Synaptics Corporation

Amazon Technologies, Inc.

Prakriti Chintalapoodi

Rui Zhang

Nickolas Fotopoulos

Eric Foxlin

Drew Garvin Keppel

Described herein is a system for improving navigation by detecting glass surfaces. For example, the system may build an occupancy map representing objects present in an environment. The system performs additional processing to input scan data in order to detect glass surfaces and distinguish these glass surfaces from other obstacles. As glass is only detected within a narrow range of angles and the number of returns are small compared to non-glass surfaces, the system may determine whether an obstacle represented in the input scan data is glass by calculating a maximum range of angles and a number of overlapping returns for the obstacle. For example, the system may identify glass surfaces by identifying objects that are only detected within a narrow range of angles and that have a low number of overlapping returns.

Glass detection using lidar

A method of detecting touch inputs, in the presence of moisture, in a sensing region of an input device. The input device acquires sensor information about the sensing region via a plurality of sensor electrodes configured for capacitive sensing. A first capacitive image of the sensing region is generated based on the received sensor information. The input device further determines a set of contiguous regions in the first capacitive image and selects, from the set of contiguous regions, one or more contiguous regions that correspond to valid inputs. The one or more contiguous regions may be selected based at least in part on a plurality of capacitive images previously acquired for the sensing region. The input device may further report positional information for each of the selected contiguous regions. For example, the positional information may be used to process user inputs associated with the selected contiguous regions.

Multi-touch detection in moisture

A method for moisture detection includes obtaining absolute capacitive sensor data, and processing circuitry, determining a contiguous region in a capacitive image generated based on the absolute capacitive sensor data, determining a concavity parameter of the contiguous region, and detecting a presence of moisture based at least in part on the concavity parameter. The method further includes operating based on a presence of moisture.

Moisture management

Hybrid detection includes determining a first profiles based on multiple capacitive measurements, segmenting the first profiles into one dimensional intervals to obtain multiple segments, determining multiple regions of interest using the segments, and determining a set of contiguous regions based on multiple mutual capacitive measurements. Hybrid detection further includes selecting, from the set of contiguous regions, a set of valid contiguous regions using the regions of interest, and reporting positional information for each contiguous region in the set of valid contiguous regions.

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San Jose, CA, United States of America

Prakriti Chintalapoodi