ESA GNC Conference Papers Repository

Title:
Hazard Avoidance for Planetary Landing: GNC Design and Performance Assessment
Authors:
Parreira, B.; Di Sotto, E.; Rogata, P.; Caramagno, A.; Rebordão, J.
Presented at:
Tralee 2008
DOI:
Full paper:
Abstract:

Technologies for planetary landing have been studied and developed since the late fifties during the Moon race, which culminated in 1969 with the first human landing on the Moon. Nowadays, instead of humans, small probes/landers are sent to distant planetary bodies. These landings are often performed by a pre-programmed time sequence of events that bring the lander to a full stop in a desired area at the planet surface (e.g. ‘pathfinder-type’ is a open-loop landing with airbags; ‘Viking-type’ a semi-automatic landing). Future exploration missions envisage landing on planetary surfaces that are not known apriori, or in areas that are not flat and hazard free as the nominal selected Landing Sites (LS) of the current exploration missions. Landers also tend to become smaller and lighter, not so robust to surface hazards. Autonomous pinpoint soft-landing systems that include Hazard Avoidance (HA) capability are therefore required to guarantee safe landing. An HA system is responsible for the detection of any hazards that put in risk the landing mission and path-planning to avoid the detected hazards. Hazard detection implies the lander to be equipped with proper sensing devices. In the frame of this study, an optical sensor, onboard camera, is used to detect hazards (e.g. craters, rocks, boulders, high slopes, etc.) in the landing zone. This paper briefly describes the developed HA algorithms (already described in more detail in [3]), and presents the work done in the consolidation of the performance assessment of the algorithms on a realistic landing on Mercury. Specifically, the following aspects were studied: assessment of Guidance performance with respect to Navigation errors, Monte Carlo campaign carried out to evaluate the closed loop performance of the HA function, profiling of HA software, and assessment of applicability of HA concept to Mars landing scenario.