José Luis Gordillo

A Behavior-Based Strategy for Single and Multi-Robot Autonomous Exploration

In this paper, we consider the problem of autonomous exploration of unknown environments with single and multiple robots. This is a challenging task, with several potential applications. We propose a simple yet effective approach that combines a behavior-based navigation with an efficient data structure to store previously visited regions. This allows robots to safely navigate, disperse and efficiently explore the environment. A series of experiments performed using a realistic robotic simulator and a real testbed scenario demonstrate that our technique effectively distributes the robots over the environment and allows them to quickly accomplish their mission in large open spaces, narrow cluttered environments, dead-end corridors, as well as rooms with minimum exits.

Kinematics and Dynamics of a New 16 DOF Humanoid Biped Robot with Active Toe Joint

Humanoid biped robots are typically complex in design, having numerous Degrees-of-Freedom (DOF) due to the ambitious goal of mimicking the human gait. The paper proposes a new architecture for a biped robot with seven DOF per each leg and one DOF corresponding to the toe joint. Furthermore, this work presents close equations for the forward and inverse kinematics by dividing the walking gait into the Sagittal and Frontal planes. This paper explains the mathematical model of the dynamics equations for the legs into the Sagittal and Frontal planes by further applying the principle of Lagrangian dynamics. Finally, a control approach using a PD control law with gravity compensation was recurred in order to control the desired trajectories and finding the required torque by the joints. The paper contains several simulations and numerical examples to prove the analytical results, using SimMechanics of MATLAB toolbox and SolidWorks to verify the analytical results.

Model-Based Development of Virtual Laboratories for Robotics Over the Internet

Extending technical education to students abroad requires the systematic development of virtual laboratories (VLs) that provide interaction with real and specialized equipment. This paper proposes a generic and modular model for VLs for robotics over the Internet. The model is defined by using Unified Modeling Language (UML) to depict its software structure and also Petri nets to describe its dynamic behavior. A development methodology uses the model as a reference framework. This proposed methodology, based on experiment specifications, customizes the framework in UML and formally translates its dynamic description, depicted by statecharts, into the Petri net formalism. Petri nets are used to analyze, control, and validate the VL dynamic design as a stable and event-synchronized telerobotic system. UML and Petri net charts obtained from the methodology supply a complete guideline for the developer to implement VLs for robotics. The model and its methodology are used to develop a remote VL for mobile robotics. This paper attempts to bridge the gap between ad hoc and formal implementation of VLs.

Parallel sort on a linear array of cellular automata

A cellular automata machine (CA machine) is a structure of interconnected elementary automata, evolving in a parallel and synchronous way. In this paper, we analyse the CA Machine as a general computing structure in which specific computations on the input data must be done. We extend the standard definition of cellular automata to include some requirements of memory to store data, also with some rules to detect the end of the computations and to obtain a result. To validate and illustrate the computations on the CA machine, we present the analysis and implementation of parallel sort algorithms. We describe algorithms, in which each automata cell has a key to be ordered. The sort is performed by the exchange of keys between cell neighbours. Rules are included in order that a cell chooses the neighbour with which the exchange (swap) will be performed, without knowing its cell index nor the length of the array. We show that the algorithm complexity of sorting n keys in those machines is linear on n.<<ETX>>

Autonomous Observer: a tool for remote experimentation in robotics

This paper describes a robotics technology--the Autonomous Observer (AO)--developed to facilitate experimentation over the Internet. The AO is a mobile robot equipped with visual sensors. It applies visual tracking and motion planning techniques to track a designated moving object (the target) in an environment cluttered by obstacles and repeatedly measure the targets pose. This pose is sent over the Internet to remote users who can observe 3D real-time graphic renderings of the targets motion in its environment under individually selected viewpoints. The AO was used to set up an experiment in which a can-collecting robot (playing the role of the target) equipped with a range sensor and a simple arm automatically detects coke cans and collects them in a bag.

Synthesis of odor tracking algorithms with genetic programming

At the moment, smell sensors for odor source localization in mobile robotics represent a topic of interest for researchers around the world. In particular, we introduce in this paper the idea of developing biologically inspired sniffing robots in combination with bioinspired techniques such as evolutionary computing. The aim is to approach the problem of creating an artificial nose that can be incorporated into a real working system, while considering the environmental model and odor behavior, the perception system, and algorithm for tracking the odor plume. Current algorithms try to emulate animal behavior in an attempt to replicate their capability to follow odors. Nevertheless, odor perception systems are still in their infancy and far from their biological counterpart. This paper presents a proposal in which a real-working artificial nose is tested as a perception system within a mobile robot. Genetic programming is used as the learning technique platform to develop odor source localization algorithms. Experiments in simulation and with an actual working robot are presented and the results compared with two algorithms. The quality of results demonstrates that genetic programming is able to recreate chemotaxis behavior by considering mathematical models for odor propagation and perception system.

Mobile robotics virtual laboratory over the Internet

In this paper, we describe a mobile robotics virtual laboratory that allows the user to define and perform remote experiments over the Internet using a mobile minirobot. The user interacts with a user interface, which receives a work space top view from a remote laboratory facility. She defines and draws a C-Space on the image, and provides a destination point. Once C-Space and destination are defined, a potential field based planner draws a path. This path is sent to the laboratory facility and a vision-based computer system makes the robot follow that path. Several capabilities to enhance real-time users interaction are provided: grab and drop path modification, virtual obstacles insertion, changeable experiment settings, and a complementary observer system used to get a detailed view of the robot and its workspace.

Directional Aptitude Analysis in Odor Source Localization Techniques for Rescue Robots Applications

Olfaction is an interesting new challenging area for intelligent systems to be developed and applied in rescue robots applications. The use of a sniffing robot following the smell of precise odors is one way to increase the efficiency and the fastness of a multi-robot team in a disaster area. The most important task of a sniffing robot in a rescue application is the odor source localization, which inspired on nature, requires the capacity of directionality. The intention of this document is to prove that the diffusion, advection, and gradient behaviors are actually present in a semi-controlled environment with an odor source simulating a continuous and relatively constant gas leak.

Placing Artificial Visual Landmarks in a Mobile Robot Workspace

Recently, research on mobile robotics has been focused on achieving reliable performance on autonomous systems. We believe that one possible way to do this is by using landmarks to bound uncertainty during the path planning and navigation stages. In this paper, we present an algorithm to compute the position of artificial visual landmarks in a mobile robot workspace.We aim to maximize the region in the workspace from where a landmark can be seen, i.e., to define the position of the landmarks in the workspace. After pointing out that this problem is combinatorial in nature, we propose a simulated annealing type of technique to find the optimal landmark arrangement.

Visual EKF-SLAM from Heterogeneous Landmarks

Many applications require the localization of a moving object, e.g., a robot, using sensory data acquired from embedded devices. Simultaneous localization and mapping from vision performs both the spatial and temporal fusion of these data on a map when a camera moves in an unknown environment. Such a SLAM process executes two interleaved functions: the front-end detects and tracks features from images, while the back-end interprets features as landmark observations and estimates both the landmarks and the robot positions with respect to a selected reference frame. This paper describes a complete visual SLAM solution, combining both point and line landmarks on a single map. The proposed method has an impact on both the back-end and the front-end. The contributions comprehend the use of heterogeneous landmark-based EKF-SLAM (the management of a map composed of both point and line landmarks); from this perspective, the comparison between landmark parametrizations and the evaluation of how the heterogeneity improves the accuracy on the camera localization, the development of a front-end active-search process for linear landmarks integrated into SLAM and the experimentation methodology.