Cristina Urdiales

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.

Non-parametric planar shape representation based on adaptive curvature functions

This paper presents a non-parametric method to extract a very short feature vector from the curvature function of a planar shape. Curvature is adaptively calculated using a new procedure that removes noise from the contour without missing relevant points. Then, its Fourier transform is projected onto a set of vectors, which have been chosen to be as representative as possible, to obtain the similarity between the input object and each vector of the set. These similarity values are the elements of the feature vector. The proposed method is very fast and classification has proven that the representation is good.

2D object recognition based on curvature functions obtained from local histograms of the contour chain code

Abstract In this paper a real time 2D object recognition algorithm is proposed. Contours are represented by their curvature functions, decomposed in the Fourier domain as linear combination of a set of representative objects. Finally, objects are identified by multilevel clustering.

A new multi-criteria optimization strategy for shared control in wheelchair assisted navigation

In todays aging society, many people require mobility assistance, that can be provided by robotized assistive wheelchairs with a certain degree of autonomy when manual control is unfeasible due to disability.Robot wheelchairs, though, are not supposed to be completely in control because lack of human intervention may lead to loss of residual capabilities and frustration. Most of these systems rely on shared control, which typically consists of swapping control from human to robot when needed. However, this means that persons never deal with situations they find difficult. We propose a new shared control approach to allow constant cooperation between humans and robots, so that assistance may be adapted to the user’s skills. Our proposal is based on the reactive navigation paradigm, where robot and human commands become different goals in a Potential Field. Our main novelty is that human and robot attractors are weighted by their respective local efficiencies at each time instant. This produces an emergent behavior that combines both inputs in an efficient, safe and smooth way and is dynamically adapted to the user’s needs. The proposed control scheme has been successfully tested at hospital Fondazione Santa Lucia (FSL) in Rome with several volunteers presenting different disabilities.

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.

Intelligent healthcare managing: an assistive technology approach

This paper is about the key role of Personalization through Ambient Intelligence in the development of Assistive Technologies for the elders. Ambient Intelligence implies three relatively new technologies: Ubiquitous Computation, Ubiquitous Communication, and Intelligent User Interfaces. We also present our own ideas about the integration of intelligent agent technology with other technologies to build specific assistive tools for the people with disabilities and for the new generation of senior citizens.

A purely reactive navigation scheme for dynamic environments using Case-Based Reasoning

This paper presents a new sonar based purely reactive navigation technique for mobile platforms. The method relies on Case-Based Reasoning to adapt itself to any robot and environment through learning, both by observation and self experience. Thus, unlike in other reactive techniques, kinematics or dynamics do not need to be explicitly taken into account. Also, learning from different sources allows combination of their advantages into a safe and smooth path to the goal. The method has been succesfully implemented on a Pioneer robot wielding 8 Polaroid sonar sensors.

Dynamic calibration and zero configuration positioning system for WSN

Indoor localization is of key importance in many areas of application and market sectors. There are many approaches to solve the problem, based on optical, ultrasound or radiofrequency measurements. RF has been increasingly used with the deployment of Wireless Sensor Networks (WSN) based on standards like WiFi, Bluetooth or Zigbee, so that additional hardware is not required for localization. A desirable characteristic in these systems are the zero configuration and dynamic calibration features. Based in these two characteristics, some methods have already been developed for WiFi and Bluetooth standards. In this paper a dynamic calibration localization system for WSN is presented, focused on IEEE 802.15.4 standard. Quite robust experimental results have been obtained from a prototype developed on Tmote Sky devices.

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.