Murali Ramaswamy Chari

Smartphones power flying robots

Consumer grade technology seen in cameras and phones has led to the price/performance ratio of sensors and processors falling dramatically over the last decade. In particular, most devices are packaged with a camera, a gyroscope, and an accelerometer, important sensors for aerial robotics. The low mass and small form factor make them particularly well suited for autonomous flight with small flying robots, especially in GPS-denied environments. In this work, we present the first fully autonomous smartphone-based quadrotor. All the computation, sensing and control runs on an off-the-shelf smartphone, with all the software functionality in a smartphone app.We show how quadrotors can be stabilized and controlled to achieve autonomous flight in indoor buildings with application to smart homes, search and rescue, construction and architecture. The work allows any consumer with a smartphone to autonomously drive a quadrotor robot platform, even without GPS, by downloading an app, and concurrently build 3-D maps.

Information-theoretic database building and querying for mobile augmented reality applications

Recently, there has been tremendous interest in the area of mobile Augmented Reality (AR) with applications including navigation, social networking, gaming and education. Current generation mobile phones are equipped with camera, GPS and other sensors, e.g., magnetic compass, accelerometer, gyro in addition to having ever increasing computing/graphics capabilities and memory storage. Mobile AR applications process the output of one or more sensors to augment the real world view with useful information. This papers focus is on the camera sensor output, and describes the building blocks for a vision-based AR system. We present information-theoretic techniques to build and maintain an image (feature) database based on reference images, and for querying the captured input images against this database. Performance results using standard image sets are provided demonstrating superior recognition performance even with dramatic reductions in feature database size.

A swarm of flying smartphones

In the last decade, consumer electronic devices such as smartphones, are packaged with small cameras, gyroscopes, and accelerometers, all sensors allowing autonomous deployment of aerial robots in GPS-denied environments. Our previous work [1], demonstrated the feasibility of using smartphones for autonomous flight. In many applications, there is a large interest to the use multiple autonomous aerial vehicles in a cooperative manner to speed up the operation of the mission. In this work, we present the first fully autonomous smartphone-based swarm of quadrotors. Multiple vehicles are able to plan safe trajectories avoiding inter-robot collisions, optimizing at the same time a given task and concurrently building in a cooperative manner a 3-D map of the environment. The sensing, sensor fusion, control, and planning are all done on an offthe- shelf Samsung Galaxy S5 smartphone using just the single camera and IMU available on the phone. The work allows any consumer with multiple smartphones to autonomously drive a swarm of multiple vehicles without GPS, by downloading an app, and have the swarm cooperatively map a 3-D environment.

MediaFLO Technology: FLO Air Interface Overview

MediaFLOTM is a mobile broadcast technology based on open and global standards. A key component of MediaFLO is the FLOTM (Forward Link Only) air interface technology which has multiple published Telecommunications Industry Association (TIA) [13] specifications. FLO is also recognized by ITU-R as a recommended technology for mobile broadcasting and is in the approval process at the European Telecommunications Standards Institute (ETSI). Global standardization efforts are driven and supported by the FLO Forum [3], an industry consortia consisting of 90+ member companies throughout the global mobile broadcast value chain. MediaFLO technology has been launched commercially in the United States (USA) through the nationwide mobile broadcast network built by MediaFLO USA, Inc [10]. Verizon Wireless has deployed MediaFLO services in 50 U.S. markets, and AT&T expects to launch commercial services in early 2008 leveraging the MediaFLO USA network. In addition, MediaFLO technology is being trialed in major markets around the world. Unlike other mobile broadcast technologies that have evolved from legacy systems, MediaFLO was designed from the ground up for the mobile environment. Consequently, it can deliver mobile broadcast services in a very efficient manner and offers unique advantages such as low receiver power consumption, fast channel switching time, robust reception in mobile fading channels, high spectral efficiency and efficient statistical multiplexing of service channels. MediaFLO technology achieves all of these advantages simultaneously without compromising one for another. Figure 7.1 shows the MediaFLO protocol stack on the interface between the MediaFLO network and the MediaFLO device. The FLO Air Interface specification consists of Physical Layer, MAC (Medium Access Control) Layer, Control Layer

Autonomous flight and cooperative control for reconstruction using aerial robots powered by smartphones

Advances in consumer electronics products and the technology seen in personal computers, digital cameras, and smartphones phones have led to the price/performance ratio of sensors and processors falling dramatically over the last decade. In particular, many consumer products are packaged with small cameras, gyroscopes, and accelerometers, all sensors that are needed for autonomous robots in GPS-denied environments. The low mass and small form factor make them particularly well suited for autonomous flight with small flying robots. In this work, we present the first fully autonomous smartphone-based system for quadrotors. We show how multiple quadrotors can be stabilized and controlled to achieve autonomous flight in indoor buildings with application to smart homes, search and rescue, monitoring construction projects, and developing models for architecture design. In our work, the computation for sensing and control runs on an off-the-shelf smartphone, with all the software functionality embedded in a smartphone app. No additional sensors or processors are required for autonomous flight. We are also able to use multiple, coordinated autonomous aerial vehicles to improve the efficiency of our mission. In our framework, multiple vehicles are able to plan safe trajectories avoiding inter-robot collisions, while concurrently building in a cooperative manner a three-dimensional map of the environment. The work allows any consumer with any number of robots equipped with smartphones to autonomously drive a team of quadrotor robots, even without GPS, by downloading our app and cooperatively build three-dimensional maps.