ConservationBots: Autonomous Aerial Robot for Fast Robust Wildlife Tracking in Complex Terrains

TL;DR

ConservationBots is an autonomous aerial robot system designed for fast, robust wildlife tracking in complex terrains, combining innovative planning, sensing, and tracking algorithms to outperform manual methods in real-world conservation tasks.

Contribution

The paper introduces a novel autonomous aerial robot with advanced planning and sensing strategies for wildlife tracking, addressing practical challenges in complex environments.

Findings

Robust localization and fast task completion demonstrated in simulations and field tests.

Effective tracking of nocturnal, underground-dwelling wombats compared to expert biologists.

Significant reduction in disturbance to wildlife during tracking operations.

Abstract

Today, the most widespread, widely applicable technology for gathering data relies on experienced scientists armed with handheld radio telemetry equipment to locate low-power radio transmitters attached to wildlife from the ground. Although aerial robots can transform labor-intensive conservation tasks, the realization of autonomous systems for tackling task complexities under real-world conditions remains a challenge. We developed ConservationBots-small aerial robots for tracking multiple, dynamic, radio-tagged wildlife. The aerial robot achieves robust localization performance and fast task completion times -- significant for energy-limited aerial systems while avoiding close encounters with potential, counter-productive disturbances to wildlife. Our approach overcomes the technical and practical problems posed by combining a lightweight sensor with new concepts: i) planning to determine both trajectory and measurement actions guided by an information-theoretic objective, which allows the robot to strategically select near-instantaneous range-only measurements to achieve faster localization, and time-consuming sensor rotation actions to acquire bearing measurements and achieve robust tracking performance; ii) a bearing detector more robust to noise and iii) a tracking algorithm formulation robust to missed and false detections experienced in real-world conditions. We conducted extensive studies: simulations built upon complex signal propagation over high-resolution elevation data on diverse geographical terrains; field testing; studies with wombats (Lasiorhinus latifrons; nocturnal, vulnerable species dwelling in underground warrens) and tracking comparisons with a highly experienced biologist to validate the effectiveness of our aerial robot and demonstrate the significant advantages over the manual method.