Path Planning for Autonomous Mobile Robots: A Review.

Providing mobile robots with autonomous capabilities is advantageous. It allows one to dispense with the intervention of human operators, which may prove beneficial in economic and safety terms. Autonomy requires, in most cases, the use of path planners that enable the robot to deliberate about how to move from its location at one moment to another. Looking for the most appropriate path planning algorithm according to the requirements imposed by users can be challenging, given the overwhelming number of approaches that exist in the literature. Moreover, the past review works analyzed here cover only some of these approaches, missing important ones. For this reason, our paper aims to serve as a starting point for a clear and comprehensive overview of the research to date. It introduces a global classification of path planning algorithms, with a focus on those approaches used along with autonomous ground vehicles, but is also extendable to other robots moving on surfaces, such as autonomous boats. Moreover, the models used to represent the environment, together with the robot mobility and dynamics, are also addressed from the perspective of path planning. Each of the path planning categories presented in the classification is disclosed and analyzed, and a discussion about their applicability is added at the end.

A Gesture Recognition Algorithm for Hand-Assisted Laparoscopic Surgery.

Minimally invasive surgery (MIS) techniques are growing in quantity and complexity to cover a wider range of interventions. More specifically, hand-assisted laparoscopic surgery (HALS) involves the use of one surgeon's hand inside the patient whereas the other one manages a single laparoscopic tool. In this scenario, those surgical procedures performed with an additional tool require the aid of an assistant. Furthermore, in the case of a human-robot assistant pairing a fluid communication is mandatory. This human-machine interaction must combine both explicit orders and implicit information from the surgical gestures. In this context, this paper focuses on the development of a hand gesture recognition system for HALS. The recognition is based on a hidden Markov model (HMM) algorithm with an improved automated training step, which can also learn during the online surgical procedure by means of a reinforcement learning process.