Social robots, such as the CMU CoBot, are becoming more common. These robots use our networking infrastructure in very different ways than the humans for which the infrastructure was designed. In this project, we examine how we can make these robots both use this infrastrucutre more efficiently and how to make use of these robots to monitor and improve our infrastructure.


Robot-based Sensing

In this project, we consider the opportunity of using mobile robots and mobile personal devices (e.g. cell phones) as a practical approach for collecting fine-grain sensor measurements of our indoor environments. The goal is to better understand how our surroundings vary over both space and time and enable agents to more effectively operate in our environments with environment-specific, data-driven decision making.

Such efforts require first developing an effective data collection framework that collects sensor measurements from a wide range of mobile devices that can be found across our environments. We focus specifically on mobile devices and robots because they can collect sensor measurements from numerous locations across our environments by simply moving around.

This project focuses on the task of data collection from mobile sources including both cell phones and autonomous robots. We are investigating data collection frameworks, the challenges of analyzing fine-grain measurements, active navigation strategies to ensure up-to-date maps, and applications that use such maps allow agents to make timely and accurate decisions.


People


Publications

“Multi-robot information sharing for complementing limited perception: A case study of moving ball interception”
by Richard Wang, Manuela Veloso, and Srinivasan Seshan.
In Proceedings of IEEE ICRA, (Karlsruhe, Germany), May 2013.
Details. Download: PDF.

“Iterative Snapping of Odometry Trajectories for Path Identification”
by Richard Wang, Manuela Veloso, and Srinivasan Seshan.
In Proceedings of the RoboCup Symposium, (Eindhoven, Netherlands), July 2013.
Details. Download: PDF.

“O-Snap: Optimal snapping of odometry trajectories for route identification”
by Richard Wang, Manuela Veloso, and Srinivasan Seshan.
In Proceedings of IEEE ICRA, (Hong Kong, China), May 2014, pp. 5824-5829, IEEE.
Details. Download: PDF.

“Indoor Trajectory Identification: Snapping with Uncertainty”
by Ravi Shroff, Y. Zha, Richard Wang, Manuela Veloso, and Srinivasan Seshan.
In Proceedings of Workshops at the Twenty-Ninth AAAI Conference on Artificial Intelligence, (Austin, TX), Jan. 2015.
Details. Download: PDF.

“Wireless Map-Based Handoffs for Mobile Robots”
by Richard Wang, Matthew Mukerjee, Manuela Veloso, and Srinivasan Seshan.
In Proceedings of IEEE ICRA, (Seattle, WA), May 2015.
Details. Download: PDF.

“Indoor Trajectory Identification: Snapping with Uncertainty”
by Richard Wang, Ravi Shroff, Y. Zha, Manuela Veloso, and Srinivasan Seshan.
In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'15), (Hamburg, Germany), Sep. 2015.
Details. Download: PDF.

“Using Autonomous Robots to Diagnose Wireless Connectivity”
by Richard Wang, Manuela Veloso, and Srinivasan Seshan.
In Workshop on The Path to Success: Failures in rEal Robots (FinE-R)(FINER'15), (Hamburg, Germany), Oct. 2015.
Details. Download: PDF.

“Active Sensing Data Collection with Autonomous Mobile Robots”
by Richard Wang, Manuela Veloso, and Srinivasan Seshan.
In Proceedings of IEEE ICRA, (Stockholm, Sweden), May 2016.
Details.