The dynamics in the vicinity of small bodies are highly nonlinear. Trajectory design in small-body environments requires accurate gravity and solar radiation pressure models to guarantee the satisfaction of spacecraft operational constraints such as thruster silent times, state, and control constraints. The G-PROX guidance algorithm generates fuel-optimal trajectories in the vicinity of asteroids and small bodies. The non-convexity in the control constraints is handled with the lossless convexification technique, which is a convex relaxation of the control constraints. G-PROX uses sequential convex programming and solves a convergent sequence of convex optimization problems generated via sequential linearization of both the dynamics and control bounds, synergistically combined with lossless convexification. The sequence of convex optimization problems converges to a locally optimal solution of the original nonlinear non-convex problem.
The G-PROX guidance algorithm enforces thruster silent time constraints as well as position, velocity, and control constraints using a convex optimization framework. Prior algorithms used simple control parameterizations that could not satisfy all the operational constraints at once in certain mission scenarios. Additionally, G-PROX optimizes a cost function (e.g., fuel or energy) while satisfying all the operational constraints, whereas prior parametric guidance algorithms could only generate feasible solutions that satisfy boundary conditions without optimizing the cost function and without guaranteeing that state constraints would be satisfied.
The G-PROX guidance algorithm performs autonomous path-planning and control near primitive bodies, enabling auto-piloting (the ability for the spacecraft to optimize and execute translational motion without aid from the ground). G-PROX enables new mission design paradigms that include long-duration surface observations from tens of meters range, precise station keeping, and rapid movement between observations of multiple surface targets.
This work was done by Jordi Casoliva, Stephen B. Broschart, and Shyamkumar Bhaskaran of JPL/Caltech; and Behçet Açıkmeşe and Daniel Dueri of the University of Texas at Austin for NASA’s Jet Propulsion Laboratory.
This software is available for commercial licensing. Please contact Dan Broderick at
This Brief includes a Technical Support Package (TSP).
Autonomous Guidance Algorithm to Auto-Pilot Spacecraft in the Vicinity of Primitive Celestial Bodies
(reference NPO49325) is currently available for download from the TSP library.
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Overview
The document outlines the development of an autonomous guidance algorithm, G-PROX, designed to enable spacecraft to optimize and execute translational motion in the vicinity of primitive celestial bodies, such as asteroids and comets. This technology is crucial for enhancing mission design paradigms, allowing for long-duration surface observations, precise station keeping, rapid movement between multiple targets, and quick responses to unexpected scenarios.
G-PROX operates by requiring a definition of dynamics, control and state constraints, boundary conditions, and a gravity model, while eliminating the need for user-supplied initial guesses or expert adjustments to the optimal solution. The algorithm has been implemented in C programming language, significantly improving computational speed—by approximately 30 times for the G-OPT solver and 5.6 times for G-PROX overall compared to its previous Matlab version.
The document details the performance of G-PROX through various mission scenarios, including the Itokawa touch-and-go landing trajectories and multiple flybys of Comet Tempel 1. For the Itokawa mission, G-PROX generated landing trajectories for 86 locations in just 520 seconds, a substantial improvement over traditional methods that required about an hour per trajectory. The flybys of Comet Tempel 1 involved a sequence of eight consecutive maneuvers with specific periapsis radii, showcasing G-PROX's ability to handle complex constraints and nonlinear dynamics effectively.
The project aims to enhance NASA's Jet Propulsion Laboratory's (JPL) capabilities in autonomous path-planning and control, making it competitive for future missions to primitive bodies. The algorithm's development involved rigorous testing and validation through high-fidelity simulations, ensuring its reliability for real-world applications.
In summary, G-PROX represents a significant advancement in autonomous spacecraft guidance technology, enabling efficient and precise navigation in challenging environments. This innovation not only promises to improve mission outcomes but also enhances the scientific return on investment for space exploration initiatives. The document serves as a comprehensive overview of the algorithm's capabilities, performance metrics, and its potential impact on future space missions.
