Guillermo Enriquez

Wireless Sensor Network and RFID Fusion Approach for Mobile Robot Navigation

There are numerous applications for mobile robots that require relatively high levels of speed and precision. For many systems, these two properties are a tradeoff, as oftentimes increasing the movement speed can mean failing to detect some sensors. This research attempts to create a useful and practical system by combining a wireless sensor network with a passive radio frequency identification system. The sensor network provides fast general navigation in open areas and the radio frequency identification system provides precision navigation near static obstacles. By fusing the data from both systems, we are able to provide fast and accurate navigation for a mobile robot. Additionally, with WSN nodes and passive RFID tag mats, the system infrastructure can be easily installed in existing environments.

Wireless sensor network and RFID sensor fusion for mobile robots navigation

Many indoor, mobile robot applications require relatively high levels of speed and precision during navigation. Often times, these properties are a trade-off with some sensors losing reliability when the robot moves at higher speeds. In this paper, we present a useful and practical system that combines a wireless sensor network with a passive radio frequency identification system (RFID). The sensor network provides the robot with fast, general navigation in open areas. Near static obstacles, it is fused with data from a radio frequency identification system, allowing the robot to perform more precise navigation and avoid static obstacles without the aid of sensors often used in obstacle avoidance, such as sonar or cameras. Experiments were conducted in a real environment to show the utility of the system.

Wireless sensor network-based navigation for human-aware guidance robot

While most mobile robots possess the ability to navigate to and from given locations, for a robot to truly perform guidance, human awareness is also needed. Our guidance robot system possesses both, using a wireless sensor network for navigation and a vision-based tracking system for human awareness. We use the network to create a virtual directional field for the robot. As the network is ad-hoc and scalable, it is ideal for quick installation in existing environments. The vision system is used to estimate the relative direction and distance from the robot to the following human. Using these values, the system ensures that the human does not wander away from the robot during guidance. We setup a simulated hallway environment in order to perform an experiment to test the efficacy of our system in a real world application. The robot was able to successfully navigate to the goal and chase the human to reestablish guidance if the human wandered. The two requirements for performing true guidance.

Indonesian puppet theater robot with gamelan music emotion recognition

In this paper, we propose to protect wayang puppet theater, an intangible cultural heritage from Indonesia by turning a robot into a puppeteer successor. We developed a seven degrees-of-freedom manipulator to actuate sticks attached to the wayang puppet body and hands. We also developed a gamelan music emotion recognition so that the robot could control its movement based on the musical pattern. The robot could imitate some of the puppeteers manipulations and correctly recognized by a human for around 80% in overall. The experiments also revealed that the algorithm had overall over than 90% recognition rate for identifying the delighted song, afraid song and noise.

Contextual Awareness in a WSN/RFID Fusion Navigation System

We present insight into how contextual awareness can be derived from, and improve, a fusion algorithm combing a WSN and a passive RFID for autonomous mobile robot navigation. Contextual awareness of not where the robot is, but rather the context in which it exists in relation to the environment and human user serves to improve accuracy in navigation, alters the speed of the robot, and modifies its behavior. The WSN system, using a virtual potential field, provides fast general navigation in open areas and the RFID provides precision navigation near static obstacles and in narrow areas. We verified the effectiveness of our approaches through navigational and guidance experiments.

Embodied communication between human and robot in route guidance

Walking with someone or guiding them to a destination is a simple task that humans do everyday. However, while almost any mobile robot can navigate to a given point while a human walks behind it, these robots do not take into consideration whether the human is following along properly. Our research involves the use of a wireless sensor network for navigation of a guidance robot and a vision-based tracking system for human awareness. The network creates a virtual directional field that provides a directional imperative to the robot, and the vision system allows it to detect if a following human has strayed. We also present a demonstration of our system in a real world application.

Control moment gyroscope for swing motion control

The analysis of movements has been applied to various fields. However, they are typically only in the form of visual or analytical data from a motion analyzer. Users are unable to feel these types of analysis directly on their bodies. In some fields, such as sports and rehabilitation, it is more efficient to feel a motion than to see the image or numerical data in order to acquire skills. Therefore we propose a device to teach users a desired motion directly using force produced by a Control Moment Gyroscope (CMG). In particular, we focus on a swing motion in golf, baseball, or tennis. This paper introduces the developed CMG prototype and its validation in the control of pendulum movement.

A novel approach to low cost, wide range motion capture system: Validation and application to human behavior analysis

From new hardware arise possibilities to develop novel methods of monitoring human behavior. In this paper we present a low cost system using two RGB-D cameras in a 3m × 8m space. Using developed software, we are able to easily collect, combine, visualize, modify, and analyze data. To validate the system, we measured human behavior in a walking experiment (N = 11). The data obtained from the system showed an accurate measurement and validated our approach for Human Interaction analysis.

Active Contour Model-based control of multi-agent robots

Applications for multi-agent robot systems have been extensively studied because of their flexibility under a wide variety of situations and there are various proposals for control methods. Our research focuses on the control of robot positions for a generalized task: the transportation of some object of unknown shape to some goal destination. We propose a method that places each robot at a position along the contour of the object based on the Active Counter Model, a method often utilized in image processing. With our ACM-inspired algorithm, robots can surround the target object without knowing its shape in advance. If object transportation by a multi-agent system which was less expensive and utilized exchangeable robots were realized it would have properties that would lend itself to applications in real world environments.