NASA’s Jet Propulsion Laboratory (JPL) has developed a probabilistic algorithm for hazard detection and avoidance (HDA) that robustly handles sensor noise. Conventional surface characterization methods use fixed hazard thresholds to determine hazardous landing locations; these thresholds are set lower than lander tolerances to compensate for sensor noise, but this leads to excessive false alarms and significantly reduces the number of safe locations. JPL’s probabilistic method seamlessly combines the distance to nearest hazard and the local roughness, and incorporates the presence of navigation errors to determine the probability that a given location is a safe landing site. This innovative algorithm enables onboard hazard detection and avoidance to increase the probability of safe landing and allow landings in more scientifically interesting but challenging sites.
JPL’s probabilistic, LIDAR-based HDA approach models the sensor noise to characterize the probability of the accuracy of the reconstructed surface’s representation. The algorithm further incorporates a navigation uncertainty model and a landing site selection process. For each location, the full extent of the area under the lander is inspected for hazard assessment, and surface features become hazards as a function of lander characteristics such as design geometry and tolerance to slope and roughness.
The HDA algorithms have been demonstrated and their performance evaluated with test cases designed to validate expectations, and with Monte Carlo simulations designed to validate overall performance in the presence of noise and uncertainty. The results show that slope detection on crater rims and steep terrain and roughness detection inside craters are improved with the probabilistic HDA approach. In addition, modeling the lander slope using pad placement rather than plane fit results in better hazard detection and therefore safer landing.
Possible applications for
this technology include autonomous helicopter landing/defense rescue, supply delivery, disaster assistance, and planetary exploration.