Inertial measurement unit

About: Inertial measurement unit is a research topic. Over the lifetime, 13326 publications have been published within this topic receiving 189083 citations. The topic is also known as: IMU.

Stabilization and Trajectory Tracking of a Quad-Rotor Using Vision

Abstract: We propose a vision-based position control method, with the purpose of providing some level of autonomy to a quad-rotor unmanned aerial vehicle. Our approach estimates the helicopter X-Y-Z position with respect to a landing pad on the ground. This technique allows us to measure the position variables that are difficult to compute when using conventional navigation systems, for example inertial sensors or Global Positioning Systems in urban environment or indoor. We also present a method to measure translational speed in a local frame. The control strategy implemented is based on a full state feedback controller. Experimental results validate the effectiveness of our method.

Front-Crawl Instantaneous Velocity Estimation Using a Wearable Inertial Measurement Unit

Abstract: Monitoring the performance is a crucial task for elite sports during both training and competition. Velocity is the key parameter of performance in swimming, but swimming performance evaluation remains immature due to the complexities of measurements in water. The purpose of this study is to use a single inertial measurement unit (IMU) to estimate front crawl velocity. Thirty swimmers, equipped with an IMU on the sacrum, each performed four different velocity trials of 25 m in ascending order. A tethered speedometer was used as the velocity measurement reference. Deployment of biomechanical constraints of front crawl locomotion and change detection framework on acceleration signal paved the way for a drift-free integration of forward acceleration using IMU to estimate the swimmers velocity. A difference of 0.6 ± 5.4 cm·s−1 on mean cycle velocity and an RMS difference of 11.3 cm·s−1 in instantaneous velocity estimation were observed between IMU and the reference. The most important contribution of the study is a new practical tool for objective evaluation of swimming performance. A single body-worn IMU provides timely feedback for coaches and sport scientists without any complicated setup or restraining the swimmer’s natural technique.

Inertial Sensor-Based Indoor Pedestrian Localization with Minimum 802.15.4a Configuration

Abstract: Available techniques for indoor object locating systems, such as inertial sensor-based system or radio fingerprinting, hardly satisfy both cost-effectiveness and accuracy. In particular, inertial sensor-based locating systems are often supplemented with radio signals to improve localization accuracy. A radio-assisted localization system is still costly due to the infrastructure requirements and management overheads. In this paper, we propose a low-cost and yet accurate indoor pedestrian localization scheme with a small number of radio beacons whose location information is unknown. Our scheme applies the Simultaneous Location and Mapping (SLAM) technique used in robotics to mobile device, which is equipped with both inertial sensors and the IEEE802.15.4a Chirp Spread Spectrum (CSS) radio, to obtain accurate locations of pedestrians in indoor environment. The proposed system is validated with real implementations. The experiment results show approximately 1.5 m mean error observed during 276 m of pedestrian moving in a 380 m2 indoor environment with five position-unknown beacons.

A Reliable Fusion Positioning Strategy for Land Vehicles in GPS-Denied Environments Based on Low-Cost Sensors

Abstract: How to achieve reliable and accurate positioning performance using low-cost sensors is one of the main challenges for land vehicles. This paper proposes a novel fusion positioning strategy for land vehicles in GPS-denied environments, which enhances the positioning performance simultaneously from the sensor and methodology levels. It integrates multiple complementary low-cost sensors not only incorporating GPS and microelectromechanical-based inertial measurement unit, but also a “virtual” sensor, i.e., a sliding-mode observer (SMO). The SMO is first synthesized based on nonlinear vehicle dynamics model to estimate vehicle state information robustly. Then, a federated Kalman filter (FKF) is designed to fuse all sensor information, which can easily isolate and accommodate such sensor failures as GPS ones due to its decentralized filtering architecture. Further, a hybrid global estimator (HGE) is constructed by augmenting the FKF with a grey predictor, which has the advantages of dealing with the systems with uncertain or insufficient information. The HGE works in the update mode when there is no GPS failure, whereas it switches to the prediction mode in case of GPS outage to realize accurate and reliable positioning. The experimental results validate the effectiveness and reliability of the proposed strategy.

High-performance, low cost inertial MEMS: A market in motion!

Abstract: The latest advances in MEMS inertial sensors for applications where size, weight, power, and cost are key considerations are having profound effects on the market place. MEMS industrial and tactical-grade sensors are the most dynamic technology in the high-performance inertial industry. Yole Developpement sees the market growing from $381.8M in 2011 to $638.8M in 2017 for single MEMS accelerometers and gyroscopes or assemblies of MEMS accelerometers and gyroscopes.