Humberto Martínez-Barberá

Modeling Distributed Transportation Systems Composed of Flexible Automated Guided Vehicles in Flexible Manufacturing Systems

This paper proposes a methodology for modeling and controlling a flexible material handling system (MHS), composed of multiple automated guided vehicles (AGVs), suitable for Flexible Manufacturing Systems (FMSs). The AGVs incorporate artificial intelligent techniques to: i) facilitate the configuration and adaptation when there are layout modifications and ii) simplify the interaction between them using simple coordination models. In order to achieve higher flexibility, the MHS makes use of a decentralized navigation control, which increases autonomy and scalability, and a distributed Petri net for solving task allocation and traffic control problems. In order to facilitate the integration with the manufacturing processes, tasks dispatched by manufacturing cells are allocated by the MHS itself, taking into account pending transportation tasks and the systems performance. The whole system has been tested in a real factory and is currently in operational use.

Fuzzy self-localization using natural features in the four-legged league

In the RoboCup four-legged league, robots mainly rely on artificial coloured landmarks for localisation. As it was done in other leagues, artificial landmarks will soon be removed as part of the RoboCup push toward playing in more natural environments. Unfortunately, the robots in this league have very unreliable odometry due to poor modeling of legged locomotion and to undetected collisions. This makes the use of robust sensor-based localization a necessity. We present an extension of our previous technique for fuzzy self-localization based on artificial landmarks, by including observations of features that occur naturally in the soccer field. In this paper, we focus on the use of corners between the field lines. We show experimental results obtained using these features together with the two nets. Eventually, our approach should allow us to migrate from landmarks-only to line-only localisation.

Fuzzy uncertainty modeling for grid based localization of mobile robots

This paper presents a localization method using fuzzy logic to represent the different facets of uncertainty present in sensor data. Our method follows the typical predict-update cycle of recursive state estimators to estimate the robots location. The method is implemented on a fuzzy position grid, and several simplifications are introduced to reduce computational complexity. The main advantages of this fuzzy logic method compared to most current ones are: (i) only an approximate sensor model is required, (ii) several facets of location uncertainty can be represented, and (iii) ambiguities in the sensor information are directly represented, thus avoiding having to solve the data association problem separately. Our method has been validated experimentally on two different platforms, a legged robot equipped with vision and a wheeled robot equipped with range sensors. The experiments show that our method can solve both the tracking and the global localization problem. They also show that this method can successfully cope with ambiguous observations, when several features may be associated to the same observation, and with robot kidnapping situations. Additional experiments are presented that compare our approach with a state-of-the-art probabilistic method.

Robust feedback control of ZMP-based gait for the humanoid robot Nao

Numerous approaches have been proposed to generate well-balanced gaits in biped robots that show excellent performance in simulated environments. However, in general, the dynamic balance of the robots decreases dramatically when these methods are tested in physical platforms. Since humanoid robots are intended to collaborate with humans and operate in everyday environments, it is of paramount importance to test such approaches both in physical platforms and under severe conditions. In this work, the special characteristics of the Nao humanoid platform are analyzed and a control system that allows robust walking and disturbance rejection is proposed. This approach combines the zero moment point (ZMP) stability criterion with angular momentum suppression and step timing control. The proposed method is especially suitable for platforms with limited computational resources and sensory and sensory-motor capabilities.

Development of a flexible AGV for flexible manufacturing systems

Purpose – The paper aims to describe the design and development of an automated guided vehicle (AGV) that incorporates artificial intelligence techniques to increase its autonomy and flexibility. The aim is developing a flexible AGV that operates as a flexible material handling system (MHS) in dynamic industrial environments.Design/methodology/approach – Introduces the entire on‐board control system including hardware and software designs. The sensory system consists of a laser navigation system for localisation and a security laser scanner for sensing the environment. The software architecture is instantiated in a CPU that is connected to low level controllers through a CAN bus. Simplicity, flexibility, robustness and safety were concerned in the design process.Findings – The developed prototype is able to operate in partially structured and dynamic environments, is easily configured using an approximated description of the workplace and is able to adapt when slight floor layout modifications. This devel...Purpose – The paper aims to describe the design and development of an automated guided vehicle (AGV) that incorporates artificial intelligence techniques to increase its autonomy and flexibility. The aim is developing a flexible AGV that operates as a flexible material handling system (MHS) in dynamic industrial environments. Design/methodology/approach – Introduces the entire on-board control system including hardware and software designs. The sensory system consists of a laser navigation system for localisation and a security laser scanner for sensing the environment. The software architecture is instantiated in a CPU that is connected to low level controllers through a CAN bus. Simplicity, flexibility, robustness and safety were concerned in the design process. Findings – The developed prototype is able to operate in partially structured and dynamic environments, is easily configured using an approximated description of the workplace and is able to adapt when slight floor layout modifications. This development shows that current technology permits introducing intelligent vehicles in complex manufacturing systems. Practical implications – The prototype is successfully tested in a real factory, operating as a flexible MHS, transporting pallets between production and storage lines. Originality/value – A novel flexible AGV is designed and developed to operate as a flexible MHS in dynamic industrial environments. The system satisfies the safety and robustness requirements of industrial applications. The flexible MHS results especially suitable for manufacturing systems that suffers from cyclic and seasonal variations and for flexible manufacturing systems where the possibility of choosing alternative routes is a must.

Programming multirobot applications using the ThinkingCap-II Java framework

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Decentralized Traffic Control for Non-Holonomic Flexible Automated Guided Vehicles in Industrial Environments

see front matter 2009 Elsevier Ltd. A doi:10.1016/j.aei.2009.08.011 * Corresponding author. E-mail addresses: humberto@um.es (H. Martíne dherrero@ing.uc3m.es (D. Herrero-Pérez). This paper presents a Java framework, ThinkingCap-II, for developing mobile multirobot applications, which has been successfully used in indoor, automotive and industrial robotics applications. It consists of a reference architecture that serves as a guide to make the functional decomposition of a robotics system, a software architecture that allows a uniform and reusable way of organising software components for robotics applications, and a communication infrastructure that allows software modules to communicate in a common way. A key aspect of this software architecture is that it allows code reusability by high level abstraction and a uniform way of accessing the characteristics of the sensors. In order to show the suitability of the framework, for both diverse complex platforms and multirobot applications, two case studies are discussed. One is an autonomous car-like vehicle which is guided by a manned vehicle, and the other an autonomous industrial vehicle which is member of a multirobot transportation system. 2009 Elsevier Ltd. All rights reserved.

An Accurate and Robust Flexible Guidance System for Indoor Industrial Environments

This paper deals with the problem of coordinating flexible automated guided vehicles (AGVs) in real manufacturing systems. The problem consists of ensuring safe and successful task execution while several AGVs operate as a distributed transportation system in real industrial environments. The proposed solution combines different decentralized techniques to increase the flexibility and scalability of the multirobot system. The coordination is addressed by dividing the problem into path planning, obstacle avoidance and traffic control problems. The path planning method takes into account the location of mates for replanning the routes. The obstacle avoidance technique considers the kinematic constraints of the platform for reactive motion control. The traffic control approach makes use of a decentralized control policy that takes into account the capabilities of vehicles. By combining all these techniques and configuring the system properly, we present the successful development of a distributed transportation system composed of a team of flexible AGVs. The proposed solution has been validated using both a set of custom-modified AGVs operating in a real factory and a simulation of several AGVs operating in a virtual scenario.

Lateral Disturbance Rejection for the Nao Robot

This work presents the development of a flexible industrial guidance system used to guide Automated Guided Vehicles (AGVs) in indoor industrial environments. Typically, wireless guidance systems are composed of path-tracking and localization methods linked to follow a certain route. This paper focuses on the localization approach that permits industrial vehicles to operate indoors with the grade of accuracy, repeatability and reliability required by industrial applications. A key point is that, apart from accuracy, the position estimates should be performed at a high sample rate in order to permit the path tracker to follow the route properly. Robustness of absolute positioning is also crucial in industrial applications. An Extended Kalman Filter (EKF) is adopted to fuse the information provided by a laser navigation system and odometry. The effectiveness of the development is tested using a custom modified commercial industrial vehicle operating in an industrial setting.

Petri Nets based coordination of flexible autonomous guided vehicles in flexible manufacturing systems

Maintaining balance in the presence of disturbances is crucial for bipedal robots. In this paper, we focus on the lateral motion component. In order to attain disturbance rejection and to quickly recover balance, we combine three different control approaches. As a principal building block, we generate center of mass trajectories with a linear model predictive controller that takes scheduled footsteps into account. Strong disturbances generate unexpected angular momenta that can compromise stability. A second control layer extends the underlying preview controller with two recovery strategies that modify the planned CoM trajectories to dampen the rotational velocity of the robot and adapt the timing of the steps according to the expected orbital energy of CoM trajectories at support exchange. Experiments with a real Nao robot show that the system is able to recover from lateral disturbances as long as the robot does not tip over the current support leg.