The aerogravity-assist maneuver is proposed as a tool to improve the efficiency of the gravity assist, because due to the interaction with the planetary atmosphere, the angular deviation of the velocity vector can be definitely increased. Even though the drag reduces the spacecraft velocity, the overall A v gain could be substantial for a high-lift-to-drag vehicle. A previous study addressed the three-dimensional dynamic modeling and optimization of the maneuver, including heliocentric plane change, heating rate, and structural load analysis. A multidisciplinary study of aerogravity assist is proposed, focusing on coupled trajectory and vehicle shape optimization. A planar aerogravity assist of Mars is selected as a test case, with the aim of maximizing the vehicle heliocentric velocity and limiting the heating rate experienced during the atmospheric pass. A multiobjective approach is adopted, and a particle swarm optimization algorithm is chosen to detect the set of Pareto-optimal solutions. The study includes a further refinement of the trajectory for three significant shapes belonging to the Pareto curve. The associated optimal control problem is solved by selecting a direct-method approach. The dynamics are transcribed into a set of nonlinear constraints, and the arising nonlinear programming problem is solved through a sequential quadratic programming solver.