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The first step towards aerial planetary exploration has been made. Ingenuity shows extremely promising results, and new missions are already underway. Rotorcraft are capable of flight. This capability could be utilized to support the last stages of Entry, Descent, and Landing. Thus, mass and complexity could be scaled down.
Autorotation is one method of descent. It describes unpowered descent and landing, typically performed by helicopters in case of an engine failure. MAPLE is suggested to test these procedures and understand autorotation on other planets. In this series of experiments, the Ingenuity helicopter is utilized. Ingenuity would autorotate a ”mid-air-landing” before continuing with normal flight. Ultimately, the collected data shall help to understand autorotation on Mars and its utilization for interplanetary exploration.
Autonomous mobile robots operating in unknown terrain have to guide
their drive decisions through local perception. Local mapping and
traversability analysis is essential for safe rover operation and low level
locomotion. This thesis deals with the challenge of building a local,
robot centric map from ultra short baseline stereo imagery for height
and traversability estimation.
Several grid-based, incremental mapping algorithms are compared and
evaluated in a multi size, multi resolution framework. A new, covariance
based mapping update is introduced, which is capable of detecting sub-
cellsize obstacles and abstracts the terrain of one cell as a first order
surface.
The presented mapping setup is capable of producing reliable ter-
rain and traversability estimates under the conditions expected for the
Cooperative Autonomous Distributed Robotic Exploreration (CADRE)
mission.
Algorithmic- and software architecture design targets high reliability
and efficiency for meeting the tight constraints implied by CADRE’s
small on-board embedded CPU.
Extensive evaluations are conducted to find possible edge-case scenar-
ios in the operating envelope of the map and to confirm performance
parameters. The research in this thesis targets the CADRE mission, but
is applicable to any form of mobile robotics which require height- and
traversability mapping.
This paper presents a novel approach to Thrust Vector Control (TVC) for small Unmanned Aerial Vehicles (UAVs). The difficulties associated with conventional feed-forward TVC are outlined, and a practical solution to conquer these challenges is derived. The solution relies on observing boom deformations that are created by different thrust vector directions and high-velocity air inflow. The paper describes the required measurement electronics as well as the implementation of a dedicated testbed that allows the evaluation of mid-flight force measurements. Wind-tunnel tests show that the presented method for active thrust vector determination is able to quantify the disturbances due to the incoming air flow.