Publication | Closed Access
Autonomous Safe Landing Site Detection for a Future Mars Science Helicopter
17
Citations
15
References
2021
Year
Unknown Venue
EngineeringField RoboticsFlying RobotUnmanned VehicleAdvanced Navigation CapabilitiesUnmanned SystemMars Science HelicopterMartian ExplorationSystems EngineeringRobot LearningMachine VisionVision RoboticsAutonomous NavigationComputer VisionAerial RoboticsOdometryAerospace EngineeringFuture Mars RotorcraftsRemote SensingRobotics
Future Mars Rotorcrafts require advanced navigation capabilities to enable all terrain access for science investigations with long distance flights that are executed fully autonomously. A critical component is the ability to safely land in hazardous terrain as part of a mission, or triggered by an emergency situation. In this paper, we present an advanced navigation system for continuous on-board terrain reconstruction for the purpose of hazard-free landing site detection for the autonomous navigation of a Mars Science Helicopter - a JPL research concept that investigates the feasibility of flying a multi-kilogram science payload at various Mars science locations, with flight ranges of multiple kilometers per flight. Our approach builds on a vision-based perception system that incorporates an on-board visual-inertial state estimator augmented by a laser altimeter (range-VIO), and a structure-from-motion 3D reconstruction approach that uses a single, downward-looking camera to provide dense depth measurements while the vehicle is in motion. Depth measurements are accumulated in a local, robot-centric, multi- resolution elevation map that is analyzed by a landing site detector to extract safe landing areas below the rotorcraft, based on a heuristic that includes slope, roughness and the presence of landing hazards. Detected landing sites are prioritized by an on-board autonomy engine that either selects suitable landing sites for immediate landing maneuvers, or can explore a terrain location as part of a mission in order to find a best landing site in a pre-planned area. We demonstrate and evaluate our approach on simulated data and data acquired with a surrogate unmanned aerial system (UAS) executing flights over relevant terrain.
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