This research proposes an integral system combining a hybrid BCI interface and shared control system for navigation and manipulation applications. In particular, the system consists of an electrical wheelchair with an embedded robotic arm that can assist a user to achieve essencial tasks such as picking up a cup of water. The proposed system uses a graphic interface that allows the user to select the possible control tasks through EEG signals based of steady state visual evocked potentials (SSVEP). On the other hand, the wheelchair is controlled by cervical movements related to head movement obtained by inertial sensors that assign navigation commands to the wheelchair, while ultrasonic sensors allow obstacle detection. Experimental results demonstrate the viability of the system and potential use as assistive technology for patients with motor paralysis conditions.

ACKNOWLEDGMENT This work was financial supported by Concytec-The World Bank Project ”Improvement and Expansion of Services of the National System of Science, Technology and Technological Innovation” 8682-PE, through its executing unit Fondecyt under contract No. 054-2018-FONDECYT- BM-IADT-AV.Furthermore, the authors thank the support of the Pontificia Universidad Catolica del Peru and the Center for Autonomous Systems of the Sydney University of Technology for the support provided during the execution of the research project.

The following paper describes the design, implementation and preliminary tests of an Unmanned Surface Vessel (USV) robot, able to collect water quality parameters and bathymeter measurements in lakes and bodies of fresh water at the Peruvian highlands. The USV robot is developed in order to be a measurement tool to monitor water pollution and help to improve the current methods used for this task. The USV integrates a video system which is used to maneuver the robot, a multiparameter probe for measuring water quality parameters (temperature, pH, dissolved oxygen, turbidity, conductivity and colored dissolved organic matter), a bathymeter to obtain depth measurements, and a wireless outdoor base station to create a wireless local area network through which the data is received and transmitted. The preliminary results of the performance of the USV are obtained from a lake located in the Pe...

This paper describes a novel multi-task allocation method for the autonomous navigation to improve the efficiency for executing mission considering an Unmanned Surface Vehicle (USV) developed by the Pontificia Universidad Catolica del Peru (PUCP). The new method is developed based upon the self-organizing map (SOM) algorithm, with the consideration of the priorities of the sample stations that USV need to visit, as well as the lattice distances from the sample stations to the start point. Using this new method, an optimized order of visiting sequence can be calculated according to the battery energy limit of the USV. The new multi-task allocation method has been verified in simulation environments with results proving the effectiveness and capabilities of the system.