Relative Motion Equations in the local-vertical local-Horizon Frame for Rendezvous in lunar Orbits

In this paper, a set of equations for relative motion description in lunar orbits is presented. The local-vertical local-horizon frame is selected to describe the relative dynamics of a chaser approaching a target in lunar orbit, allowing the development of relative guidance and navigation systems for rendezvous and docking. The model considers the Earth and Moon gravitational influence on the two spacecraft, which are assumed to have negligible masses. The proposed equations are intended for the study of rendezvous missions with a future cis-lunar space station, whose development is currently investigated by several space agencies as the next step for space exploration

Distributed Cooperative Deployment of Heterogeneous Autonomous Agents: A Pareto Suboptimal Approach

The paper presents a distributed cooperative control law for autonomous deployment of a team of heterogeneous agents. Deployment problems deal with the coordination of groups of agents in order to cover one or more assigned areas of the operational space. In particular, we consider a team composed by agents with different dynamics, sensing capabilities, and resources available for the deployment. Sensing heterogeneity is addressed by means of the descriptor function framework, an abstraction that provides a set of mathematical tools for describing both agent sensing capabilities and the desired deployment. A distributed cooperative control law is then formally derived nding a suboptimal solution of a cooperative dierential game, where the agents are interested in achieving the requested deployment, while optimizing the resources usage according to their dynamics. The control law eectiveness is proven by theoretical arguments, and supported by numerical simulations

Swarm Obstacle and Collision Avoidance using Descriptor Functions

The descriptor function framework is used as tool for the control management of a swarm of dynamic agents. In this framework, a provision is made for obstacle and collision avoidance, thus improving the potential of the methodology from previous results. Obstacle and collision avoidance terms are added to the overall mission performance index, and the resulting control law moves the agents along obstacle and collision free trajectories. The analytical derivation is validated via numerical simulations