Nec Laboratories America, Inc.

Nec Corporation

Lucent Technologies Inc.

Alcatel Lucent

Alcatel-lucent USA Inc.

Nec C Orporation

Other

Florida State University Research Foundation, Inc.

Ranch Networks, Inc.

Sampath Rangarajan

Mohammad Ali Khojastepour

Narayan Prasad

Karthikeyan Sundaresan

Guosen Yue

Eugene Chai

Honghai Zhang

Meilong Jiang

Mustafa Arslan

Rajesh Mahindra

Sarit Mukherjee

Ravindranath Kokku

Xiaodong Wang

Sanjoy Paul

Kishore Ramachandran

Ayon Chakraborty

Katherine Hua Guo

Shalini Yajnik

Yan Xin

Randeep Singh Bhatia

Ajay Rajkumar

Girija J Narlikar

Yuanxi Jiang

Ali Tajer

Yasaman Ghasempour

Harish Viswanathan

Robert Arnott

Jubin Jose

Michael D Turner

Sachin Garg

Yennun Huang

Suman Das

Caroline Liang

Xinyu Zhang

Sureshbabu P Nair

Sudhir Aggarwal

Ramanujan Sheshadri

Chueng-Hsien Lin

Luca Venturino

Jongwon Yoon

Kyungtae Kim

Krishna Garikipati

Priya Rajan

Anand Kagalkar

Carlos Bocanegra

Vaibhav Singh

Ariel Cohen

Xiufeng Xie

Ashutosh Dhekne

Hajar Mahdavi-Doost

Patricia Wells

Mohammad Rostami

Hemant Banavar

Ting Wang

Navjot Singh

Neda Cvijetic

Yasushi Maruta

Paul Anthony Polakos

Peter Bosch

Ivica Rimac

Duong Pham

Pablo Rodriguez

Balakrishnan Narendran

Tejas Naik

Jiasi Chen

Xiadong Wang

Mehrdad Moradi

Mohammad A Khajehnejad

Md Shaifur Rahman

Alexander Sarin

Arun Gurung

Wenzhuo Ouyang

Hao Zhu

Junguk Cho

Arijit Banerjee

Karthik Sundaresan

Peilong Li

Hoonghai Zhang

Pablo Rodriquez

Anil Takkallapalli

Ram Ayyakad

Raghuram A Devarakonda

Alexander Pavlovsky

Sarang Moreshwar Gadgil

Hariharasudhan Viswanathan

Shasha Li

Ahmed O F Atya

Pankaj Jalote

Jie Xiong

Yi Xu

Samet Oymak

MdShaifur Rahman

Swadhin Pradhan

Sanaz Barghi

Cheng Liu

Mohammad Khojastepour

Systems and methods for automatically constructing a 3-dimensional (3D) model of a feature using a drone. The method includes generating a reconnaissance flight path that minimizes battery usage by the drone, and conducting a discovery flight that uses the reconnaissance flight path. The method further includes transmitting reconnaissance laser sensor data from the drone to a processing system for target identification, and selecting a target feature for 3D model construction based on the reconnaissance laser sensor data. The method further includes scanning the target feature using a laser sensor, transmitting laser sensor data for the target feature having a minimum point density from the drone to the processing system for 3D model construction, and constructing the 3D model from the minimum point density laser sensor data.

Near real-time reconstruction using drones

A product locating system is provided. The system includes at least one Radio Frequency (RF) backscatter transmitter configured to emit a main carrier RF signal that forms an excitation signal. The system further includes a passive RF backscatter tag associated with a product and configured to generate an Ultra-Wideband (UWB) signal from the excitation signal. The system also includes at least one RF backscatter receiver configured to simultaneously receive both the excitation signal from the at least one RF backscatter transmitter and the UWB signal from the passive RF backscatter tag, and compute the time-difference-of-arrival (TDoA) therebetween. TDoA information from multiple RF backscatter receivers, including the at least one RF backscatter receiver, is aggregated to compute the location of the product to which the passive RF backscatter tag is attached.

Locating objects in indoor spaces using radio frequency backscatter tags

Systems and methods for self-checkout at a point-of-sale are provided. The system and method includes using a plurality of radio frequency identification (RFID) transceivers within a store, and an RFID reader configured to receive an RFID code from an RFID tag activated by the plurality of radio frequency identification (RFID) transceivers. The system and method also includes using a classifier configured to determine whether the RFID tag is inside or outside a designated area, wherein the classifier is trained in a manner that a number of items incorrectly identified as being purchased is below a threshold to minimize customer dissatisfaction (CDS) determined as the ratio of the value of items charged to the customer but not purchased by a customer to the total charge to the customer.

Neural network classifier trained for purchasing differentiation

A method for product tagging is presented including emitting, by at least one RF backscatter transmitter, a dual-tone Radio Frequency (RF) signal embedded within a standardized RF signal on a frequency channel, reflecting and frequency shifting, by a passive RF backscatter tag associated with a product, the dual-tone RF signal to a different frequency channel, and reading, by at least one RF backscatter receiver, the product on the different frequency channel by detecting a distributed ambient backscatter signal generated by a reflection and frequency shifting of the dual-tone RF signal by the passive RF backscatter tag.

Reading passive wireless tags using commodity devices

Systems and methods for is provided for self-checkout at a point-of-sale. The system and method includes a plurality of radio frequency identification (RFID) transceivers, an RFID reader, wherein the RFID reader is configured to receive a response with an RFID code from each of a plurality of RFID tags activated simultaneously by at least one of the plurality of radio frequency identification (RFID) transceivers, and decode the RFID code from the response received from each of the RFID tags, and a classifier configured to determine whether each of the plurality of RFID tags is inside or outside a walk-through checkout area inside a store, wherein the system calculates an amount charged to a customer based on the cost of the items identified as within the walk-through checkout area.

Self checkout system

Methods and systems for localization within an environment include determining a topology estimate of nodes located in a dynamic indoor environment, based on distances measured between the nodes. Rigid k-core sub-graphs of the topology estimate are generated to determine relative localizations of the nodes. Relative localizations are transformed into absolute localizations to generate a map of positions of the nodes within the environment. A feature of the map is deployed to a device in the environment.

Infrastructure-free tracking and response

Systems and methods for determining radio-frequency identification (RFID) tag proximity groups are provided. The method includes receiving RFID tag readings from multiple RFID tags. The method includes determining signal strengths of the RFID tag readings. The method includes determining pairs of RFID tags based on the RFID tag readings. The method also includes implementing a twin recurrent neural network (RNN) to determine proximity groups of RFID tags based on distance similarity over time between each of the pairs of the RFID tags.

Tracking RFID groups with spatio-temporal proximity

Aspects of the present disclosure describe systems, methods and structures that perform linear-grammetry and calibration by simultaneous multilateration using only edge distance estimates via two-way ranging.

Linear-grammetry and calibration by simultaneous multilateration using only edge distance estimates through two-way ranging

Devices and systems for implementing a walk-through gate are provided. The devices include a walk-through gate structure having boundaries that have curved inner surfaces on each side of a cavity. The curved inner surfaces are partially covered by a reflective material. The devices include radio frequency (RF) signal transmitters positioned tangent to the curved inner surfaces and RF signal receivers. The devices also include apertures that provide access to the cavity of the walk-through gate structure.

Walk-through gate with signal separation

Aspects of the present disclosure describe systems, methods, and structures infrastructure-free RF tracking in dynamic indoor environments.

Infrastructure-free RF tracking in dynamic indoor environments

A method for employing cycle counting is presented. The method includes interrogating, by an RFID reader, RFID tags by using a plurality of antenna ports, determining, by an activation sequencer, an activation sequence of the plurality of antenna ports that have been enabled, collecting RFID tag responses from each of the RFID tags, and matching one or more of the RFID tag responses to a particular antenna port of the plurality of antenna ports in an activation cycle.

RFID-based self-checkout systems using cycle counting

A walk-through gate is provided. The walk-through gate includes a first semi-transparent side wall and a second semi-transparent side wall encapsulating a walk-through gate volume having an ingress portion and an egress portion. The walk-through gate further includes a plurality of antennas for wirelessly receiving product identifiers for wireless checkout. At least one of the plurality of antennas is made of a semi-transparent conductive material.

Transparent walk-through gate

Systems and methods implementing a multi-unmanned aerial vehicle (UAV) wireless communication network are provided. The system includes application UAVs that wirelessly provide applications. The system includes relay UAVs that connect the application UAVs to a ground station. The ground station connects to a wireless backhaul network. Processor devices determine mobility for the application UAVs based on application-specific objectives. The processor devices also determine mobility for the relay UAVs based on forming and maintaining the wireless backhaul network.

Unmanned aerial vehicle network

Systems and methods for localizing and tracking mobile objects are provided. A method includes determining an initial location of a node in a multi-hop network based on multi-lateration from an unmanned aerial vehicle. The method also includes applying an adaptive aperture to address a non-uniform velocity of the node based on the turn and a velocity vector. A determination whether localization for the node can be implemented using first hop nodes in the multi-hop network is made. In response to a determination that localization cannot be implemented using the first hop nodes, inertial sensor measurements associated with the node are accessed and the inertial sensor measurements are integrated with the adaptive aperture to improve localization accuracy.

Tracking indoor objects with inertial sensor measurements

A Radio Frequency Identification (RFID) localization system is provided. The system includes a set of passive RFID tags, each for reflecting transmitted signals. The system further includes an RFID reader for detecting the reflected signals by the passive RFID tags. The system also includes a processor for localizing an object in an area based on the reflected signals by computing signatures using probabilistic macro-channels between the RFID reader and locations of the passive RFID tags. The transmitted signals form inputs to the probabilistic macro-channels, and the signatures form outputs from the probabilistic macro-channels.

Signature-based RFID localization

Growing community of inventors

Bridgewater, NJ, United States of America

Sampath Rangarajan