- Research
Controlled-Mobile Aerial Sensor Networks
The SensorFly is a novel low-cost controlled-mobile aerial sensor networking platform. A flock of these 29g autonomous helicopter nodes with communication, ranging and collaborative path determination capabilities, can be extremely useful in sensing survivors after disasters or adversaries in urban combat scenarios.
The platform is under active development. We are currently designing and prototyping the 5th generation of SensorFly hardware and software. The software and hardware schematics are open source and available through our GitHub repository. Stay tuned!
SugarMap: Location-less Coverage for Micro-aerial Sensing Swarms
SugarMap enables resource-constrained MAV nodes to achieve efficient sensing coverage. The self-establishing system uses approximate actuation models of mobile nodes in conjunction with radio signatures from self-deployed stationary anchor nodes to create a common coverage map. Consequently, the system coordinates node movements to reduce sensing overlap and increase the speed and efficiency of coverage. The system uses particle filters to account for uncertainty in sensors and actuation of MAV nodes, and incorporates redundancy to guarantee coverage.
WiFlock: Collaborative Group Discovery and Maintenance
Low energy neighbor discovery, group formation, and group maintenance is a fundamental service in mobile sensor networks. Traditional solutions consider these protocols separately. WiFlock is an energy-efficient protocol that combines discovery and maintenance using a collaborative beaconing mechanism. WiFlock combines a coordinated synchronized listening and evenly-spaced transmission (SLEST) schedule effectively with one-way discovery beacons to fulfill both purposes. We show that shorter listening duration implies smaller discovery latency and faster group information propagation. We evaluate WiFlock on a 50-node test bed with nodes running at 0.2% duty cycles. We show that WiFlock has shorter discovery latency and better scalability than previous approaches.
SugarTrail: Survey-free Indoor Navigation in Retail Environments
SugarTrail is a system for indoor navigation assistance in retail environments that minimizes the need for active tagging and does not require existing maps. By leveraging the structured movement patterns of shoppers in retail store environments, the system provides higher accuracy than existing radio finger-printing approaches. With minimal setup and no active user participation, the system automatically learns user movement pathways in indoor environments from radio-frequency and magnetic signatures. These pathways are clustered and used to automatically build a navigable virtual roadmap of the environment.
PANDAA: Zero-Config Device Arrangement-Detection
PANDAA is a zero-configuration spatial localization system for networked devices based on ambient sound sensing. After initial placement of the devices, ambient sounds, such as human speech, music, footsteps, finger snaps, hand claps, or coughs and sneezes, are used to autonomously resolve the spatial relative arrangement of devices using trigonometric bounds and successive approximation. Using only time difference of arrival measurements as a bound for successive estimations, PANDAA is able to achieve an average of 0.17 meter accuracy for device location in the meeting room deployment.
Point: Spatially-Aware Interaction for Mobile Devices
Using built-in microphones and speakers on commodity mobile devices, Spartacus uses a novel acoustic Doppler-effect based technique to enable users to accurately initiate an interaction with a neighboring device through a pointing gesture. Experimental results show that Spartacus achieves an average 90% device selection accuracy within 3m for most interaction scenarios.
Polaris: Accurate Indoor Orientations using Ceiling Patterns
Polaris is a system for providing accurate orientations for mobile phones in indoor environments using ubiquitous ceiling patterns in a building as orientation references. Though digital compasses are commonly used in mobile phones to determine device orientations, they are vulnerable to indoor magnetic interference. Since ceiling patterns are universal and unrelated to magnetic fields, Polaris can provide accurate orientations for mobile devices even under severe magnetic interferences. The achieved accuracy is over 4.5 degree, 3.5X better than raw compass readings.
Over-the-air Incremental Sensor Network Reprogramming
An over-the-air sensor network reprogramming system for Sensor Andrew, Carnegie Mellon’s campus-wide wireless sensor network. The system’s incremental binary patch update capability reduces communication and hence energy on average by 70%, for reprogramming resource constrained sensor nodes. Available as part of the Nano-RK real-time WSN operating system source code.
