Mapping a chaser satellite's feasibility space for soft docking

Space missions are becoming increasingly complex, and engineers are designing multi-satellite architectures with on-orbit operations as means of accomplishing several mission objectives. Multiple concepts have emerged for autonomous robotic servicing and assembly of orbiting assets or the active removal of space debris, all of which rely on close proximity operation of independently controlled elements. In order for engineers to assess whether a chaser satellite can perform a rendezvous and docking to a given target, various factors must be assessed, including the fuel required, maximum thrust required, contact forces and torques, and the time necessary from rendezvous to secure docking. These factors may be defined for any pair of chaser and target satellites. This paper proposes a definition of a feasibility space, consisting of the set of values for the chaser and target over which a given chaser satellite can perform a soft dock to the target. This feasibility space is defined with respect to the target satellite's physical parameters and dynamic state. In order to map the feasibility space, a trajectory type must be specified. This study utilizes an Archimedes Spiral rendezvous approach path. While not a fuel or time optimal trajectory, it has been selected for this analysis because its path may be expressed analytically while the chaser faces the target's docking area throughout the maneuver, thereby keeping the docking location in the field of view of the chaser's rendezvous sensors for as much time as possible. The paper presents the analytical computation of the chaser satellite's requirements based on the expression of an Archimedes Spiral, as well as a method for mapping the feasibility space using non-dimensional parameters to aid in the extensibility for one trajectory type to multiple chasers and targets. Additionally, the paper presents a method of using the resultant feasibility space maps to assist mission planners and chaser satellite designers in determining the likelihood of soft docking success for a given point in the feasibility space. The processes discussed in the paper can be applied to other trajectory types and for any type of chaser or target satellite for future missions.

[1]  Lydia Tapia,et al.  Stochastic reachability based motion planning for multiple moving obstacle avoidance , 2014, HSCC.

[2]  Meeko M. K. Oishi,et al.  Computing probabilistic viable sets for partially observable systems using truncated gaussians and adaptive gridding , 2015, 2015 American Control Conference (ACC).

[3]  Ian M. Mitchell,et al.  The continual reachability set and its computation using maximal reachability techniques , 2011, IEEE Conference on Decision and Control and European Control Conference.

[4]  A. Krener,et al.  Nonlinear controllability and observability , 1977 .

[5]  Meeko M. K. Oishi,et al.  Reachability analysis for continuous systems under shared control: Application to user-interface design , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[6]  Ian M. Mitchell,et al.  Computing the viability kernel using maximal reachable sets , 2012, HSCC '12.

[7]  N. Matni,et al.  Reachability-based abstraction for an aircraft landing under shared control , 2008, 2008 American Control Conference.

[8]  Meeko M. K. Oishi,et al.  Schur-based decomposition for reachability analysis of linear time-invariant systems , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[9]  Katsuhiko Ogata,et al.  Modern Control Engineering , 1970 .

[10]  Tadeusz Kaczorek,et al.  Constructability and observability of standard and positive electrical circuits , 2013 .

[11]  M. Hoagland,et al.  Feedback Systems An Introduction for Scientists and Engineers SECOND EDITION , 2015 .

[12]  Ian M. Mitchell,et al.  Lagrangian methods for approximating the viability kernel in high-dimensional systems , 2013, Autom..

[13]  Meeko Oishi,et al.  User-Interfaces for Hybrid Systems: Analysis and Design through Hybrid Reachability , 2003 .

[14]  Meeko M. K. Oishi,et al.  Reachability for partially observable discrete time stochastic hybrid systems , 2014, Autom..

[15]  Lisa Kaplan The Feasibility of Using Robotic Systems at the International Space Station for Exterior Inspections , 2000 .