Goal-oriented path planning for ground and aerial vehicles

Nowadays autonomous robots are used in everyday life more than ever. The idea that motivate the develop of new autonomous application is to lessen the fatigue of repetitive works and to make safer the work that are difficult if done by humans alone. Another goal of autonomous robots is to improve precision and repetitiveness in the actuation of actions. Car makers are now showing to consider autonomous driving a ground braking functionality and one of the most important additions to their assets to maintain a sustainable competitive edge on the market in the mid-long term. Same scenario is happening in almost every technological area. To be competitive on the market, companies need to add intelligent feature to their products. For example in drone market all the top of the line product have autonomous features and companies invest a lot of effort to improve these features. Path planning is a crucial part of the creation of autonomous systems. While motion planning is a difficult task in general, its application to autonomous vehicles and drone moving in presence of other actor imposes requirements that make it even more challenging. For example autonomous cars have to deal with other cars, pedestrians, cyclists, etc.. Moreover road going vehicles obey non-holonomic motion laws that must be accounted for during planning. Another example are drones that flying in presence of pedestrian can be a danger if not driven correctly. Path Planning is a huge field of study. In this dissertation we focus our attention on those application where the planner has a well target. We provide an architecture and algorithms that allow the build of a general system that allows autonomous robot to reach a target. Attention is given in the generation of behaviors that are very smooth. Moreover is given top priority to the safety of the system.