519 research outputs found
Behavior Trees in Robotics and AI: An Introduction
A Behavior Tree (BT) is a way to structure the switching between different
tasks in an autonomous agent, such as a robot or a virtual entity in a computer
game. BTs are a very efficient way of creating complex systems that are both
modular and reactive. These properties are crucial in many applications, which
has led to the spread of BT from computer game programming to many branches of
AI and Robotics. In this book, we will first give an introduction to BTs, then
we describe how BTs relate to, and in many cases generalize, earlier switching
structures. These ideas are then used as a foundation for a set of efficient
and easy to use design principles. Properties such as safety, robustness, and
efficiency are important for an autonomous system, and we describe a set of
tools for formally analyzing these using a state space description of BTs. With
the new analysis tools, we can formalize the descriptions of how BTs generalize
earlier approaches. We also show the use of BTs in automated planning and
machine learning. Finally, we describe an extended set of tools to capture the
behavior of Stochastic BTs, where the outcomes of actions are described by
probabilities. These tools enable the computation of both success probabilities
and time to completion
Wavefront Propagation and Fuzzy Based Autonomous Navigation
Path planning and obstacle avoidance are the two major issues in any
navigation system. Wavefront propagation algorithm, as a good path planner, can
be used to determine an optimal path. Obstacle avoidance can be achieved using
possibility theory. Combining these two functions enable a robot to
autonomously navigate to its destination. This paper presents the approach and
results in implementing an autonomous navigation system for an indoor mobile
robot. The system developed is based on a laser sensor used to retrieve data to
update a two dimensional world model of therobot environment. Waypoints in the
path are incorporated into the obstacle avoidance. Features such as ageing of
objects and smooth motion planning are implemented to enhance efficiency and
also to cater for dynamic environments
Robot Behavior Architecture Based on Smart Resource Service Execution
[EN] Robot behavior definition aims to classify and specify the robot tasks execution. Behavior architecture design is crucial for proper robot operation performance. According to this, this work aims to establish a robot behavior architecture based on distributed intelligent services. Therefore, behavior definition is set in a high-level delegating the task execution to distributed services provided by network abstractions characterized as Smart Resources. In order to provide a mechanism to measure the performance of this architecture, an evaluation mechanisms based on a service performance composition is introduced. In order to test this proposal it is designed a real use case implementing the proposed robot behavior architecture on a real navigation task.Work supported by the Spanish Science and Innovation Ministry MICINN: CICYT 866 project M2C2: Codiseño de sistemas de control con criticidad mixta basado en 867 misiones TIN2014-56158-C4-4-P and PAID (Polytechnic University of Valencia): 868 UPV-PAID-FPI-2013.Munera-Sánchez, E.; Poza-Lujan, J.; Posadas-Yagüe, J.; Simó Ten, JE.; Blanes Noguera, F. (2017). Robot Behavior Architecture Based on Smart Resource Service Execution. International Journal of Soft Computing And Artificial Intelligence (Online). 5(1):55-60. http://hdl.handle.net/10251/152272S55605
A Hierarchical Hybrid Architecture for Mission-Oriented Robot Control
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-03413-3_26In this work is presented a general architecture for a multi
physical agent network system based on the coordination and the behaviour
management. The system is organised in a hierarchical structure
where are distinguished the individual agent actions and the collective
ones linked to the whole agent network. Individual actions are also organised
in a hybrid layered system that take advantages from reactive and
deliberative control. Sensing system is involved as well in the behaviour
architecture improving the information acquisition performance.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under the CICYT project Mission Based Control (COBAMI): DPI2011-28507-C02-02, under coordinated project High Integrity Partitioned Embedded Systems (Hi-PartES): TIN2011-28567-C03-03, and under the collaborative research project supported by the European Union MultiPARTES Project: FP7-ICT 287702. 2011-14.Muñoz Alcobendas, M.; Munera Sánchez, E.; Blanes Noguera, F.; SimĂł Ten, JE. (2013). A Hierarchical Hybrid Architecture for Mission-Oriented Robot Control. En ROBOT2013: First Iberian Robotics Conference: Advances in Robotics, Vol. 1. Springer. 363-380. https://doi.org/10.1007/978-3-319-03413-3_26S363380Aragues, R.: Consistent data association in multi-robot systems with limited communications. Robotics: Science and Systems, 97–104 (2010)Aragues, R., Cortes, J., Sagues, C.: Distributed consensus on robot networks for dynamically merging feature-based maps. IEEE Transactions on Robotics (2012)Arkin, R.C.: Motor schema based mobile robot navigation. The International Journal of Robotics Research 8(4), 92–112 (1989)Asama, H., Habib, M.K., Endo, I., Ozaki, K., Matsumoto, A., Ishida, Y.: Functional distribution among multiple mobile robots in an autonomous and decentralized robot system. In: Proceedings of the 1991 IEEE International Conference on Robotics and Automation. IEEE (1991)Benet, G., Blanes, F., MartĂnez, M., SimĂł, J.: A multisensor robot distributed architecture. In: IFAC Conference INCOM 1998 (1998)Brooks, R.: A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation 2(1), 14–23 (1986)Canas, J.M., Matellán, V.: Dynamic schema hierarchies for an autonomous robot. In: Garijo, F.J., Riquelme, J.-C., Toro, M. (eds.) IBERAMIA 2002. LNCS (LNAI), vol. 2527, pp. 903–912. Springer, Heidelberg (2002)Choset, H., Nagatani, K.: Topological simultaneous localization and mapping (SLAM): toward exact localization without explicit localization. IEEE Transactions on Robotics and Automation 17(2), 125–137 (2001)Fox, D., Burgard, W., Dellaert, F., Thrun, S.: Monte carlo localization: Efficient position estimation for mobile robots. American Association for Artificial Intelligence, 343–349 (1999)Hu, J., Xie, L., Xu, J.: Vision-based multi-agent cooperative target search. In: Control Automation Robotics & Vision (ICARCV), pp. 895–900 (2012)Huq, R., Mann, G.K.I., Gosine, R.G.: Behavior-modulation technique in mobile robotics using fuzzy discrete event system. IEEE Transactions on Robotics 22(5), 903–916 (2006)Jayasiri, A., Mann, G., Gosine, R.G.: Mobile robot behavior coordination using supervisory control of fuzzy discrete event systems. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009, pp. 690–695 (2009)Jayasiri, A., Mann, G.K.I., Gosine, R.G.: Behavior coordination of mobile robotics using supervisory control of fuzzy discrete event systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 41(5), 1224–1238 (2011)Koenig, N., Howard, A.: Gazebo-3d multiple robot simulator with dynamics. Technical report (2006)Lin, F., Ying, H.: Modeling and control of fuzzy discrete event systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 32(4), 408–415 (2002)Madden, J.D.: Multi-robot system based on model of wolf hunting behavior to emulate wolf and elk interactions. In: 2010 IEEE International Conference on Robotics and Biomimetics, ROBIO, pp. 1043–1050 (2010)Mataric, M.J.: Interaction and intelligent behavior. Technical report, DTIC Document (1994)Olivera, V.M., Molina, J.M., Sommaruga, L., et al.: Fuzzy cooperation of autonomous robots. In: Fourth International System on Intelligent Robotics Systems, Lisboa, Portugal (1996)McGann, C., Py, F., Rajan, K., Thomas, H., Henthorn, R., McEwen, R.: A deliberative architecture for auv control. In: IEEE International Conference on Robotics and Automation, ICRA 2008, pp. 1049–1054. IEEE (2008)Munera, E., Muñoz, M., SimĂł, J., Blanes, F.: Humanoid Robot Self-Location In SPL League. In: ComitĂ© Español de Automática (CEA), XXXIII Jornadas de Automatica, 797–804 (2012)Proetzsch, M., Luksch, T., Berns, K.: Development of complex robotic systems using the behavior-based control architecture iB2C. Robotics and Autonomous Systems 58(1), 46–67 (2010)Qiu, D.: Supervisory control of fuzzy discrete event systems: a formal approach. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 35(1), 72–88 (2005)Aladebaran Robotics. NAO Software Documentation 1.12. Technical report (2012)St-Pierre, M., Gingras, D.: Comparison between the unscented Kalman filter and the extended Kalman filter for the position estimation module of an integrated navigation information system. In: 2004 IEEE Intelligent Vehicles Symposium, pp. 831–835 (2004)Stoytchev, A., Arkin, R.C.: Combining deliberation, reactivity, and motivation in the context of a behavior-based robot architecture. In: Proceedings of the 2001 IEEE International Symposium on Computational Intelligence in Robotics and Automation, pp. 290–295 (2001)Nicolau, V., Muñoz, M., SimĂł, J.: KertrolBot Platform. SiDiReLi: Distributed System with Limited Resources. Technical report, Institute of Control Systems and Industrial Computing - Polytechnic University of Valencia, Valencia, Spain (2011
A New Classification Technique in Mobile Robot Navigation
This paper presents a novel pattern recognition algorithm that use weightless neural network (WNNs) technique.This technique plays a role of situation classifier to judge the situation around the mobile robot environment and makes control decision in mobile robot navigation. The WNNs technique is choosen due to significant advantages over conventional neural network, such as they can be easily implemented in hardware using standard RAM, faster in training phase and work with small resources. Using a simple classification algorithm, the similar data will be grouped with each other and it will be possible to attach similar data classes to specific local areas in the mobile robot environment. This strategy is demonstrated in simple mobile robot powered by low cost microcontrollers with 512 bytes of RAM and low cost sensors. Experimental result shows, when number of neuron increases the average environmental recognition ratehas risen from 87.6% to 98.5%.The WNNs technique allows the mobile robot to recognize many and different environmental patterns and avoid obstacles in real time. Moreover, by using proposed WNNstechnique mobile robot has successfully reached the goal in dynamic environment compare to fuzzy logic technique and logic function, capable of dealing with uncertainty in sensor reading, achieving good performance in performing control actions with 0.56% error rate in mobile robot speed
Dynamic Behavior Sequencing in a Hybrid Robot Architecture
Hybrid robot control architectures separate plans, coordination, and actions into separate processing layers to provide deliberative and reactive functionality. This approach promotes more complex systems that perform well in goal-oriented and dynamic environments. In various architectures, the connections and contents of the functional layers are tightly coupled so system updates and changes require major changes throughout the system. This work proposes an abstract behavior representation, a dynamic behavior hierarchy generation algorithm, and an architecture design to reduce this major change incorporation process. The behavior representation provides an abstract interface for loose coupling of behavior planning and execution components. The hierarchy generation algorithm utilizes the interface allowing dynamic sequencing of behaviors based on behavior descriptions and system objectives without knowledge of the low-level implementation or the high-level goals the behaviors achieve. This is accomplished within the proposed architecture design, which is based on the Three Layer Architecture (TLA) paradigm. The design provides functional decomposition of system components with respect to levels of abstraction and temporal complexity. The layers and components within this architecture are independent of surrounding components and are coupled only by the linking mechanisms that the individual components and layers allow. The experiments in this thesis demonstrate that the: 1) behavior representation provides an interface for describing a behavior’s functionality without restricting or dictating its actual implementation; 2) hierarchy generation algorithm utilizes the representation interface for accomplishing high-level tasks through dynamic behavior sequencing; 3) representation, control logic, and architecture design create a loose coupling, but defined link, between the planning and behavior execution layer of the hybrid architecture, which creates a system-of-systems implementation that requires minimal reprogramming for system modifications
Incorporating temporal-bounded CBR techniques in real-time agents
Nowadays, MAS paradigm tries to move Computation to a new level of abstraction: Computation as interaction,
where large complex systems are seen in terms of the services they offer, and consequently in
terms of the entities or agents providing or consuming services. However, MAS technology is found to
be lacking in some critical environments as real-time environments. An interaction-based vision of a
real-time system involves the purchase of a responsibility by any entity or agent for the accomplishment
of a required service under possibly hard or soft temporal conditions. This vision notably increases the
complexity of these kinds of systems. The main problem in the architecture development of agents in
real-time environments is with the deliberation process where it is difficult to integrate complex
bounded deliberative processes for decision-making in a simple and efficient way. According to this, this
work presents a temporal-bounded deliberative case-based behaviour as an anytime solution. More specifically,
the work proposes a new temporal-bounded CBR algorithm which facilitates deliberative processes
for agents in real-time environments, which need both real-time and deliberative capabilities.
The paper presents too an application example for the automated management simulation of internal
and external mail in a department plant. This example has allowed to evaluate the proposal investigating
the performance of the system and the temporal-bounded deliberative case-based behaviour.
2010 Elsevier Ltd. All rights reserved.This work is supported by TIN2006-14630-C03-01 projects of the Spanish government, GVPRE/2008/070 project, FEDER funds and CONSOLIDER-INGENIO 2010 under Grant CSD2007-00022.Navarro Llácer, M.; Heras Barberá, SM.; Julian Inglada, VJ.; Botti Navarro, VJ. (2011). Incorporating temporal-bounded CBR techniques in real-time agents. Expert Systems with Applications. 38(3):2783-2796. https://doi.org/10.1016/j.eswa.2010.08.070S2783279638
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