Quadrotor control for RF source localization and tracking

Preliminary results on quadrotor control strategies enabling omnidirectional radio frequency (RF) sensing for source localization and tracking are discussed. The use of a quadrotor for source localization and tracking requires a tight coupling of the attitude control and RF sensing designs. We present a controller for tracking a ramp reference input in yaw (causing rotation of quadrotor) while maintaining a constant altitude hover or translation. The ability to track a ramp in the yaw angle is crucial for RF bearing estimation using received signal strength (RSS) measurements from a directional antenna as it avoids the need for additional gimbaling payload. This bearing or angle of arrival (AOA) estimate is then utilized by a particle filter for source localization and tracking. We report on extensive experiments that suggest that this approach is appropriate even in complex indoor environments where multipath fading effects are difficult to model.

[1]  Raffaello D'Andrea,et al.  Quadrocopter Trajectory Generation and Control , 2011 .

[2]  Vijay Kumar,et al.  Minimum snap trajectory generation and control for quadrotors , 2011, 2011 IEEE International Conference on Robotics and Automation.

[3]  Dezhen Song,et al.  Localization of Unknown Networked Radio Sources Using a Mobile Robot with a Directional Antenna , 2007, 2007 American Control Conference.

[4]  Jonathan P. How,et al.  Actuator Constrained Trajectory Generation and Control for Variable-Pitch Quadrotors , 2012 .

[5]  Rogelio Lozano,et al.  Quad Rotorcraft Control: Vision-Based Hovering and Navigation , 2012 .

[6]  Peter Biber,et al.  Wireless node localization based on RSSI using a rotating antenna on a mobile robot , 2009, 2009 6th Workshop on Positioning, Navigation and Communication.

[7]  Claire J. Tomlin,et al.  Quadrotor Helicopter Flight Dynamics and Control: Theory and Experiment , 2007 .

[8]  Rogelio Lozano,et al.  Quad Rotorcraft Switching Control: An Application for the Task of Path Following , 2014, IEEE Transactions on Control Systems Technology.

[9]  Tao Yang,et al.  Feedback particle filter-based multiple target tracking using bearing-only measurements , 2012, 2012 15th International Conference on Information Fusion.

[10]  S. Sastry,et al.  Output tracking control design of a helicopter model based on approximate linearization , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).

[11]  B N Hood,et al.  Estimating DoA From Radio-Frequency RSSI Measurements Using an Actuated Reflector , 2011, IEEE Sensors Journal.

[12]  Brian M. Sadler,et al.  RF source-seeking by a micro aerial vehicle using rotation-based angle of arrival estimates , 2013, 2013 American Control Conference.

[13]  F. Tufvesson,et al.  Radio and IMU based indoor positioning and tracking , 2012, 2012 19th International Conference on Systems, Signals and Image Processing (IWSSIP).

[14]  Gang Wang,et al.  I am the antenna: accurate outdoor AP location using smartphones , 2011, MobiCom '11.

[15]  Fredrik Gustafsson,et al.  On Resampling Algorithms for Particle Filters , 2006, 2006 IEEE Nonlinear Statistical Signal Processing Workshop.

[16]  Gaurav S. Sukhatme,et al.  Relative bearing estimation from commodity radios , 2009, 2009 IEEE International Conference on Robotics and Automation.

[17]  Vijay Kumar,et al.  Localization using ambiguous bearings from radio signal strength , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.