Titlebook: ROBOT2022: Fifth Iberian Robotics Conference; Advances in Robotics Danilo Tardioli,Vicente Matellán,Lino Marques Conference proceedings 202

颂扬本人

Robot Navigation Anticipative Strategies in Deep Reinforcement Motion Planningrians. Second, we have used these anticipative strategies in real-life experiments using the hybrid motion planning method and the ROS Navigation Stack with Dynamic Windows Approach (NS-DWA). The results in simulations and real-life experiments show very good results in open environments and also in mixed scenarios with narrow spaces.

指耕作

Aerial Robot with Electronic Nose for Air Quality Monitoringin case wireless communication is not possible. Finally, a flight test has been performed to verify the correct operation of the system. A stable signal is achieved regardless of the flight of the drone. Besides, it is also possible to detect a NO2 source.

碌碌之人

A Novel Odor Source Localization Method via a Deep Neural Network-Based Odor Compassork (CNN) module and a long short-term memory (LSTM) module. An OSL strategy is further designed based on the proposed odor compass. Experimental results validate the feasibility of the proposed method.

西瓜

单调女

Deep Learning for Victims Detection from Virtual and Real Search and Rescue Environmentsdrid, generating models from images obtained with the ARTU-R robot (A1 Rescue Task UPM Robot) and have been validated with real search and rescue exercises at the University of Malaga. The main results show that the models obtained from virtual environments apply to real ones.

细菌等

战役

An Inductive Logic Programming Approach for Entangled Tube Modeling in Bin Picking with a high performance, using a relatively small dataset and low amount of time for training. Therefore, this work serves as a proof-of-concept that ILP is a valuable method to acquire knowledge and validate heuristics for pose and shape estimation in complex bin picking scenarios.

instructive

Potential Field Based Swarm Exploration of Processes Governed by Partial Differential Equationsiding collisions. The developed strategy is evaluated in simulations as well as in Hardware-in-the-Loop experiments. It is shown to outperform a systematic sampling strategy for swarms of the same size.

Coterminous

Deep Learning for Victims Detection from Virtual and Real Search and Rescue Environmentsguarding the rescuer’s integrity. The rising in the neural networks field and their application in image detection algorithms have made it possible to facilitate the early detection of victims in these first phases of exploration. This article analyses the effectiveness of applying neural network mo

Bother

Full-stack S-DOVS: Autonomous Navigation in Complete Real-World Dynamic Scenariose a low success rate, do not consider robot kinodynamic constraints or are not able to navigate through big scenarios where the known map information is needed. In this work, a previously existing planner, the Strategy-based Dynamic Object Velocity Space, S-DOVS, is modified and adapted to be includ