This article presents a methodology to recycle and upgrade a 4-DOF educational robot manipulator with a gripper. The robot is upgraded by providing it an artificial vision that allows obtaining the position and shape of objects collected by it. A low-cost and open-source hardware solution is also proposed to achieve motion control of the robot through a decentralized control scheme. The robot joints are actuated through five direct current motors coupled to optical encoders. Each encoder signal is fed to a proportional integral derivative controller with anti-windup that employs the motor velocity provided by a state observer. The motion controller works with only two open-architecture Arduino Mega boards, which carry out data acquisition of the optical encoder signals. MATLAB-Simulink is used to implement the controller as well as a friendly graphical interface, which allows the user to interact with the manipulator. The communication between the Arduino boards and MATLAB-Simulink is performed in real-time utilizing the Arduino IO Toolbox. Through the proposed controller, the robot follows a trajectory to collect a desired object, avoiding its collision with other objects. This fact is verified through a set of experiments presented in the paper.

This paper discusses the overall design and implementation of a video sensor for the detection of risky behaviors of car drivers near previously identified and georeferenced black spots. The main goal is to provide the driver with a visual audio alert that informs of the proximity of an area of high incidence of highway accidents only if their driving behavior could result in a risky situation. It proposes a video sensor for detecting and supervising driver behavior, its main objective being manual distractions, so hand driver supervision is performed. A GPS signal is also considered, the GPS information is compared with a database of global positioning Black Spots to determine the relative proximity of a risky area. The outputs of the video sensor and GPS sensor are combined to evaluate a possible risky behavior. The results are promising in terms of risk analysis in order to be validated for use in the context of the automotive industry as future work.