Communications: directive radio wave systems and devices (e.g. – Directive – Beacon or receiver
Reexamination Certificate
2000-02-17
2001-11-27
Blum, Theodore M. (Department: 3662)
Communications: directive radio wave systems and devices (e.g.,
Directive
Beacon or receiver
C342S457000, C701S207000
Reexamination Certificate
active
06323807
ABSTRACT:
FIELD OF THE INVENTION
This invention relates generally to wearable computing devices, and more particularly, to indoor navigation using wearable computing devices.
BACKGROUND OF THE INVENTION
For many applications of wearable computing devices, the ability to detect aspects of a user's internal or external state is essential. Generally, this is called context awareness.
Internal context aware computing has been used to detect a variety of aspects of a user's internal state. For example, sensors have measured psychological patterns of the user, such as expressions of joy or anger, and these psychological parameters have been correlated with physiological parameters such as heart rate and physical activity. Actigraphy, i.e., processed accelerometer readings, has been used for detailed and long-term measurement of hand tremors to help Parkinson patients manage their symptoms. Wearable computing devices have also been used for detecting when a person is sleeping, and for correlating between levels of activity and mood disorders, and attention-deficit hyperactivity disorder.
External context aware computing has been used in applications such as automated tour guides, and for people and animal tracking,. With automated tour guides, the wearable devices augment the user's view of attractions.
Wearable devices can also provide navigational assistance for visually impaired people. GPS information acquired by wearable devices has been used in context-aware computing to assist field workers track wild animals.
For the purpose of navigating, most prior art work has focused on rich and well understood sensors such as optical, vision, and audio sensors. For example, U.S. Pat. No. 5,793,483 describes an optical measurement system that includes an optical beam transmitter, and an optical beam detector to measure a distance between the transmitter and detector. U.S. Pat. No. 5,378,969 describes a system for controlling robot navigation that uses a map of the environment that was prepared in advance. In the map, shape features of objects are predesignated. The robot has a vision sensor. In its navigation, the robot recognizes its current position from the shape feature.
In the field of robot navigation, many systems also rely on sonar sensors, which are not appropriate for wearable systems where control of orientation is a problem.
For indoor navigation, GPS is difficult to use. U.S. Pat. No. 5,959,575, describes an interior GPS navigation method. There, ground transceivers transmit a pseudo-satellite signal which includes positional coordinates of the round transceiver. Active badges and systems based on beacons require the installation and maintenance of complex and expensive infrastructures.
It is desired to perform indoor navigation using only passive wearable sensors that rely entirely on naturally-occurring, signals. A challenge with this type of application, and other related ones, is that the raw sensor signals are often unsuitable for use as direct inputs to a machine-learning process to model an environment. The reason is that there is too great a statistical distance between the raw signals and the high-level inference that is to be made. One goal of the invention is to increase the likelihood that a correct inference is made.
SUMMARY OF THE INVENTION
The invention provides a wearable computing device for context awareness computing. More particularly, the wearable device according to the invention can be used for navigating an indoor environment. The wearable device includes passive sensors for measuring magnetic fields from steel beams in walls, floors, and ceilings of building, ambient light emitted from fixed arrangements of fluorescent lights, and temperature gradients across rooms. In addition, the passive sensors measure distinctive acceleration patterns due to ascending or descending staircases, riding, an escalator or elevator, simply walking, or counting the number of steps taken.
During a learning phase, the raw signals from the sensors are provided to a learning module. The signals are preprocessed to extract high-level features. These high-level features do not add new knowledge to the system. Instead, the features reformulate existing information into a form that is more effective for a machine-learning process. Once a model of the environment has been learned, the system can be used for navigation.
More particularly, a wearable device is configured for navigating, in an indoor environment. The device includes passive sensors for measuring environmental physical conditions at known locations in the indoor environment and at unknown locations in the indoor environment. A wearable computer is coupled to the passive sensors.
The computer is configured to construct a first statistical model of the environment according to the measured physical conditions at known locations and a second statistical model of the environment according to the measured physical conditions at the unknown locations. Processing means of the computer determine a probability that the unknown locations correspond to any of the known locations by comparing the second statistical model to the first statistical model.
REFERENCES:
patent: 5402340 (1995-03-01), White et al.
patent: 5470233 (1995-11-01), Fruchterman et al.
patent: 5726660 (1998-03-01), Purdy et al.
patent: 5798733 (1998-08-01), Ethridge
patent: 5828321 (1998-10-01), Matsuzaki
patent: 5902347 (1999-05-01), Backman et al.
patent: 5940346 (1999-08-01), Sadowsky et al.
patent: 6081230 (2000-06-01), Hoshino et al.
Schmidt et al.; “Advanced Interaction in Context”; Lecture Notes in Science 1707, Gellersen Ed. ; First International Symposium, Sep. 1999. pp. 89-101.
“Low Voltage Temperature Sensors”; TMP35/TMP36/TMP37; Analog Devices.
“PCM-DAS 16/330 A/D Conversion Card”; ComputerBoards, Inc.
“Three-Axis Magnetic Sensor Hybird”; HMC2003; Honeywell Sensor Products.
Golding Andrew R.
Lesh Neal B.
Blum Theodore M.
Brinkman Dirk
Mitsubishi Electric Research Laboratories Inc.
LandOfFree
Indoor navigation with wearable passive sensors does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Indoor navigation with wearable passive sensors, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Indoor navigation with wearable passive sensors will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2574046