UAV4PE: An Open-Source Framework to Plan UAV Autonomous Missions for Planetary Exploration

Abstract

Autonomous Unmanned Aerial Vehicles (UAV) for planetary exploration missions require increased onboard mission-planning and decision-making capabilities to access full operational potential in remote environments (e.g., Antarctica, Mars or Titan). However, the uncertainty introduced by the environment and the limitation of available sensors has presented challenges for planning such missions. Partially Observable Markov Decision Processes (POMDPs) are commonly used to enable decision-making and mission-planning processes that account for environmental, perceptional (extrinsic) and actuation (intrinsics) uncertainty. Here, we propose the UAV4PE framework, a testing framework for autonomous UAV missions using POMDP formulations. This framework integrates modular components for simulation, emulation, UAV guidance, navigation and mission planning. State-of-the-art tools such as python, C++, ROS, PX4 and JuliaPOMDP are employed by the framework, and we used python data-science libraries for the analysis of the experimental results. The source code and the experiment data are included in the UAV4PE framework. The POMDP formulation proposed here was able to plan and command a UAV-based planetary exploration mission in simulation, emulation and real-world experiments. The experiments evaluated key indicators such as the mission success rate, the surface area explored and the number of commands (actions) executed. We also discuss future work aimed at improving the UAV4PE framework, and the autonomous UAV mission planning formulation for planetary exploration.

Tendon-Driven Continuum Robots for Aerial Manipulation—A Survey of Fabrication Methods

“…The willingness to employ UAVs is increasingly evident across various research sectors, industries, government sectors, and the general public. Applications have primarily centered on industrial inspection and monitoring [1], precision agriculture [2,3], disaster management [4], environment monitoring [5][6][7], smart city operations [8], military operations [9], space and planetary exploration [10,11], archaeological exploration [12], and more. The application domains are actively expanding as cutting-edge control and manufacturing technologies are continuously researched and applied in practical scenarios.…”

Multi-UAV Mapping and Target Finding in Large, Complex, Partially Observable Environments

“…However, the complexity and size of the environments is limited, the obstacles are known prior to operation, and the rate of the motion planner is limited to 1Hz, limiting the suitability of the approach in the presence of dynamic hazards. Galvez-Serna et al [16] propose a model-based POMDP framework for planning autonomous UAV planetary exploration missions, validating the performance with simulated and real-world flight testing. Unfortunately, the hazards are known prior to operation and the environment complexity is low.…”