David Álvarez

Learn More
— This paper presents a novel robotic learning technique based on Fast Marching Square (F M 2). This method, which we have called FM Learning, is based on incorporating previous experience to the path planning system of the robot by taking into account paths taught to the robot via kinesthetic teaching, this is, guiding manually the robot through the(More)
Risk-taking behaviour has important consequences for fitness. Here, we show that risk-taking behaviour in sticklebacks consistently varies according to the habitat of origin. We compared the risk-taking behaviour of individual sticklebacks from three pond and three stream populations. Specifically, we measured willingness to forage under predation risk(More)
Sampling-based path planning algorithms are well-known because they are able to find a path in a very short period of time, even in high-dimensional spaces. However, they are non-smooth, random paths far away from the optimum. In this paper we introduce a novel improving technique based on the Fast Marching Method which improves in a deterministic,(More)
The Fast Marching Method is a very popular algorithm to compute times-of-arrival maps (distances map measured in time units). Since their proposal in 1995, it has been applied to many different applications such as robotics, medical computer vision, fluid simulation, etc. Many alternatives have been proposed with two main objectives: to reduce its(More)