Alberto Poncela

A New Efficiency-Weighted Strategy for Continuous Human/Robot Cooperation in Navigation

Autonomous robots are capable of navigating on their own. Shared control approaches, however, allow humans to make some navigation decisions. This is typically executed either by overriding the human or the robot control at some specific situations. In this paper, we propose a method to allow cooperation between humans and robots at each point of any given trajectory so that both have some weight in the emergent behavior of the mobile robot. This is achieved by evaluating their efficiencies at each time instant and combining their commands into a single order. In order to achieve a seamless combination, this procedure is integrated into a bottom-up architecture via a reactive layer. We have tested the proposed method using a real robot and several volunteers, and results have been satisfactory both from a quantitative and qualitative point of view.

Hierarchical planning in a mobile robot for map learning and navigation

This chapter focuses on autonomous navigation for mobile robots. We propose a hybrid layered architecture, which is used to navigate in totally or partially explored environments using sonar sensors. Our architecture relies on a hierarchical representation of the environment, which has both a metric and a topological level, which is based on the metric level. High level planning layers work at the topological level deliberatively, while low level navigation layers operate at the metric level reactively. The main advantage of the proposed scheme is that it can operate in both known and unknown environments rapidly and efficiently.

Efficient integration of metric and topological maps for directed exploration of unknown environments

Recent research in mobile robot navigation is focused on integrating the metric and topological paradigms to unsupervisedly construct representations of indoor environments. While metric methods produce accurate environment representations, these representations present a huge data volume and they are consequently difficult to process in real time. On the other hand, topological maps can be processed in a more efficient way, but they are typically difficult to disambiguate and update. This paper describes an exploration algorithm for totally or partially unexplored environments. The algorithm is based on a representation that integrates the metric and topological paradigms. Exploration planning is performed at two levels: global planning is performed at topological level and local planning is performed at metric level. The main advantage of the proposed algorithm is that exploration can be performed in a fast and efficient way by using the presented representation. The method has been successfully tested for a Pioneer P2AT mobile robot in indoor environments.

Efficiency based reactive shared control for collaborative human/robot navigation

Autonomous robots are capable of navigating on their own. In some cases, though, it is interesting to allow humans to influence navigation. Shared control is typically achieved either by giving control to the human or the robot at some specific situations. In this work, we propose a method to share control between humans and robots at each point of a given trajectory, so that both have weight in the resulting behavior of the mobile. This is achieved by estimating their respective local efficiencies at each time instant and combining their commands into a single order. In order to achieve a seamless combination, this procedure is integrated into a bottom-up architecture via a reactive layer. The system is meant to be used in wheelchair control for people with disabilities. Thus far, we have tested the proposed method using a Pioneer AT robot driven by several volunteers. Results have been satisfactory both from a quantitative and qualitative point of view.

Command-based voice teleoperation of a mobile robot via a human-robot interface

Verbal communication is the most natural way of human–robot interaction. Such an interaction is usually achieved by means of a human-robot interface (HRI). In this paper, a HRI is presented to teleoperate a robotic platform via the user’s voice. Hence, a speech recognition system is necessary. In this work, a user-dependent acoustic model for Spanish speakers has been developed to teleoperate a robot with a set of commands. Experimental results have been successful, both in terms of a high recognition rate and the navigation of the robot under the control of the user’s voice.

Place characterization for navigation via behaviour merging for an autonomous mobile robot

This paper presents a novel approach to characterize and recognize places in unknown environments for behaviour-based navigation purposes. This recognition technique classifies a given robot position in three categories, wall, corridor or door. The technique allows the robot not only to select the behaviour that better fits that situation, but also to fuse them in a seamless way. It is supported by a local grid built from sonar readings. The contour of this grid is extracted, represented by its FFT, and it is reduced to a short feature vector by using principal component analysis. The method has been successfully tested in real environments with a Pioneer robot equipped with 8 frontal sonar sensors, proving its feasibility and effectiveness.

A CBR approach to Behaviour-Based Navigation for an Autonomous Mobile Robot

This paper presents a new CBR navigation scheme based on three behaviours: wall following, corridor following and door crossing. The system switches among CBR behaviours depending on a local grid built around the robot from sonar sensor readings. The main advantage of the proposed system is that it can easily adapt to any robot and environment, learning, both by training and by its own experience. The method has been successfully tested in real environments with a Pioneer robot equipped with 8 frontal sonar sensors.

Collaborative emergent navigation based on biometric weighted shared control

This paper presents a new approach to shared control. It consists of combining orders from a mobile and a human. The weight of these orders is obtained by evaluating their corresponding efficiencies but also of his/her condition, which is estimated by continuously monitoring attached biosensors. We rely on a hierarchical architecture where the reactive layer provides a simple and adaptive combination of these sources. We have evaluated the resulting emergent behaviour for different tasks to measure their efficiencies under different circumstances. The system has been successfully tested in real environments from a quantitative and a qualitative point of view.

A web-based software educational tool for electronic instrumentation teaching

This article presents a new software tool for electronic instrumentation teaching. The software is concerned with the main concepts underlying instrumentation systems. It is based on Java applets and organized as a tutorial. It acts as a visual tool for interactive simulations. The tool covers, in a practical manner, all the stages of a basic electronic instrumentation system, the sensor, the signal conditioning, and the analog to digital conversion. It must be meant as a complement to classical teaching methodologies based on lectures, not as a substitute of such pedagogical strategies. The software helps students in learning principles of measurement systems, to improve the teaching–learning process in the discipline.

A New Sonar-based Landmark for Localization in Indoor Environments

This paper presents a new sonar based landmark to represent significant places in an environment for localization purposes. This landmark is based on extracting the contour free of obstacles around the robot from a local evidence grid. This contour is represented by its curvature, calculated by a noise-resistant function which adapts to the natural scale of the contour at each point. Then, curvature is reduced to a short feature vector by using Principal Component Analysis. The landmark calculation method has been successfully tested in a medium scale real environment using a Pioneer robot with Polaroid sonar sensors.