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The aim of our study is to detect balance disorders and a tendency towards the falls in the elderly, knowing gait parameters. In this paper we present a new tool for gait analysis based on markerless human motion capture, from camera feeds.…

Artificial Intelligence · Computer Science 2007-05-23 Jamal Saboune , François Charpillet

Although people spend most of their time indoors, outdoor tracking systems, such as the Global Positioning System (GPS), are predominantly used for location-based services. These systems are accurate outdoors, easy to use, and operate…

Emerging Technologies · Computer Science 2024-10-04 Alpha Diallo , Benoit Garbinato

Accurate and reliable navigation is essential for autonomous ground vehicle operations. Standard INS/GNSS fusion relies on GNSS position updates, which provide limited observability of orientation and inertial sensor error states,…

Robotics · Computer Science 2026-05-26 Gal Versano , Itzik Klein

This paper presents an algorithm to improve state estimation for legged robots. Among existing model-based state estimation methods for legged robots, the contact-aided invariant extended Kalman filter defines the state on a Lie group to…

Robotics · Computer Science 2026-01-29 Seokju Lee , Hyun-Bin Kim , Kyung-Soo Kim

We present two novel techniques for detecting zero-velocity events to improve foot-mounted inertial navigation. Our first technique augments a classical zero-velocity detector by incorporating a motion classifier that adaptively updates the…

Robotics · Computer Science 2020-05-05 Brandon Wagstaff , Valentin Peretroukhin , Jonathan Kelly

Estimating the limbs pose in a wearable way may benefit multiple areas such as rehabilitation, teleoperation, human-robot interaction, gaming, and many more. Several solutions are commercially available, but they are usually expensive or…

This paper proposes an interaction and safety-aware motion-planning method for an autonomous vehicle in uncertain multi-vehicle traffic environments. The method integrates the ability of the interaction-aware interacting multiple model…

Systems and Control · Electrical Eng. & Systems 2023-09-14 Jian Zhou , Björn Olofsson , Erik Frisk

Marker-based Optical Motion Capture (OMC) systems and associated musculoskeletal (MSK) modelling predictions offer non-invasively obtainable insights into in vivo joint and muscle loading, aiding clinical decision-making. However, an OMC…

Machine Learning · Computer Science 2023-04-25 Abhishek Dasgupta , Rahul Sharma , Challenger Mishra , Vikranth H. Nagaraja

The contribution gives a micro-structural insight into the pedestrian decision process during an egress situation. A method how to extract the decisions of pedestrians from the trajectories recorded during the experiments is introduced. The…

Multiagent Systems · Computer Science 2018-01-08 Pavel Hrabák , Ondřej Ticháček , Vladimíra Sečkárová

Inverse dynamic analysis using musculoskeletal modeling is a powerful tool, which is utilized in a range of applications to estimate forces in ligaments, muscles, and joints, non-invasively. To date, the conventional input used in this…

This paper presents a state-estimation solution for legged robots that uses a set of low-cost, compact, and lightweight sensors to achieve low-drift pose and velocity estimation under challenging locomotion conditions. The key idea is to…

Robotics · Computer Science 2025-07-23 Shuo Yang , Zixin Zhang , John Z. Zhang , Ibrahima Sory Sow , Zachary Manchester

A simple approach to gyro and accelerometer bias estimation is proposed. It does not involve Kalman filtering or similar formal techniques. Instead, it is based on physical intuition and exploits a duality between gimbaled and strapdown…

Systems and Control · Computer Science 2013-07-02 Vasiliy M. Tereshkov

As cameras and inertial sensors are becoming ubiquitous in mobile devices and robots, it holds great potential to design visual-inertial navigation systems (VINS) for efficient versatile 3D motion tracking which utilize any (multiple)…

Robotics · Computer Science 2020-06-30 Kevin Eckenhoff , Patrick Geneva , Guoquan Huang

This letter presents a model-agnostic meta-learning (MAML) based framework for simultaneous and accurate estimation of human gait phase and terrain geometry using a small set of fabric-based wearable soft sensors, with efficient adaptation…

The future of inland navigation increasingly relies on autonomous systems and remote operations, emphasizing the need for accurate vessel trajectory prediction. This study addresses the challenges of video-based vessel tracking and…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Alexander Puzicha , Konstantin Wüstefeld , Kathrin Wilms , Frank Weichert

We propose iMoT, an innovative Transformer-based inertial odometry method that retrieves cross-modal information from motion and rotation modalities for accurate positional estimation. Unlike prior work, during the encoding of the motion…

Machine Learning · Computer Science 2025-01-14 Son Minh Nguyen , Linh Duy Tran , Duc Viet Le , Paul J. M Havinga

Motion prediction is a key factor towards the full deployment of autonomous vehicles. It is fundamental in order to assure safety while navigating through highly interactive complex scenarios. In this work, the framework IAMP (Interaction-…

Robotics · Computer Science 2023-04-25 Vinicius Trentin , Chenxu Ma , Jorge Villagra , Zaid Al-Ars

Many Inertial Navigation Systems (INS) use Global Navigation Satellite System (GNSS) position as the primary measurement to drive filter performance and bound error growth. However, commercial-grade GNSS receivers introduce unknown…

Robotics · Computer Science 2026-05-14 Giulio Delama , Martin Scheiber , Yixiao Ge , Tarek Hamel , Stephan Weiss , Robert Mahony

We propose a multisensor fusion framework for onboard real-time navigation of a quadrotor in an indoor environment, by integrating sensor readings from an Inertial Measurement Unit (IMU), a camera-based object detection algorithm, and an…

A computationally efficient method for online joint state inference and dynamical model learning is presented. The dynamical model combines an a priori known, physically derived, state-space model with a radial basis function expansion…

Systems and Control · Electrical Eng. & Systems 2021-07-12 Anton Kullberg , Isaac Skog , Gustaf Hendeby
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