Concept for an Automatic Annotation of Automotive Radar Data Using AI-segmented Aerial Camera Images

This paper presents an approach to automatically annotate automotive radar data with AI-segmented aerial camera images. For this, the images of an unmanned aerial vehicle (UAV) above a radar vehicle are panoptically segmented and mapped in the ground plane onto the radar images. The detected instances and segments in the camera image can then be applied directly as labels for the radar data. Owing to the advantageous bird's eye position, the UAV camera does not suffer from optical occlusion and is capable of creating annotations within the complete field of view of the radar. The effectiveness and scalability are demonstrated in measurements, where 589 pedestrians in the radar data were automatically labeled within 2 minutes.Comment: 6 pages, 5 figures, accepted at IEEE International Radar Conference 2023 to the Special Session "Automotive Radar

Solving the Goddard problem with thrust and dynamic pressure constraints using saturation functions

International audienceThis paper addresses the well-known Goddard problem in the formulation of Seywald and Cliff with the objective to maximize the altitude of a vertically ascending rocket sub ject to dynamic pressure and thrust constraints. The Goddard problem is used to propose a new method to systematically incorporate the constraints into the system dynamics by means of saturation functions. This procedure results in an unconstrained and penalized optimal control problem which strictly satisfies the constraints. The approach requires no knowledge of the switching structure of the optimal solution and avoids the explicit consideration of singular arcs. A collocation method is used to solve the BVPs derived from the optimality conditions and demonstrates the applicability of the method to constrained optimal control problems

Constructive Methods for Initialization and Handling Mixed State-Input Constraints in Optimal Control

International audienceNew methods are presented to address two issues in indirect optimal control: the calculation of a starting point for the numerical solution and the consideration of mixed state-input constraints. In the first method, an auxiliary optimal control problem is constructed from a given initial trajectory of the system. Its adjoint variables are simply zero. This auxiliary problem is then used within a homotopy approach to eventually reach the original optimal control problem and the desired optimal solution. The second method concerns the incorporation of mixed state- input constraints into the dynamics of the considered optimal control problem. It uses saturation functions which strictly satisfy the constraints. In this way, the original constrained optimal control problem is transformed into an unconstrained one with an additional regularization term. The two approaches are derived within a general framework. For sake of illustration, they are applied to the space shuttle reentry problem, which represents a challenging benchmark due to its high numerical sensitivity and the presence of input and heating constraints. The reentry problem is solved with a collocation method and demonstrates the applicability and accuracy of the proposed constructive methods