Future space missions depend on autonomous rendezvous, ranging from human exploration and large-scale in-orbit assembly to debris removal and satellite servicing. Classical strategies such as V- and R-Bar hopping have been extensively used due to their safety guarantees, holding points, and structured phases, yet their implementation has traditionally relied on pre-generated trajectories that are executed in flight. This approach limits adaptability and does not fully exploit modern control techniques, particularly when mission-specific constraints such as Keep Out Zones or spacecraft restrictions must be considered.

This work addresses these limitations by proposing a model predictive control formulation for the short-range phase of rendezvous that reconstructs classical V-, R-Bar, and generalized glideslope hopping approaches while recovering them directly in the optimization problem. The proposed framework incorporates additional mission constraints, including Keep Out Zones enforced via Control Barrier Functions, alongside the approaches, ensuring they remain valid under different dynamical models. The results show that the controller is able to autonomously recover the expected classical hopping behaviors, maintain passive abort safety, and satisfy constraints in both single-run and Monte Carlo simulations.