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.

Realtime perception for catching a flying ball with a mobile humanoid

Abstract: This paper presents a realtime perception system for catching flying balls with DLR's humanoid Rollin' Justin. We use a two-staged bottom up approach in which we first detect balls as circles and feed these measurements into a multiple hypothesis tracker (MHT). The novel circle detection scheme works in realistic scenes without tuning parameters or background assumptions. We extend the classical multi-hypothesis tracking with prior information about the expected trajectories, therefore limiting the number of hypotheses in the first place. Since the robot starts moving while the ball is still tracked, the cameras shake heavily. A 6-DOF inertial measurements unit (IMU) is integrated to compensate this motion. Using ground-truth from a marker based tracking system we evaluate the metrical accuracy of the motion compensation as well as the tracker's prediction accuracy while in motion.

Miniature Low-Power Inertial Sensors: Promising Technology for Implantable Motion Capture Systems

Abstract: Inertial and magnetic sensors are valuable for untethered, self-contained human movement analysis. Very recently, complete integration of inertial sensors, magnetic sensors, and processing into single packages, has resulted in miniature, low power devices that could feasibly be employed in an implantable motion capture system. We developed a wearable sensor system based on a commercially available system-in-package inertial and magnetic sensor. We characterized the accuracy of the system in measuring 3-D orientation—with and without magnetometer-based heading compensation—relative to a research grade optical motion capture system. The root mean square error was less than 4 $^{\circ}$ in dynamic and static conditions about all axes. Using four sensors, recording from seven degrees-of-freedom of the upper limb (shoulder, elbow, wrist) was demonstrated in one subject during reaching motions. Very high correlation and low error was found across all joints relative to the optical motion capture system. Findings were similar to previous publications using inertial sensors, but at a fraction of the power consumption and size of the sensors. Such ultra-small, low power sensors provide exciting new avenues for movement monitoring for various movement disorders, movement-based command interfaces for assistive devices, and implementation of kinematic feedback systems for assistive interventions like functional electrical stimulation.

On the attitude estimation of accelerating rigid-bodies using GPS and IMU measurements

Abstract: We present two observers that estimate the orientation of a rigid body, which is subjected to linear accelerations and rotational motion, using a global positioning system (GPS) and a body-attached inertial measurement unit (IMU). Unlike some other attitude estimation schemes (which assume that the accelerometer measures the gravity vector, which is not realistic when the rigid body is subject to large linear accelerations), the proposed results belong to the special class of velocity-aided attitude observers, which instead use the true accelerometer measurements (i.e., the system's apparent acceleration). The linear velocity of the rigid body (obtained from the GPS) is used to obviate the requirement of the linear acceleration (which is assumed unavailable in the inertial frame). The new observers can handle large accelerations of the rigid body which could otherwise destroy the performance of other types of attitude observers which assume that the accelerometer measures the gravity vector.