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.

Opportunistic radio SLAM for indoor navigation using smartphone sensors

Abstract: This paper provides the experimental results of a system utilising only the sensors available on a smartphone to provide an indoor positioning system that does not require any prior knowledge of floor plans, transmitter locations, radio signal strength databases, etc. The system utilises a Distributed Particle Filter Simultaneous Localisation and Mapping (DPSLAM) method to provide constraints on the drift of a simple hip-mounted Inertial Measurement Unit (IMU) integrated into the smartphone and providing the core information on the movement of the user. This system was developed during a project investigating methods of providing relative positioning systems to a team operating for extended periods without GPS. The paper concentrates on the DPSLAM positioning technique suitable for use by an individual with no prior knowledge of the area of operation before deployment. As with all SLAM systems, the user is simply required to revisit locations periodically to enable IMU drifts to be observed and corrected.

A step toward GPS/INS personal navigation systems: real-time assessment of gait by foot inertial sensing

Abstract: In this paper, we develop a system for which applications in the field of personal navigation are planned. In the current version, the system embodies a Global Positioning System (GPS) receiver and an inertial measurement unit (IMU), composed of two dual-axis accelerometers and one single-axis gyro. The IMU is positioned at a subject's foot instep, and it is intended to produce estimates of some gait parameters, including stride length, stride time, and walking speed. Data from GPS and IMU are managed by a DSP-based control box. The computations performed by the DSP processor allow to detect subsequent foot contacts by a threshold-based method applied to gyro signal, and to reconstruct the trajectory of the foot instep by numerical strapdown integration. Features of human walking dynamics are incorporated in the algorithm to enhance the estimation accuracy against errors due to sensor noise and integration drift. All computations are performed by the DSP processor in real-time conditions. The foot sensor performance is assessed during outdoor level walking trials. The traveled distance estimated by inertial dead-reckoning is compared with the estimate produced by GPS in experimental conditions where GPS can be used as a reference source for accurate absolute positioning. Results show the remarkable accuracy achieved by foot inertial sensing.

Wearable earpiece for providing social and environmental awareness

Abstract: An intelligent earpiece to be worn over an ear of a user is described. The earpiece includes a processor connected to the IMU, the GPS unit and the at least one camera. The processor can recognize an object in the surrounding environment by analyzing the image data based on the stored object data and at least one of the inertial measurement data or the location data. The processor can determine a desirable event or action based on the recognized object, the previously determined user data, and a current time or day. The processor can determine a destination based on the determined desirable event or action. The processor can determine a navigation path for navigating the intelligent guidance device to the destination based on the determined destination, the image data, the inertial measurement data or the location data. The processor can determine output data based on the determined navigation path.

Cooperative localization by dual foot-mounted inertial sensors and inter-agent ranging

Abstract: The implementation challenges of cooperative localization by dual foot-mounted inertial sensors and inter-agent ranging are discussed, and work on the subject is reviewed. System architecture and sensor fusion are identified as key challenges. A partially decentralized system architecture based on step-wise inertial navigation and step-wise dead reckoning is presented. This architecture is argued to reduce the computational cost and required communication bandwidth by around two orders of magnitude while only giving negligible information loss in comparison with a naive centralized implementation. This makes a joint global state estimation feasible for up to a platoon-sized group of agents. Furthermore, robust and low-cost sensor fusion for the considered setup, based on state space transformation and marginalization, is presented. The transformation and marginalization are used to give the necessary flexibility for presented sampling-based updates for the inter-agent ranging and ranging free fusion of the two feet of an individual agent. Finally, the characteristics of the suggested implementation are demonstrated with simulations and a real-time system implementation.