The obstacle avoidance maneuver is required for an autonomous vehicle. It is essential to define the system's performance by evaluating the minimum reaction times of the vehicle and analyzing the probability of success of the avoiding operation. This paper presents a collision avoidance algorithm based on the velocity obstacle approach that guarantees collision-free maneuvers. The vehicle is controlled by an optimal feedback control named FLOP, designed to produce the best performance in terms of safety and minimum kinetic collision energy. Dimensionless accident evaluation parameters are proposed to compare different crash scenarios.

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The purpose of the present paper is the identification of optimal trajectories of quadruped robots through genetic algorithms. The method is based on the identification of the optimal time history of forces and torques exchanged between the ground and the body, without any constraints on leg kinematics. The solutions show how it is possible to obtain similar trajectories to those of a horse’s walk but obtaining better performance in terms of energy cost. Finally, a map of the optimal gaits found according to the different speeds is presented, identifying the transition threshold between the walk and the trot as a function of the total energy spent.

The scope of the paper is to develop a methodology for finding optimal gaits of a quadruped robot using genetic algorithm, comparing the results to the ones resulting from natural evolution. The optimization is performed over preimposed contact forces to find the best shapes that guarantees the minimum energy consumption during a single stride cycle. The dynamic formulation of the four-dimensional model is developed without involving any specific kinematic mechanism for the legs, considering the entire gait spectrum a quadruped can exhibit. The optimization model consists of a set of constraints that ensure the feasibility and stability of the gaits. Results are presented for an optimization requiring a constant speed of 1.35 𝑚/𝑠. The optimal gait was found to be consistent to nature, suggesting that energy consumption is one of the key factors contributing to the evolution of gaiting patterns in quadrupeds. Eventually, a comparison between different existing gait patterns is carried out in terms of foot contact time and energy consumption.

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This paper presents the Auto-Sapiens project, an autonomous driving car developed by the Mechatronics and Vehicle Dynamics Lab, at Sapienza University of Rome. Auto-Sapiens is a technological platform to test and improve innovative control algorithms. The car platform is a standard car (Smart ForTwo) equipped with throttle, brake, steering actuators and different sensors for attitude identification and environment reconstruction. The first experiments of the Auto-Sapiens car test a new obstacle avoidance. The vehicle, controlled by an optimal variational feedback control, recently developed by the authors, includes the nonlinearities inherent in the car dynamics for better performances. Results show the effectiveness of the system in terms of safety and robustness of the avoidance maneuvers.

This paper presents the Auto-Sapiens project, an autonomous driving car developed by the Mechatronics and Vehicle Dynamics Lab, at Sapienza University of Rome. Auto-Sapiens is a technological platform to test and improve innovative control algorithms. The car platform is a standard car (Smart ForTwo) equipped with throttle, brake, steering actuators and different sensors for attitude identification and environment reconstruction. The first experiments of the Auto-Sapiens car test a new obstacle avoidance. The vehicle, controlled by an optimal variational feedback control, recently developed by the authors, includes the nonlinearities inherent in the car dynamics for better performances. Results show the effectiveness of the system in terms of safety and robustness of the avoidance maneuvers.

This paper presents the preliminary activities undertaken for the research project SUNMARE (Surface UNmanned multipurpose research MARine vEhicle), which aims at the development of an innovative autonomous platform for marine, oceanographic, lacustrine, and submerged/semi-submerged cultural heritage monitoring/measurements. SUNMARE is a modular ship comprising of a mother unmanned ship and a smaller autonomous vehicle. Through an innovative fully autonomous launch and recovery system (LARS), the Unmanned surface vehicle (USV) can detach and reconnect to the mother ship. The architecture of the LARS and the on-purposely designed control algorithms are here presented together with statistical recovery success analysis concerning the autonomous dynamic connection of the vehicles, so to assess the reliability of the system.