Teodiano Freire Bastos Filho

Human-Machine Interface Based on Electro-Biological Signals for Mobile Vehicles

In this paper, a system to allow the communication between a human being and a robot, through a human-machine interface (HMI), is proposed. Such HMI makes possible to use electro-biological signals, such as electromyogram (EMG), electrooculogram (EOG) and electroencephalogram (EEG) to control devices like an autonomous wheelchair. An electronic board containing an environmental map has also been developed. Thus, the user selects a cell in the map, through some electro-biological signal, which is understood by the system as the place the mobile vehicle should reach. A control system to guide the robot to seek for this goal is also presented, including experimental results

An approach to avoid obstacles in mobile robot navigation: the tangential escape

An approach to guide a mobile robot from an initial position to a goal position avoiding any obstacle in its path, when navigating in a semi-structured environment, is proposed in this paper. Such an approach, hereinafter referred to as tangential escape, consists in changing the current robot orientation through a suitable combination of the values of the angular and linear velocities (the control actions) whenever an obstacle is detected close to it. Then, the robot starts navigating in parallel to the tangent to the obstacle, regarding the point of the obstacle boundary the robot sensing system identifies as the closest one. The stability of the control system designed according this approach is proven, showing that the robot reaches any reachable goal, with or without a prescribed final orientation. Such a control system is programmed onboard a mobile platform whose sensing system is a laser scanner which provides 181 range measurements, for experimental validation. The results obtained are presented and discussed, allowing concluding that the tangential escape approach is able to guide the robot along trajectories that result in a reduction of the traveling time, thus saving batteries and reducing the motor wearing.

Navegación Autónoma Asistida Basada en SLAM para una Silla de Ruedas Robotizada en Entornos Restringidos

In this work, an interface specially designed for a robotic wheelchair’s navigation within confined spaces is presented. The interface performance is based on two modus: autonomous and non-autonomous. The non-autonomous execution of the robotic wheelchair interface is performed by means of a joystick. The joystick is adapted to the wheelchair’s patient capabilities and it governs the motion of the vehicle within the environment. The autonomous modus of the robotic wheelchair is executed when the user has to turn a given angle within the environment. The turning strategy is performed by means of both: a maneuverability algorithm which is compatible with the wheelchair’s kinematics and the SLAM (Simultaneous Localization and Mapping) algorithm. In addition, the autonomous modus is composed by two modules: a path planning module and a control module. The path planning module uses the map information provided by the SLAM algorithm to generate a safe path compatible with the robotic wheelchair. Such path will allow the vehicle to reach the orientation -angle of turning- given by the user. The control module governs the motion of the robotic wheelchair by means of a trajectory controller when following the path generated by the path planning algorithm. The controller references are updated by the SLAM estimation of the wheelchair’s pose within the environment. Experimental results using a real robotic wheelchair are also shown in this work.

Experimental evidences for visual evoked potentials with stimuli beyond the conscious perception threshold

The Steady State Visual Evoked Potentials (SSVEP), present in ElectroEncephaloGram (EEG) signal, are currently used as a convenient approach to a Brain-Computer Interface (BCI). However, the stimulus frequencies are bellow the Flicker Fusion Frequency (FFF). In this work, the possibility of producing SSVEP for stimulus frequency beyond the FFF is investigated. From our experimental SSVEP results, it is shown that there are consistent evidences to support the hypothesis of non-conscious perception. Finally, their practical implications to both engineering and psychological issues are duly discussed.

Ambient Assisted Route Planner based on XML files with accessibility information

This work introduces an Ambient Assisted Route Planner (A2RP) aimed for providing route planning in unknown indoor environments. System was first designed as an assistive mobility aid to be used by intelligent powered wheelchairs, although it can be suitable also for other autonomous mobile robotics systems, non-automated mobility device users or pedestrians. A2RP system is based on a set of XML description files that can be retrieved from the internet. These files contain all the information needed to access public or private buildings: floor maps, accessibility information, available routes and calibration landmarks. XML description files must be created, located and maintained in an internet server specially dedicated for this purpose. This paper presents description files structure and the associated software applications: a visual editor to build and maintain XML accessibility information files and a navigation setup program to be run on board of the intelligent wheelchair processor.

Autonomous assistance navigation for robotic wheelchairs in confined spaces

In this work, a visual interface for the assistance of a robotic wheelchairs navigation is presented. The visual interface is developed for the navigation in confined spaces such as narrows corridors or corridor-ends. The interface performs two navigation modus: non-autonomous and autonomous. The non-autonomous driving of the robotic wheelchair is made by means of a hand-joystick. The joystick directs the motion of the vehicle within the environment. The autonomous driving is performed when the user of the wheelchair has to turn (90, ™90 or 180 degrees) within the environment. The turning strategy is performed by a maneuverability algorithm compatible with the kinematics of the wheelchair and by the SLAM (Simultaneous Localization and Mapping) algorithm. The SLAM algorithm provides the interface with the information concerning the environment disposition and the pose -position and orientation-of the wheelchair within the environment. Experimental and statistical results of the interface are also shown in this work.

A Nonlinear Control Applied to Team Formation Based on Omnidirectional Vision

In this work a mobile robot cooperation strategy based on computational vision is presented. Such strategy can be applied to a mobile robot team formed by simple and cheap robots and a leader robot with more computational power. The leader has an omnidirectional visual system and uses color segmentation to obtain the pose of the follower robots. This visual information is used as visual feedback to a nonlinear stable controller that manages team formation. Simulations and tests were run and current results are encouraging

A NEW MOBILE ROBOT CONTROL ARCHITECTURE VIA CONTROL OUTPUT FUSION

Abstract A new architecture for controlling the navigation of a mobile robot based on the fusion of the output of several controllers is proposed. A decentralised information filter accomplishes the fusion of the outputs of the controllers. The output of each controller is connected to a local filter with a covariance associated to it. The lower this co-variance is, the bigger is the influence of the corresponding controller on the fused output. A fuzzy logic-based approach is proposed to determine such covariances. The control system is implemented in a commercial robot and its performance is shown through a practical navigation experiment.

Analysis of the use of a robot to improve social skills in children with autism spectrum disorder

Introduction Autism Spectrum Disorder is a set of developmental disorders that imply in poor social skills, lack of interest in activities and interaction with people. Treatments rely on teaching social skills and in such therapies robotics may offer aid. This work is a pilot study, which aims to show the development and usage of a ludic mobile robot for stimulating social skills in ASD children. Methods A mobile robot with a special costume and a monitor to display multimedia contents was designed to interact with ASD children. A mediator controls the robot’s movements in a room prepared for interactive sessions. Sessions are recorded to assess the following social skills: eye gazing, touching the robot and imitating the mediator. The interaction is evaluated using the Goal Attainment Scale and Likert scale. Ten children were evaluated (50% with ASD), using as inclusion criteria children with age 7-8, without use of medication, and without tendency to aggression or stereotyped movements. Results It was observed that the ASD group touched the robot about twice more in average than the control group (CG). They also looked away and imitated the mediator in a quite similar way as the CG, and showed extra social skills (verbal and non-verbal communication). These results are considered an advance in terms of improvement of social skills in ASD children. Conclusions Our studies indicate that the robot stimulated social skills in 4/5 of the ASD children, which shows that its concepts are useful to improve socialization and quality of life.

An Ethernet sniffer for On-line acquisition of EEG with the BrainNet36® device applied to a BCI

This paper presents an Ethernet sniffer programmed in ANSI C to export in an on-line way the electroencephalographic (EEG) data acquired with the device BrainNet36®, which is a Brazilian EEG device for clinical and polysomnography purposes. The sniffer proved to be useful for off-line analysis of the EEG and also for on-line applications, as Brain Computer-Interfaces (BCIs). Despite its limitations and packet losses at around 1.7% due to noise, the off-line analysis of the EEG successfully replicated results of the literature regarding the Event-Related (De)Synchronization (ERD/ERS) and Evoked Potentials (EPs) calculated for mental tasks. For on-line applications the sniffer was used to program a single-switch BCI for on-line classification of motor and no motor mental tasks with high success rate. Nowadays, the BrainNet36® device is being used for EEG research at many Brazilian universities, therefore, we hope that this article may encourage on-line applications. Finally, as the sniffer operation is explained here with examples, this text may serve as a reference guide for potential users.