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CBBR: enabling distributed shared memory-based coordination among mobile robots

Science China(Information Sciences) 2016年第8期59卷 23-39页

作者： Xue JIANG Yu HUANG State Key Laboratory for Novel Software Technology Nanjing University

Coordinating mobile robots are widely used in commercial and industrial settings to fulfill various tasks. However, to program the coordination among mobile robots is challenging. A coordination framework is needed to shield the programmer from handling low-level details of robot control and communication, while supporting flexible and cost-effective coordination at the same time. The coordination framework should also be able to well coexist with the underlying robot control. To this end, we propose the Coordination-enabled behavior-based robotics(CBBR) framework. CBBR employs Distributed Shared Memory(DSM) to support coordination. The shared memory illusion built by the DSM greatly simplifies the coordination logic. Moreover,the flexible access patterns of the DSM and the rich consistency semantics of the DSM reads and writes enable flexible and cost-effective coordination. With the coordination support from the DSM, CBBR naturally extends the classical behavior-based robotics(BBR) for robot control. From the perspective of robot control using BBR, the shared variables in the DSM act as the logical sensors capturing the status of coordination. The coordination algorithms are encapsulated into coordination behaviors. Thus, the physical environment status and the coordination status may trigger the physical and the coordination behaviors. The scheduling of both types of behaviors integrates coordination into robot control. We conduct a case study to demonstrate the use of CBBR. The performance measurements show the cost-effectiveness of coordinating mobile robots based on CBBR, in terms of time, space, and energy consumption.

关键词： distributed shared memory behavior-based robotics coordination behavior hierarchy behavior scheduling

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behavior-based swarm model using fuzzy controller for route planning and E-waste collection

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2022年第14期29卷 19940-19954页

作者： Batoo, Khalid Mujasam Pandiaraj, Saravanan Muthuramamoorthy, Muthumareeswaran Raslan, Emad H. Krishnamoorthy, Sujatha King Saud Univ Coll Sci King Abdullah Inst Nanotechnol Riyadh Saudi Arabia CFY Deanship King Saud Univ Riyadh Saudi Arabia King Saud Univ Coll Sci Dept Phys Riyadh Saudi Arabia Wenzhou Kean Univ Dept Comp Sci Wenzhou 325060 Zhejiang Peoples R China

Nowadays, because of the increase in consumption of electronic equipment and its resource utilization, household e-waste has been generated gradually. The increase in e-waste generation brought environmental burdens as well as a health risk in several nations. The disposal of e-waste in landfills is not recommended due to some poisonous and contaminated chemicals. The improper collection of e-waste leads to a negative impact on human health and also causes air pollution, as well as the long-term effects on the environment. To address such issues, the behavior-based swarm model using a fuzzy controller (BSFC) is proposed for efficient e-waste collection. The proposed algorithm is employed to solve the problem based on routing associated with the time window for the heterogeneous fleet of the e-waste collection vehicle. The approach is provided for the online system that enables the people to request for the collection of e-waste components and also to solve the vehicle's routing problem. The optimization result demonstrates the decrease in the collection cost and also the on-time e-waste collection from the household. The method comprises the implementation of e-waste collection requests in China and India for several urban arrangements of buildings and streets. The proposed approach fetches considerable enhancement in vehicle routing plans for the e-waste collection, counting the positive social impacts for the waste collection, particularly in urban regions.

关键词： E-waste transportation Virtual leader E-waste collection Search and rescue Fuzzy controller WEEE behavior-based robotics

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Real-time behavior-based robot control

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AUTONOMOUS ROBOTS 2011年第3期30卷 233-242页

作者： Woolley, Brian G. Peterson, Gilbert L. Kresge, Jared T. USAF Inst Technol Dept Elect & Comp Engn Wright Patterson AFB OH 45433 USA

behavior-based systems form the basis of autonomous control for many robots, but there is a need to ensure these systems respond in a timely manner. Unexpected latency can adversely affect the quality of an autonomous system's operations, which in turn can affect lives and property in the real-world. A robots ability to detect and handle external events is paramount to providing safe and dependable operation. This paper presents a concurrent version of a behavior-based system called the Real-Time Unified behavior Framework, which establishes a responsive basis of behavior-based control that does not bind the system developer to any single behavior hierarchy. The concurrent design of the framework is based on modern software engineering principles and only specifies a functional interface for components, leaving the implementation details to the developers. In addition, the individual behaviors are executed by a real-time scheduler, guaranteeing the responsiveness of routines that are critical to the autonomous system's safe operation. Experimental results demonstrate the ability of this approach to provide predictable temporal operation, independent of fluctuations in high-level computational loads.

关键词： General purpose real-time operating systems behavior-based robotics Reactive behavior hierarchies

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Insights on obstacle avoidance for small unmanned aerial systems from a study of flying animal behavior

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robotics AND AUTONOMOUS SYSTEMS 2018年 99卷 17-29页

作者： Sarmiento, Traci A. Murphy, Robin R. Texas A&M Univ Dept Comp Sci & Engn College Stn TX 77845 USA

Thirty-five papers from the ethological literature were surveyed with the perception and reaction of flying animals to autonomous navigation tasks organized and analyzed using a schema theoretic framework. Flying animals are an existence proof of autonomous collision-free flight in unknown and disordered environments. Because they successfully avoid obstacles, self-orient, and evade predators and capture prey to survive, the collected information could inform the design of biologically-inspired behaviors for control of a small unmanned aerial system (SUAS) to improve the current state-of-the art in autonomous obstacle avoidance. Five observations were derived from the surveyed papers: sensing is done by vision in lighted scenarios and sonar in darkness, one sensor is always dominant, adaptive sensing is beneficial, no preference was identified for lateral versus vertical avoidance maneuvers, and reducing speed is consistently seen across species in response to objects in the flight path. Additionally, the questions of defining clutter and scale of speed reduction left unanswered by the literature were discussed. Finally, three rules for control of a SUAS in an unknown environment that restricts maneuverability were identified. These are the distance to begin maneuvers to avoid an obstacle in the flight path, the direction to adjust the flight path, and the role of centered flight in determining the adjustment. Published by Elsevier B.V.

关键词： Bio-inspired behavior-based robotics Animal behavior Small unmanned aerial systems

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A navigational primitive: Biorobotic implementation of cycloptic helical klinotaxis in planar motion

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IEEE JOURNAL OF OCEANIC ENGINEERING 2004年第3期29卷 795-806页

作者： Long, JH Lammert, AC Pell, CA Kemp, M Strother, JA Crenshaw, HC McHenry, MJ Vassar Coll Program Cognit Sci Poughkeepsie NY 12604 USA Vassar Coll Dept Biol Poughkeepsie NY 12604 USA Nekton Res LLC Durham NC 27713 USA Univ Calif Berkeley Dept Integrat Biol Berkeley CA 94720 USA GlaxoSmithKline Technol Dev Dept Res Triangle Pk NC 27709 USA Harvard Univ Dept Organism & Evolutionary Biol Cambridge MA 02138 USA

A broad diversity of microorganisms and larval aquatic animals swim along a helical. trajectory. Helical movement toward or away from stimuli involves the detection of gradients, alteration of the helical trajectory, and gradient tracking. Using sensory and neural circuitry models from swimming simulations of tadpole-like ascidian larvae (Phylum Chordata, Subphylum Urochordata), we built and tested a single-sensor, surface-swimming, tail-flapping robot that swims up a light gradient and holds station at an orbital around an area of high intensity. We implemented the some neural circuitry in a terrestrial, wheeled robot with a single photoresistor;it exhibited similar navigational behavior. We also mathematically modeled single-sensor robots navigating in plane. The simulated robots showed the importance of sensor placement and excitation field on navigational behavior. When the sensor placement and excitation field of the simulated robot matched that of the embodied robots, navigational behavior was similar. These results 1) tested and supported a proposed neural circuitry model, 2) showed the simplicity and effectiveness of using a single light sensor for navigation, and 3) demonstrated the use of helical motion in two dimensions.

关键词： aquatic vehicles behavior-based robotics navigation neural control

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Unified behavior Framework for Reactive Robot Control

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2009年第2-3期55卷 155-176页

作者： Woolley, Brian G. Peterson, Gilbert L. USAF Inst Technol Dept Elect & Comp Engn Wright Patterson AFB OH 45433 USA

behavior-based systems form the basis of autonomous control for many robots. In this article, we demonstrate that a single software framework can be used to represent many existing behavior based approaches. The unified behavior framework presented, incorporates the critical ideas and concepts of the existing reactive controllers. Additionally, the modular design of the behavior framework: (1) simplifies development and testing;(2) promotes the reuse of code;(3) supports designs that scale easily into large hierarchies while restricting code complexity;and (4) allows the behavior based system developer the freedom to use the behavior system they feel will function the best. When a hybrid or three layer control architecture includes the unified behavior framework, a common interface is shared by all behaviors, leaving the higher order planning and sequencing elements free to interchange behaviors during execution to achieve high level goals and plans. The framework's ability to compose structures from independent elements encourages experimentation and reuse while isolating the scope of troubleshooting to the behavior composition. The ability to use elemental components to build and evaluate behavior structures is demonstrated using the Robocode simulation environment. Additionally, the ability of a reactive controller to change its active behavior during execution is shown in a goal seeking robot implementation.

关键词： behavior-based robotics Reactive control architecture Software design patterns Software frameworks

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Application of SONQL for real-time learning of robot behaviors

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robotics AND AUTONOMOUS SYSTEMS 2007年第8期55卷 628-642页

作者： Carreras, Marc Yuh, Junku Baffle, Joan Ridao, Pere Univ Girona Inst Informat & Appl Girona 17071 Spain Natl Sci Fdn Arlington VA 22230 USA

This paper describes the Semi-Online Neural-Q-leaming (SONQL) algorithm designed for real-time learning of reactive robot behaviors. The Q-function is generalized by a multilayer neural network allowing the use of continuous states. The algorithm uses a database of the most recent learning samples to accelerate and improve the convergence. Each SONQL algorithm represents an independent, reactive and adaptive state-action mapping, which implements the function of a robot behavior for one degree of freedom (DOF). The generalization capability of the SONQL algorithm was demonstrated by computer simulation with the '' mountain-car '' benchmark. The SONQL was also investigated by experiment on a mobile robot for a target-following task. Experimental results show that the SONQL is promising for online robot learning. (c) 2007 Elsevier B.V. All rights reserved.

关键词： reinforcement learning Q-learning behavior-based robotics autonomous vehicles

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Dynamic Leader Allocation in Multi-robot Systems based on Nonlinear Model Predictive Control

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2020年第2期98卷 359-376页

作者： Tavares, Augusto de Holanda B. M. Madruga, Sarah Pontes Brito, Alisson V. Nascimento, Tiago P. Univ Fed Paraiba Dept Comp Syst Lab Syst Engn & Robot Joao Pessoa Paraiba Brazil

This paper presents an approach to the dynamic leader selection problem in autonomous non-holonomic mobile robot formations when the current leader enters a failure state. Our method is based on a tree structure coupled with a modified version of the Nonlinear Model Predictive Control (NMPC) that allows for behavior change at the controller level. An explanation of the control algorithm, behavior selection, and leader selection structure is given, after which the results of both simulations and experiments using a three robot formation are shown and discussed.

关键词： Nonlinear model predictive control behavior-based robotics Formation control Multi-robot systems

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The Null-Space-based behavioral Control for Mobile Robots with Velocity Actuator Saturations

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2010年第10期29卷 1317-1337页

作者： Arrichiello, Filippo Chiaverini, Stefano Indiveri, Giovanni Pedone, Paola Univ Cassino Dipartimento Automaz Elettromagnetismo Ingn Infor I-03043 Cassino FR Italy Univ Salento Dipartimento Ingn Innovaz I-73100 Lecce Italy

In this paper we present the application of the Null-Space-based behavioral (NSB) approach to the motion control of mobile robots with velocity saturated actuators. The NSB is a behavior-based robot control approach that uses a hierarchical organization of the tasks to guarantee that they are executed according to a desired priority: it uses a projection technique to avoid that, in the absence of actuator saturations, low-priority tasks could influence higher-priority tasks. The main contribution of this paper is the extension of the NSB approach to the case where actuator velocity saturation bounds are explicitly taken into account. The proposed solution dynamically scales task velocity commands so that the hierarchy of task priorities is preserved in spite of actuator velocity saturations. The approach has been validated on two specific case studies. In the first case, the NSB elaborates the motion directives for a single mobile robot that has to reach a target while avoiding a point obstacle;in this case, the mission is composed of two tasks. In the second case, the NSB elaborates the motion directives for a team of six mobile robots that has to entrap and escort a target;in this case the mission is composed of four tasks. The approach is validated by numerical simulations and by experiments with real mobile robots.

关键词： behavior-based robotics velocity saturated actuators mobile robots multi-robot systems

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Application of the utility function method for behavioral organization in a locomotion task

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IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 2005年第5期9卷 506-521页

作者： Pettersson, J Wahde, M Chalmers Dept Appl Mech S-41296 Gothenburg Sweden

The generation of a complete robotic brain for locomotion based on the utility function (UF) method for behavioral organization is demonstrated. A simulated, single-legged hopping robot is considered, and a two-stage process is used for generating the robotic brain. First, individual behaviors are constructed through artificial evolution of recurrent neural networks (RNNs). Thereafter, a behavioral organizer is generated through evolutionary optimization of utility functions. Two systems are considered: a simplified model with trivial dynamics, as well as a model using full newtonian dynamics. In both cases, the UF method was able to generate an adequate behavioral organizer, which allowed the robot to perform its primary task of moving through an arena, while avoiding collisions with obstacles and keeping the batteries sufficiently charged. The results for the simplified model were better than those for the dynamical model, a fact that could be attributed to the poor performance of the individual behaviors (implemented as RNNs) during extended operation.

关键词： behavioral organization behavior-based robotics evolutionary algorithms (EAs) structural optimization utility functions (UFs)

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