Abstract
The use of autonomous vehicles in maritime operations is a technological challenge. In the particular case of autonomous aerial vehicles (UAVs), their application ranges from inspection and surveillance of offshore power plants, and marine life observation, to search and rescue missions. Manually landing UAVs onboard water vessels can be very challenging due to limited space onboard and wave agitation. This paper proposes an autonomous solution for the task of landing commercial multicopter UAVs with onboard cameras on water vessels, based on the detection of a custom landing platform with computer vision techniques. The autonomous landing behavior was tested in real conditions, using a research vessel at sea, where the UAV was able to detect, locate, and safely land on top of the developed landing platform.

Abstract
This paper addresses the design of a hybrid feedback control system enabling a car-like, rectangular vehicle to perform a tight L-shaped turn maneuver, This case constitutes an effort towards the definition of a general purpose methodology for hybrid feedback control synthesis. The design effort encompasses the synthesis of a set of modalities and mechanisms to detect relevant events enabling the overall motion coordination so that a global goal is attempted, Simulations of the implemented controller have shown a strong robustness with respect lo modeling uncertainty and execution errors.

Abstract

Abstract

Abstract
This paper addresses the design of a hybrid feedback control system enabling a car-like, rectangular vehicle to perform a tight L-shaped turn maneuver. This case constitutes an effort towards the definition of a general purpose methodology for hybrid feedback control synthesis. The design effort encompasses the synthesis of a set of modalities and mechanisms to detect relevant events enabling the overall motion coordination so that a global goal is attempted. Simulations of the implemented controller have shown a strong robustness with respect to modeling uncertainty and execution errors.

Abstract
This paper propose a real-time vision architecture for mobile robotics, and describes a current implementation that is characterised by: low computational cost, low latency, low power, high modularity, configuration, adaptability and scalability. A pipeline structure further reduces latency and allows a paralleled hardware implementation. A dedicated hardware vision sensor was developed in order to take advantage of the proposed architecture. A new method using run length encoding (RLE) colour transition allows real-time edge determination at low computational cost. The real-time characteristics and hardware partial implementation, coupled with low energy consumption address typical autonomous systems applications.