TrackerBots: Autonomous Unmanned Aerial Vehicle for Real-Time Localization and Tracking of Multiple Radio-Tagged Animals

TL;DR

TrackerBots is an autonomous UAV system that uses RSSI measurements, particle filtering, and POMDP-based planning to efficiently locate multiple radio-tagged animals in real-time, conserving power and improving tracking accuracy.

Contribution

This work introduces a low-cost, lightweight UAV platform utilizing RSSI-based localization, particle filtering, and POMDP planning for multi-animal tracking, which is novel in its integration and real-time capabilities.

Findings

Effective real-time localization of multiple animals demonstrated in simulations.

Field experiments validated the system's accuracy and power efficiency.

The approach reduces exploration time and conserves UAV battery life.

Abstract

Autonomous aerial robots provide new possibilities to study the habitats and behaviors of endangered species through the efficient gathering of location information at temporal and spatial granularities not possible with traditional manual survey methods. We present a novel autonomous aerial vehicle system-TrackerBots-to track and localize multiple radio-tagged animals. The simplicity of measuring the received signal strength indicator (RSSI) values of very high frequency (VHF) radio-collars commonly used in the field is exploited to realize a low cost and lightweight tracking platform suitable for integration with unmanned aerial vehicles (UAVs). Due to uncertainty and the nonlinearity of the system based on RSSI measurements, our tracking and planning approaches integrate a particle filter for tracking and localizing; a partially observable Markov decision process (POMDP) for dynamic path planning. This approach allows autonomous navigation of a UAV in a direction of maximum information gain to locate multiple mobile animals and reduce exploration time; and, consequently, conserve onboard battery power. We also employ the concept of a search termination criteria to maximize the number of located animals within power constraints of the aerial system. We validated our real-time and online approach through both extensive simulations and field experiments with two mobile VHF radio-tags.