An Autonomous, End-to-End, Convex-Based Framework for Close-Range Rendezvous Trajectory Design and Guidance with Hardware Testbed Validation

TL;DR

This paper introduces CORTEX, a real-time autonomous rendezvous framework combining perception and convex optimization, validated through high-fidelity simulation and hardware tests, demonstrating precise docking under various uncertainties.

Contribution

The paper presents CORTEX, a novel perception-enabled convex optimization framework for autonomous satellite rendezvous, with integrated safety and robustness features validated in simulation and hardware.

Findings

Achieves docking errors of ~37 mm in simulation under uncertainty.

Demonstrates successful hardware-in-the-loop tests with errors below 9 mm.

Shows robustness to sensor faults and engine failures in simulated scenarios.

Abstract

Autonomous satellite servicing missions must execute close-range rendezvous under stringent safety and operational constraints while remaining computationally tractable for onboard use and robust to uncertainty in sensing, actuation, and dynamics. This paper presents CORTEX (Convex Optimization for Rendezvous Trajectory Execution), an autonomous, perception-enabled, real-time trajectory design and guidance framework for close-range rendezvous. CORTEX integrates a deep-learning perception pipeline with convex-optimisation-based trajectory design and guidance, including reference regeneration and abort-to-safe-orbit logic to recover from large deviations caused by sensor faults and engine failures. CORTEX is validated in high-fidelity software simulation and hardware-in-the-loop experiments. The software pipeline (Basilisk) models high-fidelity relative dynamics, realistic thruster execution, perception, and attitude control. Hardware testing uses (i) an optical navigation testbed to assess perception-to-estimation performance and (ii) a planar air-bearing testbed to evaluate the end-to-end guidance loop under representative actuation and subsystem effects. A Monte-Carlo campaign in simulation includes initial-state uncertainty, thrust-magnitude errors, and missed-thrust events; under the strongest case investigated, CORTEX achieves terminal docking errors of $36.85 \pm 44.46$ mm in relative position and $1.25 \pm 2.26$ mm/s in relative velocity. On the planar air-bearing testbed, 18 cases are executed (10 nominal; 8 off-nominal requiring recomputation and/or abort due to simulated engine failure and sensor malfunctions), yielding terminal errors of $8.09 \pm 5.29$ mm in position and $2.23 \pm 1.72$ mm/s in velocity.