This paper considers the problem of solving conflicts arising among several aircraft that are assumed to move in a shared airspace. Aircraft can not get closer to each other than a given safety distance in order to avoid possible conflicts between different airplanes. For such system of multiple aircraft, we consider the path planning problem among given waypoints avoiding all possible conflicts. In particular we are interested in optimal paths, i.e., we want to minimize the total flight time. We propose two different formulations of the multiaircraft conflict avoidance problem as a mixed-integer linear program: in the first case only velocity changes are admissible maneuvers, in the second one only heading angle changes are allowed. Due to the linear formulation of the two problems, solutions may be obtained quickly with standard optimization software, allowing our approach to be implemented in real time.

In this paper, we propose a novel policy for steering multiple vehicles between assigned start and goal configurations, ensuring collision avoidance. The policy rests on the assumption that all agents are cooperating by implementing the same traffic rules. However, the policy is completely decentralized, as each agent decides its own motion by applying those rules only on the locally available information, and scalable, in the sense that the amount of information processed by each agent and the computational complexity of the algorithms do not increase with the number of agents in the scenario. The proposed policy applies to systems in which new vehicles may enter the scene and start interacting with existing ones at any time, while others may leave. Under mild conditions on the initial configurations, the policy is shown to be safe, i.e., it guarantees collision avoidance throughout the system evolution. In the paper, conditions are discussed on the desired configurations of agents, under which the ultimate convergence of all vehicles to their goals can also be guaranteed. To show that such conditions are actually necessary and sufficient, which turns out to be a challenging liveness-verification problem for a complex hybrid automaton, we employ a probabilistic verification method. The paper finally presents and discusses simulations for systems of several tens of vehicles, and reports on some experimental implementation showing the practicality of the approach.

This paper considers the study of cooperative manipulation of a cable-suspended load with two generic aerial robots and without explicit communication. The role of the internal force for the asymptotic stability of the beam-position/beam-attitude equilibria is analyzed in depth. Using a nonlinear Lyapunov-based approach, we prove that if a non-zero internal force is chosen then asymptotic stabilization of any desired beam-pose configuration can be achieved with a decentralized and communication-less master-slave admittance controller. If, conversely, a zero internal force is chosen, as done in the majority of the state-of-the-art algorithms, the attitude of the beam is not controllable without communication. Non-zero internal force can be interpreted then as a fundamental factor that enables the use of cables as implicit communication means between the two vehicles in replacement of the explicit ones. Furthermore, the formal proof of the system output-strictly passivity with respect to an energy-like storage function and a certain input-output pair is given. This proves the stability and the robustness of the method even during motion. The theoretical findings are validated through numerical simulations.

The rise of collaborative robotics has offered new opportunities for integrating automation into the factories, allowing robots and humans to work side-by-side. However, this close physical coexistence inevitably brings new constraints for ensuring safe human-robot cooperation. The current paramount challenge is integrating human safety constraints without compromising the robotic performance goals, which require minimization of the task execution time alongside ensuring its accomplishment. This letter proposes a novel robot trajectory planning algorithm to produce minimum-time yet safe motion plans along specified paths in shared workspaces with humans. To this end, a safety module was used to evaluate the safety of a time-optimal trajectory iteratively. A safe replanning module was developed to optimally adapt the generated trajectory online whenever the optimal plan violates dynamically provided safety limits. In order to preserve performance, a recovery trajectory planning algorithm was included such that the robot is allowed to restore higher speed motions as soon as the safety concern has been resolved. The proposed solution's effectiveness was evaluated both in simulations and real experiments with two robotic manipulators.