In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM) problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment.

In this paper, an approach is presented that allows a robot to navigate in an urban environment by following natural language route instructions. In this situation, neither maps nor GPS information are available to the robot thus it has to rely solely on the human-given route description and the observations from its sensors. An architecture for solving problems such as navigation on the sidewalk, street direction inference, and environment labeling that arise in this situation is presented. Our initial experiments indicate that the proposed methods enable a robot to safely navigate in urban environments by following abstract route descriptions and reach previously unknown points in a city.

Purpose – This paper aims to present a teleoperation system that allows one to control a group of mobile robots in a collaborative manner. In order to show the capabilities of the collaborative teleoperation system, it seeks to present a task where the operator collaborates with a robot team to explore a remote environment in a coordinated manner. The system implements human-robot interaction by means of natural language interfaces, allowing one to teleoperate multiple mobile robots in an unknown, unstructured environment. With the supervision of the operator, the robot team builds a map of the environment with a vision-based simultaneous localization and mapping (SLAM) technique. The approach is well suited for search and rescue tasks and other applications where the operator may guide the exploration of the robots to certain areas in the map. Design/methodology/approach – In opposition with a master-slave scheme of teleoperation, an exploration mechanism is proposed that allows one to integrate the commands expressed by a human operator in an exploration task, where the actions expressed by the human operator are taken as an advice. In consequence, the robots in the remote environment choose their movements that improve the estimation of the map and best suit the requirements of the operator. Findings – It is shown that the collaborative mechanism presented is suitable to control a robot team that explores an unstructured environment. Experimental results are presented that demonstrate the validity of the approach. Practical implications – The system implements human-robot interaction by means of natural language interfaces. The robots are equipped with stereo heads and are able to find stable visual landmarks in the environment. Based on these visual landmarks, the robot team is able to build a map of the environment using a vision-based SLAM technique. SONAR proximity sensors are used to avoid collisions and find traversable ways. The robot control architecture is based on common object request broker architecture technology and allows one to operate a group of robots with dissimilar features. Originality/value – This work extends the concept of collaborative teleoperation to the exploration of a remote environment using a team of mobile robots.