Dhekne Receives NSF CAREER Award to Create Greener, More Advanced Indoor Navigation and Security Systems

Precision, millimeter-level 3D tracking of robotic arm movements – without cameras and in the dark ­– is just one of the expected benefits of new research into ultra-wideband radio (UWB) technology underway at Georgia Tech.

UWB technology uses low-level energy signals to enable short-range, high-bandwidth communications that do not interfere with other types of radio communications.

To push forward on what’s next in the field, School of Computer Science Assistant Professor Ashutosh Dhekne recently received a National Science Foundation (NSF) CAREER award for his proposal, Closing the Gaps in UWB Localization and Sensing: Algorithms, Architectures, and Prototypes.

Dhekne expects his UWB research to not only eliminate the need for cameras to sense and track the minute movements of a robotic arm, he anticipates that it will also enable the development of infinitely scalable indoor navigation systems and advanced intrusion detection systems.

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These advancements would have applications in homes as well as large, complex indoor spaces like malls, government buildings, and warehouses.

Systems using these new technologies are expected to be more environmentally friendly. They will require less computational power and generate much less data, which will significantly reduce energy usage for processing, transportation, and data storage. Privacy concerns will also be reduced because these systems do not rely on cameras.

“The overarching goal of this proposal is to carefully address some of the important challenges for indoor localization and sensing using wireless signals. This award provides an impetus to advance the state-of-the-art for indoor localization and will help support my research in the field,” said Dhekne.

The challenges Dhekne mentions relate to current algorithms and system architecture.

The technology shows promise because UWB frequencies can easily penetrate walls and the returning signals can be precisely timed. However, the algorithms and architecture used for current wireless systems cannot meet the needs for large indoor spaces.

“When we try to use the same algorithm­s for fine-grained localization, such as for localizing a pen on a whiteboard or tracking a robotic arm, we face hard-to-overcome limits of precision,” said Dhekne.

Overcoming these limitations won’t be easy. But Dhekne is confident he and his team of student researchers can develop innovative architectural solutions to dramatically advance the capabilities of UWB technology. These potential solutions include developing new multi-antenna systems that leverage the advantages of UWB and use signal phase to pinpoint an object’s location to within a millimeter.

Once more robust algorithms and improved architectural structures are developed, the team plans to move from the theoretical to the practical and create working prototypes to demonstrate the feasibility of their work.

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The expected improvements in fine-grained location and precision tracking of the 3D movements of a robotic arm will enable systems to detect deviations from nominal behavior. This is crucial to improving maintenance, auditing, and compliance record-keeping efficiencies for automated devices.

Coupled with these advances in sensing and tracking, the ability to infinitely scale systems will enable next-generation personal navigation in large spaces.

Using UWB receivers that capture signals sent by installed anchor devices, these systems will allow an unlimited number of users to pinpoint their exact location and navigate airports, parking decks, and other complex indoor areas. These systems will ensure privacy because they do not require a user’s device to transmit a UWB signal.

Advances in UWB sensing and tracking capabilities could also be used to provide better context to digital personal assistants.

“Localization makes digital personal assistants such as Google Home and Alexa more context aware. Commands given to digital assistants can become more natural when the user’s location is known.

“For example, just saying ‘turn on the lights’ can be understood as a request to turn on the living-room lights if the user is in the living room,” said Dhekne.

Another application of wireless sensing, according to Dhekne, will be for advanced security systems. Transmitted UWB signals travel in all directions and bounce off obstructions in an indoor space. People entering a space will cause detectable disturbances of the wireless signal-reflection patterns.

This approach allows a UWB-based system to ignore disturbances caused by a pet, an elderly person living in the house, or another known entity. This capability means a security system can remain constantly armed with much less chance for false alarms.

“Along with household use, this technology can also be used in museums or other high-value locations where guards are also present, since the proposed idea can ignore the movements of friendly entities,” Dhekne explained.

In addition to supporting Dhekne’s theoretical and practical research, his NSF CAREER award is also funding several upcoming educational activities related to the work including graduate student projects focused on mobile computing and the internet of things (IoT). These projects will be part of Dhekne’s CS8803-MCI course offered this coming Fall.

Educational activities planned through this grant go beyond just Georgia Tech students. For example, Dhekne and his team plan to create educational IoT kits and conduct workshops for students from local middle and high schools.

The team also intends to open source the software and other technologies produced from their research. This will enable a larger community of researchers and enthusiasts to explore wireless localization and sensing.

As for what’s next, Dhekne says that a lot more can be done to advance UWB technologies.

“In the future, I hope to work on innovative solutions to some of the most pressing issues that we face today such as sustainability.

"Wireless localization and sensing can reduce resource waste through smarter, contextually aware IoT in homes, factories, warehouses, and other large indoor spaces. Localization can improve efficiencies of these vast spaces, help us find lost items, and overall improve quality of life,” said Dhekne.