ARDEA—An MAV with skills for future planetary missions. Issue 4 (12th March 2020)

• Record Type: Journal Article
• Authors: Lutz, Philipp; Müller, Marcus G.; Maier, Moritz; Stoneman, Samantha; Tomić, Teodor; von Bargen, Ingo; Schuster, Martin J.; Steidle, Florian; Wedler, Armin; Stürzl, Wolfgang; Triebel, Rudolph
• Other Names: Loianno Giuseppe guestEditor.; Scaramuzza Davide guestEditor.
• Is Part Of: Journal of field robotics. Volume 37:Issue 4(2020)
• Page Start: 515
• Page End: 551
• Publication Date: 2020-03-12
• Subjects: aerial robotics -- computer vision -- exploration -- GPS‐denied operation -- planetary robotics; Robots, Industrial -- Periodicals; Automatic control -- Periodicals; 629.892
• DOI: 10.1002/rob.21949
• Languages: English
• ISSNs: 1556-4959

Abstract

Abstract: We introduce a prototype flying platform for planetary exploration: autonomous robot design for extraterrestrial applications (ARDEA). Communication with unmanned missions beyond Earth orbit suffers from time delay, thus a key criterion for robotic exploration is a robot's ability to perform tasks without human intervention. For autonomous operation, all computations should be done on‐board and Global Navigation Satellite System (GNSS) should not be relied on for navigation purposes. Given these objectives ARDEA is equipped with two pairs of wide‐angle stereo cameras and an inertial measurement unit (IMU) for robust visual‐inertial navigation and time‐efficient, omni‐directional 3D mapping. The four cameras cover a 24 0 ∘ vertical field of view, enabling the system to operate in confined environments such as caves formed by lava tubes. The captured images are split into several pinhole cameras, which are used for simultaneously running visual odometries. The stereo output is used for simultaneous localization and mapping, 3D map generation and collision‐free motion planning. To operate the vehicle efficiently for a variety of missions, ARDEA's capabilities have been modularized into skills which can be assembled to fulfill a mission's objectives. These skills are defined generically so that they are independent of the robot configuration, making the approach suitable for different heterogeneous robotic teams. The diverse skill set also makes the micro aerial vehicle (MAV) useful for any task where autonomous exploration is needed. For example terrestrial search and rescue missions where visual navigation in GNSS‐denied indoor environments is crucial, such as partially collapsed man‐made structures like buildings or tunnels. We have demonstrated the robustness of our system in indoor and outdoor field tests.