A common method for creating a 6 degree of freedom (DoF) device is to track a single marker with a camera to measure linear position, and use an IMU to measure angular position (orientation). This is often used for AR and VR controllers and head tracking. One key challenge is aligning the coordinate frames of the camera and the IMU, and keeping them aligned over time. This paper presents a method of frame alignment that doesn’t require user intervention, and properly handles integration errors from the gyroscope as well as the very large errors encountered when performing double integration on the linear acceleration of the IMU’s accelerometer to compute linear position. The paper also compares two options for solving for the alignment, either a recursive least-squares (RLS) approach or as a solution to Wahba’s problem.
In the not-so-distant future, handheld motion control will play a crucial role in how people interact with their smart devices. These technologies are already instrumental in gaming, smart TVs, and VR applications, and are being experimented with in other use cases ranging from consumer electronics to elder care and more. Creating a more natural user interface using handheld motion control can drive product adoption, user satisfaction and customer loyalty. It can unlock a whole new set of features that will impact how consumers use the technology they love.
Augmented and virtual reality (AR/VR) applications are all about delivering lifelike experiences. To differentiate, manufacturers need to provide a true-to-life experience that’s immersive and enjoyable.
3D audio can truly immerse a user in a new space. Sounds from a real-world source reach each ear at a different time, and your brain interprets these differences in time to determine directionality.
Hillcrest Labs develops high-accuracy sensor technology for robotics, AR/VR, handheld motion control and other motion and orientation-sensing applications.
Hillcrest Labs develops sensor technology for attitude alignment and monitoring that is used in applications where precise heading and orientation of a fixed asset are critical.
Robotic vacuum cleaners are all about simplifying lives by saving time. Cleaners that get lost or stuck in corners, miss spots on the floor or run out of battery before returning to their dock lead to dissatisfaction with your product. But innovations in sensor technology can enable robots to clean smarter and more effectively. And, multi-axis sensors are leading the charge.
Handheld motion control isn’t new. As a core feature for devices in the past, it was expensive to produce and was never able to fully blossom. But over the years, motion sensor technology has advanced by leaps and bounds, unlocking new uses.
This paper sets out to explain the background of sensor fusion processing and to present to the reader the advances in device capability that the Cortex-M7 processor enables. As well as explaining the benefits of the Cortex–M7 architecture in sensor fusion.
From game consoles to smart TV remote controls to, more recently, smartphones, sensor fusion has been used to create more intuitive and fun interactions for consumer electronics. Hillcrest has been a pioneer in this space for over a decade, developing proprietary signal processing techniques to transform human movement into high quality, application-ready motion information using MEMS inertial and magnetic sensors.
As demand for Internet content on television increases, service providers and consumer electronics manufacturers need alternative technologies to the traditional up/down/left/right remote control in order to delight consumers with new interactive experiences on TV. This paper describes why pointing is the right solution for controlling the TV experience, and compares two technologies that enable pointing remote controls: touchpad and motion control. A series of studies compare these two methods of pointing for two common use-cases: navigation and casual gaming. Results show that pointing by motion is superior to pointing with touchpad for both use-cases.
This document explains the foundations of 3D mouse cursor control for Smart TV applications. More specifically, it describes the 4 most important considerations for cursor control:
– The development of the PC mouse and the optimization for GUI navigation
– Specific considerations of the air-mouse and the living room environment
– Absolute Pointing use cases
– Freespace optimizations for Smart TV applications