation
Gabriel Fischer Abati, João Carlos Virgolino Soares, Vivian Suzano Medeiros +2
The majority of visual SLAM systems are not robust in dynamic scenarios. The ones that deal with dynamic objects in the scenes usually rely on deep-learning-based methods to detect…
Visual Localization and Mapping in Dynamic and Changing Environments
João Carlos Virgolino Soares, Vivian Suzano Medeiros, Gabriel Fischer Abati +4
The real-world deployment of fully autonomous mobile robots depends on a robust SLAM (Simultaneous Localization and Mapping) system, capable of handling dynamic environments, where…