Landmarks based path planning for UAVs in GPS-denied areas∗

Abstract In this paper, we propose a UAV path planner travelling from a given source to goal location in GPS-denied areas. The environment consists of a set of cellular towers which are treated as landmarks having finite communication range. The vehicle has to perform dead reckoning in regions where landmarks are not available. Therefore, the objective is to determine a time optimal path taking the presence of landmarks into account while ensuring the covariance due to dead-reckoning is within a given bound. Solving the stochastic optimal control problem to determine a path in the continuous domain is very difficult and hence we discrete the path as a set of way points and optimize the location of these way points to obtain a time optimal path satisfying the covariance bounds. We use a particle swarm optimization technique coupled with a rabbit-carrot based path following technique to determine a near-optimal path. Numerical results are presented to show that our approach produces feasible paths that are near-optimal and satisfy the covariance bounds.

[1]  Michael N. Vrahatis,et al.  Recent approaches to global optimization problems through Particle Swarm Optimization , 2002, Natural Computing.

[2]  Sanjiv Singh,et al.  Experimental results in range-only localization with radio , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[3]  J.G. Hanse.  Honeywell MEMS inertial technology & product status , 2004, PLANS 2004. Position Location and Navigation Symposium (IEEE Cat. No.04CH37556).

[4]  Sivakumar Rathniam,et al.  A multiple vehicle path covering problem with localization constraints: Formulation and algorithms , 2015, 2015 American Control Conference (ACC).

[5]  Jonathan P. How,et al.  Health aware stochastic planning for persistent package delivery missions using quadrotors , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  Roland Siegwart,et al.  Vision based MAV navigation in unknown and unstructured environments , 2010, 2010 IEEE International Conference on Robotics and Automation.

[7]  S. Sukkarieh,et al.  SLAM aided GPS/INS Navigation in GPS Denied and Unknown Environments , 2004 .

[8]  Jiafu Wan,et al.  Issues and Challenges of Wireless Sensor Networks Localization in Emerging Applications , 2012, 2012 International Conference on Computer Science and Electronics Engineering.

[9]  Sangkyung Sung,et al.  IMU/Vision/Lidar integrated navigation system in GNSS denied environments , 2013, 2013 IEEE Aerospace Conference.

[10]  Claire J. Tomlin,et al.  Sensor Placement for Improved Robotic Navigation , 2010, Robotics: Science and Systems.

[11]  Maciej Stachura,et al.  Cooperative Target Localization with a Communication-Aware Unmanned Aircraft System , 2010 .

[12]  P. B. Sujit,et al.  Unmanned Aerial Vehicle Path Following: A Survey and Analysis of Algorithms for Fixed-Wing Unmanned Aerial Vehicless , 2014, IEEE Control Systems.

[13]  Matthew Trinkle,et al.  GPS interference mitigation; Overview and experimental results , 2001 .

[14]  Steven Lake Waslander,et al.  Planning Paths for Package Delivery in Heterogeneous Multirobot Teams , 2015, IEEE Transactions on Automation Science and Engineering.

[15]  Alberto Speranzon,et al.  Multi-objective path planning in GPS denied environments under localization constraints , 2014, 2014 American Control Conference.