The goal of an Active Localization algorithm is to choose measurement locations to minimize the uncertainty of the location of a target as quickly as possible. This research is motivated by deploying mobile robots to find radio transmitters, for which we are developing novel algorithms and systems. Currently, we are working with researchers at the University of Minnesota who are interested in studying the movements of invasive fish in nearby lakes. A general method for localizing low-power radio transmitters has a wide range of applications such as defense, search and rescue, environmental monitoring, or wildlife tracking.
Our system is built on a combination of two commercial platforms: the six-wheel differential drive Husky A100 from Clearpath Robotics for winter operation, and robotic boats used in winter. The overall system comprises of:
- EEE PC running Ubuntu with ROS
- Garmin GPS 18x for robust waypoint navigation
- Radio antenna mounted on pan-tilt unit
- Radio telemetry equipment from ATS-Track.
A key property of the systems is that they use a directionally-sensitive antenna to detect the transmissions from nearby radio tags. This means the robot can rotate the antenna and take multiple samples to determine the bearing to the target. The more samples taken, the more accurate the bearing measurement is. However, since fish biologists use tags with a very low data rate (transmissions are sent at approximately 1 Hz), it can take a long time to gather a enough to construct a bearing measurement, as shown in the following video. The long measurement time means that taking many measurements can dominate the time to travel between them. To minimize the time to localize a target, we must take into account measurement time and travel time between each discrete measurement.
The following videos show our method of collecting bearing measurements as well as the husky navigating on frozen lakes during field trials.
Time-Optimal Active Localization Algorithms
The goal of active-localization is to select sensing locations for the robot so as to minimize the uncertainty in the location of the target as quickly as possible. As mentioned, the time to localize a target is a function of the number of measurements and the distance between them.
For this purpose, we proposed active localization algorithms and evaluated them. We provide closed-form guarantees of the final uncertainty as well as the time required to localize a target. In particular, we analyze the trade-off in time-to-localize versus the accuracy of the final estimate. A worst-case analysis was performed, and we showed that our algorithm is within a constant factor of the optimal cost (see #Related Publications, 2012 Cautious).
Of particular interest is the potential for collaboration between two or more robots. The robots must now communicate to coordinate their measurements as well as exchange the measurement values. We study the problem of simultaneously scheduling measurements as well as communications to locate targets in minimal time. We prove that it is sub-optimal to force the robots to communicate at all times; the optimal algorithm should break communication under some circumstances (See #Related Publications, 2013 Bearing-Only).
The following video highlights the two-robot localization algorithm given in [ #Related Publications, 2013 Bearing-Only].
|7||H. Bayram, J. V. Hook, V. Isler|
Gathering Bearing Data for Target Localization
IEEE Robotics and Automation Letters, 1(1): 369-374, 2016.
|6||J. Vander Hook, P. Tokekar, V. Isler|
Cautious Greedy Strategy for Bearing-Only Active Localization: Analysis and Field Experiments
Journal of Field Robotics, 31(2), 2014.
|5||P. Tokekar, E. Branson, J. Vander Hook, V. Isler|
Tracking Aquatic Invaders: Autonomous Robots for Monitoring Invasive Fish
IEEE Robotics and Automation Magazine, 20(3): 33-41, 2013.
|4|| Joshua Vander Hook, Pratap Tokekar, Volkan Isler|
Bearing-Only Active Target Localization Strategies for a System of Two Communicating Mobile Robots: Full Technical Report
Technical Report, Department of Computer Science, University of Minnesota, 2013.
|3||J. Vander Hook, P. Tokekar, V. Isler|
Cautious Greedy Strategy for Bearing-based Active Localization: Experiments and Theoretical Analysis
In Proc. IEEE/RSJ Int. Conf. on Robotics and Automation, 2012.
|2||J. Vander Hook, P. Tokekar, E. Branson, P. Bajer, P. Sorensen, V. Isler|
Local Search Strategy for Active Localization of Multiple Invasive Fish
In Proc. International Symposium on Experimental Robotics, 2012.
|1||P. Tokekar, J. Vander Hook, V. Isler|
Active Target Localization for Bearing Based Robotic Telemetry
In Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 2011.
This work is supported by NSF Awards #1111638, #0916209, #0917676, #0936710 and a fellowship from the Institute on the Environment at the University of Minnesota.