Survey of autonomous guidance methods for powered planetary landing

This paper summarizes the autonomous guidance methods(AGMs)for pinpoint soft landing on celestial surfaces.We first review the development of powered descent guidance methods,focusing on their contributions for dealing with constraints and enhancing computational efficiency.With the increasing demand for reusable launchers and more scientific returns from space exploration,pinpoint soft landing has become a basic requirement.Unlike the kilometer-level precision for previous activities,the position accuracy of future planetary landers is within tens of meters of a target respecting all constraints of velocity and attitude,which is a very difficult task and arouses renewed interest in AGMs.This paper states the generalized three-and six-degree-of-freedom optimization problems in the powered descent phase and compares the features of three typical scenarios,i.e.,the lunar,Mars,and Earth landing.On this basis,the paper details the characteristics and adaptability of AGMs by comparing aspects of analytical guidance methods,numerical optimization algorithms,and learning-based methods,and discusses the convexification treatment and solution strategies for non-convex problems.Three key issues related to AGM application,including physical feasibility,model accuracy,and real-time performance,are presented afterward for discussion.Many space organizations,such as those in the United States,China,France,Germany,and Japan,have also developed free-flying demonstrators to carry out related research.The guidance methods which have been tested on these demonstrators are briefly introduced at the end of the paper.

IoV and Blockchain-Enabled Driving Guidance Strategy in Complex Traffic Environment

Diversified traffic participants and complex traffic environment(e.g.,roadblocks or road damage exist)challenge the decision-making accuracy of a single connected and autonomous vehicle(CAV)due to its limited sensing and computing capabilities.Using Internet of Vehicles(IoV)to share driving rules between CAVs can break limitations of a single CAV,but at the same time may cause privacy and safety issues.To tackle this problem,this paper proposes to combine IoV and blockchain technologies to form an efficient and accurate autonomous guidance strategy.Specifically,we first use reinforcement learning for driving decision learning,and give the corresponding driving rule extraction method.Then,an architecture combining IoV and blockchain is designed to ensure secure driving rule sharing.Finally,the shared rules will form an effective autonomous driving guidance strategy through driving rules selection and action selection.Extensive simulation proves that the proposed strategy performs well in complex traffic environment,mainly in terms of accuracy,safety,and robustness.

Development of A Three-Dimensional Guidance System for Long-Range Maneuvering of A Miniature Autonomous Underwater Vehicle

The present paper introduces a three-dimensional guidance system developed for a miniature Autonomous Underwater Vehicle（AUV）. The guidance system determines the best trajectory for the vehicle based on target behavior and vehicle capabilities. The dynamic model of this novel AUV is derived based on its special characteristics such as the horizontal posture and the independent diving mechanism. To design the guidance strategy, the main idea is to select the desired depth, presumed proportional to the horizontal distance of the AUV and the target. By connecting the two with a straight line, this strategy helps the AUV move in a trajectory sufficiently close to this line. The adjacency of the trajectory to the line leads to reasonably short travelling distances and avoids unsafe areas. Autopilots are designed using sliding mode controller. Two different engagement geometries are considered to evaluate the strategy＇s performance： stationary target and moving target. The simulation results show that the strategy can provide sufficiently fast and smooth trajectories in both target situations.

新一代运载火箭自主控制技术

This paper introduces the autonomous control technologies for a new generation launch vehicle for guidance and attitude control.Based on the iterative guidance mode(IGM)of Long March launch vehicles,the autonomous compensation IGM(ACIGM)for the terminal attitude deviation during the coasting phase is proposed.Considering the characteristics of large static instability and weak bearing capacity,the attitude control technology based on active disturbance rejection control(ADRC)and a control method based on an accelerometer are proposed.Targeting at non-fatal failures that may occur during flights,autonomous guidance reconstruction technology,nozzle fault diagnosis and reconstruction technology in the coasting phase are studied.Some of the autonomous control technologies proposed in this paper have achieved good control results as seen through flight verification.

Design and guidance of a multi-active debris removal mission

Space debris have become exceedingly dangerous over the years as the number of objects in orbit continues to increase.Active debris removal(ADR)missions have gained significant interest as effective means of mitigating the risk of collision between objects in space.This study focuses on developing a multi-ADR mission that utilizes controlled reentry and deorbiting.The mission comprises two spacecraft:a Servicer that brings debris to a low altitude and a Shepherd that rendezvous with the debris to later perform a controlled reentry.A preliminary mission design tool(PMDT)was developed to obtain time and fuel optimal trajectories for the proposed mission while considering the effect of J2,drag,eclipses,and duty cycle.The PMDT can perform such trajectory optimizations for multi-debris missions with computational time under a minute.Three guidance schemes are also studied,taking the PMDT solution as a reference to validate the design methodology and provide guidance solutions to this complex mission profile.

Robust guidance method with terminal impact angle constraint for autonomous underwater vehicle

Based on robust control design method,a variable structure guidance method is proposed for autonomous underwater vehicle(AUV) during the guiding course with terminal impact angle constraint.Considering the intercept geometry,a sliding mode controller is proposed for controlling the hne of sight angle rate and the impact angle,based on the principle which controls the line of sight angle rate to approach zero and the terminal angle to approach the expected value more quickly as the distance decreases.Simulation results show that,with the application of the proposed method,small miss distance is achieved and the expected impact angle is reached.In addition,the system is robust to the target maneuvering.