Ai Gao

Real-time Navigation for Mars Final Approach Using X-ray Pulsars

An accurate knowledge of Mars entry condition is the significant requirement for the successful aerocapture and pinpoint landing. In order to develop the real-time navigation scheme for Mars final approach, the feasibility of navigation embedded X-ray pulsar observations is verified, and the navigation performance is comparatively analyzed. In order to choose optimal navigation pulsars from pulsar candidates, the Fisher information matrix is utilized to evaluate the observability from the estimation theory point of view. The optimal navigation pulsars thus are selected such that the determinant of the Fisher information matrix is maximal. Two navigation scenarios based on the 2012 encounter at Mars of Curiosity spacecraft combining with X-ray pulsar based measurements are then considered to demonstrate the navigation performance. Furthermore, a series of research on the error ellipse in Mars B-plane and the distribution of estimated flight path angle indicate that Xray pulsar based navigation, which may provide more accurate knowledge of Mars entry condition, is a potential navigation scheme for Mars final approach in the future.

Research on optical/inertial integrated navigation for soft landing on asteroids using mixed H 2 /H ∞ filter

Divergence of traditional Kalman filtering will happen while observation or system noise does not accorded with hypothesis and H<inf>∞</inf> filtering has not enough precision although robustness, so the popular style is the mixed H<inf>2</inf>/H<inf>∞</inf> filtering. Aiming at the problem, this paper puts forward a kind of filtering way which mixes filtering mode using a weighted combination of the H<inf>2</inf> and H<inf>∞</inf> gains without creating model for noise, and applies the algorithm to the optical/inertial integrated navigation system. The simulation results indicate that the optical/inertial integrated navigation system for soft landing on asteroids using the mixed H<inf>2</inf>/H<inf>∞</inf> filter improves the robustness as guaranteeing the enough precision of the navigation system.

Online Landing Site Selection Considering Maneuverability Constraint during Mars Powered Descent Phase

In Mars landing process, smaller hazards like rocks and craters can only be detected when the vehicle is near the surface. The original landing point might be found dangerous and thus the onboard selection of a new landing site and a real-time trajectory generation become the key to the success of the whole mission. In this paper, an autonomous online safe landing site selection considering maneuverability constraint during powered descent phase is proposed. The new landing site is selected based on a novel criterion called Landing Site Selection Index (LSSI). The index includes not only factors like safety of the terrain in view and terminal motion state, but also the maneuverability of the vehicle. A real-time slidingmode guidance is adopted to transfer the vehicle to the updated destination. The online selection and transfer process ensures the safety of the landing mission from multiple aspects. Further Monte Carlo simulations show the effectiveness and robustness of the scheme.

An action guided constraint satisfaction technique for planning problem

This paper presents an action guided constraint satisfaction technique for planning problem. Different from the standard algorithms which are almost domain independence and cannot reflect the characteristics of the planning progress, we discuss how the action rules in planning act in constraint satisfaction problems. Based on the conclusion, an action directed constraint is proposed to guide the variable selected procedure in constraint satisfaction problems. Through theoretical analysis, this technique is prior an order of magnitude in variable select procedure over the ordinary heuristic technique and can be used in constraint-programmed planning problem generally. With the simulation experiments it shows that the algorithm with action guided constraint can effectively reduce the number of constraint checks during the planning procedure and has a better performance on total running time over the standard version.

A geometric dynamic temporal reasoning method with tags

Temporal reasoning is one of the cognitive capabilities humans involve in communicating with others and everything appears related because of temporal reference. Therefore, in this paper a geometric dynamic temporal reasoning algorithm is proposed to solve the temporal reasoning problem, especially in autonomous planning and scheduling. This method is based on the representation of actions in a two dimensional coordination system. The main advantage of this method over others is that it uses tags to mark new constraints added into the constraint network, which leads the algorithm to deal with pending constraints rather than all constraints. This characteristic makes the algorithm suitable for temporal reasoning, where variables and constraints are always added dynamically. This algorithm can be used not only in intelligent planning, but also computational intelligence, real-time systems, and etc. The results show the efficiency of our algorithm from four cases simulating the planning and scheduling process.

An Action Guided Constraint Satisfaction Technique for Planning Problem

This paper presents an action guided constraint satisfaction technique for planning problem. Different from the standard algorithms which are almost domain independence and cannot reflect the characteristics of the planning progress, we discuss how the action rules in planning act in constraint satisfaction problems. Based on the conclusion, an action directed constraint is proposed to guide the variable selected procedure in constraint satisfaction problems. Through theoretical analysis, this technique is prior an order of magnitude in variable select procedure over the ordinary heuristic technique and can be used in constraint-programmed planning problem generally. With the simulation experiments it shows that the algorithm with action guided constraint can effectively reduce the number of constraint checks during the planning procedure and has a better performance on total running time over the standard version.

A Geometric Dynamic Temporal Reasoning Method with Tags for Cognitive Systems

Temporal reasoning is one of the cognitive capabilities humans involve in communicating with others and everything appears related because of temporal reference. Therefore, in this paper a geometric dynamic temporal reasoning algorithm is proposed to solve the temporal reasoning problem, especially in autonomous planning and scheduling. This method is based on the representation of actions in a two dimensional coordination system. The main advantage of this method over others is that it uses tags to mark new constraints added into the constraint network, which leads the algorithm to deal with pending constraints rather than all constraints. This characteristic makes the algorithm suitable for temporal reasoning, where variables and constraints are always added dynamically. This algorithm can be used not only in intelligent planning, but also computational intelligence, real-time systems, and etc. The results show the efficiency of our algorithm from four cases simulating the planning and scheduling process.