Robert Boschgmbh

Benzun Pious Wisely Babu

Liu Ren

Mao Ye

Shabnam Ghaffarzadegan

Zeng Dai

Zhixin Yan

Xinyu Huang

Soohwan Kim

A helmet and a method and system for controlling a digital visor of a helmet are disclosed herein. The helmet includes a visor screen having a plurality of liquid crystal display (LCD) pixels, with each LCD pixel configured to alter in transparency. The helmet also includes a light sensor configured to detect incident light. The helmet also includes a controller coupled to the visor screen and the light sensor. The controller is configured to alter the transparency of the plurality of LCD pixels based on the incident light. In embodiments, the controller can alter the transparency of the LCD pixels based on the direction and/or intensity of the incident light.

Helmet with digital visor

A helmet includes a transceiver configured to receive vehicle data from one or more sensors located on a vehicle. The helmet also includes an inertial movement unit (IMU) configured to collect helmet motion data of a rider of the vehicle and a processor in communication with the transceiver and IMU, and programmed to receive, via the transceiver, vehicle data from the one or more sensors located on the vehicle and determine a rider attention state utilizing the vehicle data from the one or more sensors located on the vehicle and the helmet motion data from the IMU.

Apparatus and system related to an intelligent helmet

A helmet includes a transceiver configured to receive vehicle data from one or more sensors located on a vehicle, an inertial measurement unit (IMU) configured to collect helmet motion data of the helmet associated with a rider of the vehicle, and a processor in communication with the transceiver and IMU, and programmed to receive, via the transceiver, vehicle data from the one or more sensors located on the vehicle, determine a gesture in response to the vehicle data from the one or more sensors located on the vehicle and the helmet motion data from the IMU, and output on a display of the helmet a status interface related to the vehicle, in response to the gesture.

System and method of vehicle aware gesture recognition in vehicles with smart helmets

A system and method for generating a tracking state for a device includes synchronizing measurement data from exteroceptive sensors and an inertial measurement unit (IMU). A processing unit is programmed to offset one of the measurement signals by a time offset that minimizes a total error between a change in rotation of the device predicted by the exteroceptive sensor data over a time interval defined by an exteroceptive sensor sampling rate and a change in rotation of the device predicted by the IMU sensor data over the time interval.

System and method for enhancing non-inertial tracking system with inertial constraints

A visual SLAM system comprises a plurality of keyframes including a keyframe, a current keyframe, and a previous keyframe, a dual dense visual odometry configured to provide a pairwise transformation estimate between two of the plurality of keyframes, a frame generator configured to create keyframe graph, a loop constraint evaluator adds a constraint to the receiving keyframe graph, and a graph optimizer configured to produce a map with trajectory.

RGB-D camera based tracking system and method thereof

A system for providing a rider of a saddle-ride vehicle, such as a motorcycle, with information about helmet usage is provided. A camera is mounted to the saddle-ride vehicle and faces the rider and monitor a rider of the vehicle and collect rider image data. A GPS system is configured to detect a location of the saddle-ride vehicle. A controller is in communication with the camera and the GPS system. The controller is configured to receive an image of the ruder from the camera, determine if the rider is wearing a helmet based on the rider image data, and output a helmet-worn indicator to the rider, in which the helmet-worn indicator varies based on the determined location of the saddle-ride vehicle.

Apparatus and warning system for intelligent helmet

A method for motion estimation in an augmented reality (AR) system includes receiving inertial sensor data and image data during movement of the AR system generating a probability map based on the inertial sensor data and the image data, the probability map corresponding to one frame in the image data and including probability values indicating that each pixel in the one frame is in an inertial coordinate frame or a local coordinate frame with a convolutional neural network encoder/decoder, identifying visual observations of at least one landmark in the local coordinate frame based on the image data and the probability map, and generating an estimate of secondary motion in the local coordinate frame based on a first prior state in a hidden Markov model (HMM) corresponding to the local coordinate frame and the visual observations of the at least one landmark in the local coordinate frame.

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San Jose, CA, United States of America

Benzun Pious Wisely Babu