Compressive Cooperative Sensing and Mapping in Mobile Networks

Reference number: STC-PS-0954
Inventor(s): Y. Mostofi; P. Sen
For more information, contact: Minh D. Tran (505-272-7937) or Lisa Kuuttila (505-272-7905)

Patent(s)

Application(s) pending

Background

Mobile intelligent networks can play a key role in emergency response, search and rescue, surveillance and security, and battlefield operations. The vision of a multi-agent robotic network cooperatively learning and adapting in harsh unknown environments to achieve a common goal is closer than ever. Some of these networks are tasked with collecting information from its environment, and problems arise when they are in charge of building a map of the spatial variations of a parameter cooperatively, which we refer to as cooperative mapping. These problems arise in applications such as mapping indoor or outdoor obstacles, ocean sampling, or aerial mapping. A mobile network tasked with exploratory missions faces an abundance of information. In such an information-rich world, there is simply not enough time to sample the entire environment due to the potential delay-sensitive nature of the application as well as other practical constraints. Therefore, it would be beneficial to the advancement of mobile intelligent networks if an environment could be mapped with only a minimum number of samples as opposed sampling the whole environment.

Technology

This technology overcomes current limitations with a novel way for a mobile intelligent network to exploit the sparse representation of the parameter of interest in the transform domain and build a map of the parameter of interest with minimal sensing. The inventors propose a framework that is based upon leveraging the recent results in the area of non-uniform sampling theory. The proposed work allows the nodes to efficiently map areas that are not sensed directly, requiring considerably fewer samples to be taken to effectively map a spatial parameter of interest. The inventors also show how their framework allows a group of mobile nodes (robots) to map the obstacles non-invasively (for instance, before entering a room or a building), with very few measurements and using only wireless transceivers.

Applications/Advantages

• Fewer samples required for same results than with conventional methods
• Efficiently and quickly maps new environments
• Requires only minimal sensing and without directly sensing a large percentage of area
• Novel way of mapping obstacles non-invasively
• Applications in efficient mapping of indoor/outdoor obstacles, ocean mapping, and aerial mapping
• Applications in emergency response, surveillance and security, and battlefield operations

Keywords

Adhoc Networks, Autonomous Systems, Computer Algorithms, Mobile/Wireless Networks, Robotics, Sensor Networks, Sensors, Signal Processing

Related Categories

• Computer Technologies and Algorithms, Circuit Design, and Signal Processing
• Mechanical Engineering and Miscellaneous Devices