Rafael Sanz

Improving collision avoidance for mobile robots in partially known environments: the beam curvature method

Abstract This paper presents a new approach to obstacle avoidance for mobile robots in cluttered and unknown or partially unknown environments. The method combines a new directional method, called beam method (BM), to improve the performance of a local obstacle avoidance approach called curvature velocity method (CVM). BM calculates the best one-step heading which is used by CVM to obtain the optimal linear and angular velocities. The resulting combined technique is called beam curvature method (BCM). Different experiments in populated and dynamic environments have proved to be very successful. The method is able to guide the robot safely and efficiently during long time periods. We present some of these results compared with other methods.

Deliberative On-Line Local Path Planning for Autonomous Mobile Robots

This paper describes a method for local path planning for mobile robots that combines reactive obstacle avoidance with on-line local path planning. Our approach is different to other model-based navigation approaches since it integrates both global and local planning processes in the same architecture while other methods only combine global path planning with a reactive method to avoid non-modelled obstacles. Our local planning is only triggered when an unexpected obstacle is found and reactive navigation is not able to regain the initial path. A new trajectory is then calculated on-line using only proximity sensor information. This trajectory can be improved during the available time using an anytime algorithm. The proposed method complements the reactive behaviour and allows the robot to navigate safely in a partially known environment during a long time period without human intervention.

Enhancing building security systems with autonomous robots

In the last few years, the amount of money spent on security has grown due to a number of factors. The surveillance system of buildings has particularly become an important issue to human daily life. This paper describes the development of a Multirobot system for building surveillance applications monitored through Internet. Each robot can handle some daily surveillance routine tasks. Sensor information such as real-time images captured by a camera on the robot with pan/tilt/zoom functions can be transmitted back to the central management office via a local area network. Teleoperation of the robots via the Internet or intranet is also possible. The complete system can be installed and reprogrammed in a very short time thanks to a high level task application programming environment named RoboGraph. Using this tool the application can be programmed using Petri nets with commands and events previously defined.

Communication framework for sensor-actuator data in mobile robots

In this paper we present a CAN based communication system to connect sensors and actuators in a mobile robot platform and integrate them in a specific navigation architecture. The goal of this work is to provide a simple, flexible and open system that allows connecting different hardware components in a mobile robot. Sensor and actuator modules can be connected or disconnected to a computer while the system is working in a similar way that USB devices work. The system has been tested in our mobile robot Rato to replace the old sensor system and has proven to integrate a ring of sonar sensors and a set of tactile sensors in our navigation architecture.

PROBABILISTIC MODELS FOR MONITORING AND FAULT DIAGNOSIS: APPLICATION AND EVALUATION IN A MOBILE ROBOT

This paper presents a general approach for building a robust and efficient supervision system for fault detection and recovery. The approach uses a set of monitors that obtain information about the system state and, instead of detecting fault states directly, detects significant differences between perceived and expected states. To deal with uncertainty in the knowledge about the system state and the result of some actions, it uses a POMDP model to decide when it is worthwhile to take recovery actions. We present the general approach and show its application with an indoor mobile robot by reporting and evaluating comparative results for different solutions.

Using hierarchical binary Petri nets to build robust mobile robot applications: RoboGraph

Most of the mobile robot control frameworks are based on a middleware layer with several independent modules that implement primitive actions and report events about their state. These modules are usually connected with different interprocess communication mechanisms. Here, we propose to use hierarchical interpreted binary Petri nets to coordinate the activity of these modules. Tasks are described using an interpreted Petri net editor and saved in a xml file. A dispatcher loads these files and executes the different Petri nets under user requests. A monitor that shows the state of all the running nets is very useful for debugging and tracing purposes. The whole system has been applied to a guide robot (vixiabot) that has been guiding users in a public event (XuventudeGalicia.net) for three days in April 2007 and is now extended to a multirobot surveillance application.

Heuristic anytime approaches to stochastic decision processes

This paper proposes a set of methods for solving stochastic decision problems modeled as partially observable Markov decision processes (POMDPs). This approach (Real Time Heuristic Decision System, RT-HDS) is based on the use of prediction methods combined with several existing heuristic decision algorithms. The prediction process is one of tree creation. The value function for the last step uses some of the classic heuristic decision methods. To illustrate how this approach works, comparative results of different algorithms with a variety of simple and complex benchmark problems are reported. The algorithm has also been tested in a mobile robot supervision architecture.

THE BEAM-CURVATURE METHOD: A NEW APPROACH FOR IMPROVING LOCAL REALTIME OBSTACLE AVOIDANCE

Abstract This paper describes a new local avoidance method for indoor mobile robots. The method uses a directional method named the Beam Method to improve the performance of a local obstacle avoidance approach called Curvature Velocity Method (CVM). The proposed Beam Method employs radial distances provided by the robot sensors to calculate the best one-step headings. The CVM uses this information to calculate the optimal translational and rotational velocities. Our approach incorporates the local information in an intuitive way, similar to human vision, by taking advantage of the natural disposition of the mobile robot sensor systems. Compared with other methods it shows more efficient performances, being able to navigate through openings very efficiently way. Several experiments in populated and dynamic environments with our mobile robot RATO have proved to be very successful.

An Intelligent Supervisory Model for Path Planning and Guidance of Mobile Robots in Non-structured Environments

Abstract In this paper an intelligent and modular decision architecture is presented. The main goal of the proposed model is the integration with an intelligent supervisor of the different subsystems of a mobile robot which performs asynchronous tasks in a coordinate fashion. Unlike other approaches, some supervisory functions are embedded in each subsystem whereas the intelligent supervisor is responsible for controlling the overall performances. The system software combines planning with reactive behaviour at different time scales. In order to provide synchronisation between both behaviours, the supervisor takes appropriate actions based on detected situations.

Increasing wireless reliability for autonomous mobile robots

There is an increasing popularity of mobile robot applications over the Internet. Robots need some kind of wireless communication to receive commands and transmit information to users. This paper describes the problems encountered to keep the mobile robots connected and the solutions adopted. The first problem was related to delays and the very low throughput that occur when the robot roams to a new access point. Most commercial systems currently installed implement proprietary solutions with different behaviors. Here, a simple and device-independent solution for mobile robot applications is proposed. The second problem is the lack of wireless coverage in some areas of buildings. The solutions adopted for these problems are based on coverage maps.