Autonomous Active Mapping in Steep Alpine Environments with Fixed-wing Aerial Vehicles

TL;DR

This work tackles autonomous avalanche-area mapping in steep alpine terrain using a fixed-wing sUAS. It formulates safety-critical navigation via circular loiter-based planning and a finite-state machine, and couples this with an online active photogrammetry framework implemented as an MDPMCTS planner to maximize information gain. The system integrates a tiltrotor VTOL platform, high-resolution imaging, and a Fisher-information-based viewpoint planning approach, validated in field tests in Davos, showing improved mapping quality over traditional sweep-pattern plans. The results demonstrate practical viability for autonomous fixed-wing operations in challenging alpine environments and highlight avenues for broader close-terrain data gathering with enhanced perception and wind handling.

Abstract

Monitoring large scale environments is a crucial task for managing remote alpine environments, especially for hazardous events such as avalanches. One key information for avalanche risk forecast is imagery of released avalanches. As these happen in remote and potentially dangerous locations this data is difficult to obtain. Fixed-wing vehicles, due to their long range and travel speeds are a promising platform to gather aerial imagery to map avalanche activities. However, operating such vehicles in mountainous terrain remains a challenge due to the complex topography, regulations, and uncertain environment. In this work, we present a system that is capable of safely navigating and mapping an avalanche using a fixed-wing aerial system and discuss the challenges arising when executing such a mission. We show in our field experiments that we can effectively navigate in steep terrain environments while maximizing the map quality. We expect our work to enable more autonomous operations of fixed-wing vehicles in alpine environments to maximize the quality of the data gathered.

Figures (8)

• Figure 1: Image of the tiltrotor VTOL platform during take-off during the field test in a narrow valley in Davos, Switzerland.
• Figure 2: Valid loiter positions overlaid as a blue surface over the terrain where the field test was conducted. The minimum and maximum distance constraint is defined as 50m and 120m. The magenta region shows the region of interest.
• Figure 3: Finite state machine of vehicle operations. Dotted transitions are triggered by the operator, and the Solid transitions are triggered upon task completion of the state. Each state is color-coded uniquely for visualizations in Fig. \ref{['fig:davos_reference_altitude']} Fig. \ref{['fig:hinwil_mapping_results']}
• Figure 4: Overview of the system that was used for flight testing. The system consists of a Mission computer, FMU which are controlled by an operator and a safety pilot.
• Figure 5: Altitude of the reference position and terrain visualized during the mission. The reference is color-coded with the vehicle state as in Fig. \ref{['fig:fsm']}. The vehicle satisfies the distance-to-terrain constraints visualized as the blue overlay.