Behavior-based Control Research Articles

Mobile robots׳ modular navigation controller using spiking neural networks

Autonomous navigation plays an important role in mobile robots. Artificial neural networks (ANNs) have been successfully used in nonlinear systems whose models are difficult to build. However, the third generation neural networks – Spiking neural networks (SNNs) – contain features that are more attractive than those of traditional neural networks (NNs). Because SNNs convey both temporal and spatial information, they are more suitable for mobile robots׳ controller design. In this paper, a modular navigation controller based on promising spiking neural networks for mobile robots is presented. The proposed behavior-based target-approaching navigation controller, in which the reactive architecture is used, is composed of three sub-controllers: the obstacle-avoidance SNN controller, the wall-following SNN controller and the goal-approaching controller. The proposed modular navigation controller does not require accurate mathematical models of the environment, and is suitable to unknown and unstructured environments. Simulation results show that the proposed transition conditions for sub-controllers are feasible. The navigation controller can control the mobile robot to reach a target successfully while avoiding obstacles and following the wall to get rid of the deadlock caused by local minimum.

Behavior-Based Formation Control of Swarm Robots

Swarm robotics is a specific research field of multirobotics where a large number of mobile robots are controlled in a coordinated way. Formation control is one of the most challenging goals for the coordination control of swarm robots. In this paper, a behavior-based control design approach is proposed for two kinds of important formation control problems: efficient initial formation and formation control while avoiding obstacles. In this approach, a classification-based searching method for generating large-scale robot formation is presented to reduce the computational complexity and speed up the initial formation process for any desired formation. The behavior-based method is applied for the formation control of swarm robot systems while navigating in an unknown environment with obstacles. Several groups of experimental results demonstrate the success of the proposed approach. These methods have potential applications for various swarm robot systems in both the simulation and the practical environments.

Intelligent Control of a Small Climbing Robot

In this paper, a fuzzy logic-based control system is proposed, which lays emphasis on the functionality of the system rather than developing a mathematical model. Applied to a climbing robot, it can achieve precise motion control along with power consumption minimization and produce versatile behaviors based effective computational method in behavior-based control paradigm to implement robot behaviors. Experimental results prove the validity of the proposed methods. The proposed fuzzy logic-based control scheme is capable to automatically change the stickiness of hands and feet based on surface slope of unsupervised systems, thus keeping the control of the motion at a predefined stable level. The effectiveness of the proposed approach is demonstrated through experimental results.

Cooperative Control of Multiple Autonomous Underwater Vehicles

The focus of research of AUV is gradually moving towards multiple autonomous underwater vehicles (MAUV) in recent years. This paper describes an investigation into cooperative control of MAUV. Firstly, a distributed control architecture (MOOS) was applied to MAUV system. According to MOOS, functionalities of AUV were organized in a modular manner and a unified information exchange mechanism was used to ensure an efficient communication between different modules. Secondly, a behavior based control strategy was proposed to enable the AUV to cooperate with each other intelligently and adaptively. Interval programming algorithm was applied to make sure that behaviors of each AUV can be coordinated in a timely and optimal manner. Stability of behavior-based control of AUV was analyzed. Finally, a distributed simulation environment was established and a series of simulation were carried out to verify the feasibility of methods mentioned above.

An Ethology-Based Hybrid Control Architecture for an Autonomous Underwater Vehicle for Performing Multiple Tasks

In this paper, we propose a control architecture for an autonomous underwater vehicle (AUV), implemented in a hybrid architecture with two layers: a hierarchical planning layer and a reactive execution layer. Most of its tasks are interpreted as a set of waypoints and then specified actions at the points. Thus, in the planning layer, the task planner is designed as a waypoint planner using a genetic algorithm. This planner generates an optimized plan, considering given constraints such as positions of obstacles, current velocities, and task priority. In addition, the execution of the task plan is monitored by a mission supervisor, which determines ongoing tasks and can change the original plan if exceptional events occur. In the execution layer, a behavior-based control with an ethology-based action selection mechanism is implemented. As a result, the AUV can always choose the most appropriate behavior, maximizing its motivation, and the robot is controlled by the output of the selected behavior. Consequently, the proposed control architecture has an open and modular structure. Numerical simulations were conducted to verify its performance.

Mating Behavior of <I>Cnephasia jactatana</I> (Lepidoptera: Tortricidae), an Important Pest of Kiwifruit

Understanding mating behavioral sequence helps us identify the mechanisms of mate assessment and choice, and better evaluate behavior-based pest control strategies. Here we describe the mating behavior of Cnephasia jactatana Walker whose females release a sex pheromone, and determine the effect of male mating status on reproductive success. The mating sequence starts when males approach females and display courtship behavior with antennation and fanning wings. Both males and females may end a mating attempt at any stage of the sequence. Both sexes assess their mates from the initial contact to copulation. Females appear to be choosier at the early and mid-stages than at the late stage of the sequence. Virgin males approach and court females significantly earlier than nonvirgin males. As compared with nonvirgin males, virgin males are approximately 1.6 times more likely to approach and 1.8 times more likely to court females, and four times more likely to achieve mating. This may be attributed to depletion of sperm and accessory gland materials and reduced ability to respond to female sex pheromones in nonvirgin males. The number of attempts by males to acquire mates may be one of the traits that females assess before choosing their mates.

Antecedents of adaptive selling among retail salespeople: A multilevel analysis

The literature on adaptive selling behavior has grown rapidly over the years, with heavier emphasis placed on industrial/professional salespeople and less attention given to retail salespeople. This study contributes to addressing this imbalance by examining the effects of two salesperson factors (selling skills and affective commitment) and two company-level variables (empowerment and behavior-based control) on the adaptive selling behavior of retail salespeople. Using data obtained from a two staged sampling procedure (105 companies and 419 salespeople), we employ a multilevel analytical procedure to model the effects of the salesperson and organizational factors on adaptive selling behavior of retail salespeople. The results indicate that selling skills and affective commitment directly influence adaptive selling while empowerment and behavior based control only indirectly influence adaptive selling behavior. Based on the findings of this study, implications for managing retail salespeople as well as limitations and suggestions for future research are presented.

Command Fusion for Navigation of Mobile Robots in Dynamic Environments with Objects

In this paper, we propose a fuzzy inference model for a navigation algorithm for a mobile robot that intelligently searches goal location in unknown dynamic environments. Our model uses sensor fusion based on situational commands using an ultrasonic sensor. Instead of using the “physical sensor fusion” method, which generates the trajectory of a robot based upon the environment model and sensory data, a “command fusion” method is used to govern the robot motions. The navigation strategy is based on a combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance based on a hierarchical behavior-based control architecture. To identify the environments, a command fusion technique is introduced where the sensory data of the ultrasonic sensors and a vision sensor are fused into the identification process. The result of experiment has shown that highlights interesting aspects of the goal seeking, obstacle avoiding, decision making process that arise from navigation interaction.

Behavior-based access control for distributed healthcare systems

Sensitivity of clinical data and strict rules regarding data sharing have caused privacy and security to be critical requirements for using patient profiles in distributed healthcare systems. The amalgamation of new information technology with traditional healthcare workflows for sharing patient pr ofiles has made the whole system vulnerable to privacy and security breaches. Standardization organizations are developing specifications to satisfy the required privacy and security requirements. In this paper we present a novel access control model compliant with healthcare standards based on a framework designed for data and service interoperability in the healthcare domain. The proposed model for customizable access control captures the dynamic behavior of the user and determines access rights accordingly. The model is generic and flexible in the sense that an access control engine dynamically receives security effective parameters from the subject user, and identifies the privilege level in accessing data using different specialized components within the engine. Standard data representation formats and ontologies are used to make the model compatible with different healthcare systems. The access control engine employs an approach to follow the user's behavior and navigates among engine components to provide the user's privilege to access a resource. A simulation environment is implemented to evaluate and test the proposed model.

Impact of Organizational Control and Reward Systems on Service Quality: An Empirical Study

This study explores the influence of the organizational control and reward systems on the commitment and service quality of staff. A group of front-line service staffs handling sales tasks served as a sample to test the hypothesized model. Results using a structural equation model indicated that service staffs who operate under a behavior-based control system have higher organizational and professional commitment, and thus produce a higher service quality compared with those who work under an outcome-based control system. Moreover, a higher fixed salary percentage leads to higher professional commitment of service staffs. Organizational and professional commitments positively influence service quality. The implications of the findings are considered and suggestions for future research are provided.

Behavior-Based Fuzzy Control for Mobile Robot Navigation

A new behavior-based fuzzy control method for mobile robot navigation is presented. It is based on behavioral architecture which can deal with uncertainties in unknown environments and has the ability to accommodate different behaviors. Basic behaviors are controlled by specific fuzzy logic controllers, respectively. The proposed approach qualifies for driving a robot to reach a target while avoiding obstacles in the environment. Simulation and experiments are performed to verify the correctness and feasibility of the proposed method.

Learning-Oriented Sales Management Control: The Case of a Pharmaceutical Company

ABSTRACT Purpose: The primary goal was to identify organizational conditions for developing a learning-oriented behavioral control system, an issue that has been neglected in previous studies. Design/Methodology/Approach: The authors conducted a case study of Nippon Boehringer Ingelheim (NBI). Findings: We found that a behavior-based sales management control system facilitates learning by salespersons when 1) the focus is on skill development, 2) fewer key performance indicators are being used, and 3) supportive supervision and knowledge sharing are promoted. Research Limitations: Because this was a single case study, it is necessary to investigate other cases in other countries and to compare the results with those of NBI to develop theories about learning-oriented behavior control systems. Practical Implications: In the early stages of sales reform, sales managers and medical representatives should not use multiple process indicators for multiple evaluations; rather, they should use a small number of process indicators (e.g., number of visits per day) so that all individuals concerned about a problem can share information and promote improvement.

Behavior-based access control for distributed healthcare systems

Sensitivity of clinical data and strict rules regarding data sharing have caused privacy and security to be critical requirements for using patient profiles in distributed healthcare systems. The a...

Finite-time attitude synchronization controllers design for spacecraft formations via behavior-based approach

This article investigates the attitude synchronization problem of spacecraft formations. A class of continuous sliding mode control schemes with finite-time convergent property is developed. The control laws are designed by the utilization of behavior-based control approach. An improved version of terminal sliding mode is applied in both the reaching phase and the sliding phase of the control system. In the presence of external disturbances, the proposed control strategies are able to overcome the unexpected phenomenon and can steer the spacecraft formation to a dynamic reference attitude state coordinately subject to arbitrary communication topologies. Numerical simulations are provided to validate the theoretical analysis.

A Decentralized Architecture for Multi-Robot Systems Based on the Null-Space-Behavioral Control with Application to Multi-Robot Border Patrolling

This paper presents a control architecture for multi-robot systems. The proposed architecture has been developed in the framework of the Null-Space-based-Behavioral (NSB) control, a competitive-collaborative behavior-based control approach. The standard NSB statically determines a set of suitably defined elementary tasks (behaviors) and their priorities, i.e., they cannot be dynamically changed according to mission requirements and environmental constraints. In this paper, a three layer architecture has been designed in order to avoid such a drawback. The single robotic unit (agent) performing the mission is placed on the lower layer. In the middle layer, suitably defined elementary behaviors are defined; these elementary behaviors are then combined, via the NSB approach, in more complex actions. The upper layer is a Supervisor in charge of dynamically selecting the proper action to be executed. As further contribution, the architecture has been applied to the multi-robot border patrolling mission to generate a decentralized, deterministic and non-communicative solution that is robust to faults, and prevents collisions, even in the case of high robot density. Finally, the simulations on a team composed by a large number of robots, and experiments on a real setup, composed by three Pioneer-3DX robots, are provided.

The Principal-Agent Model of Organization Control Theory

We propose an analytical model that integrates two parallel streams of the literature, agency theory and organizational control theory that deal with related issues. In doing so, we provide new insights into agency theory by introducing the concept of a congruent agent, and new insights into organizational control theory by using a contracting model to analyze behavior and outcome forms of controls. We study outcome-based control, i.e. contracting on the outcome; behavior-based control, i.e. contracting on a signal of effort; behavior and outcome control, i.e. contracting on the outcome and a signal of effort, which is new to the organizational control literature; and clan control, i.e. employing agents with preferences aligned with the principal’s, which is new to the agency literature. To interpret clan control in the context of agency theory, we draw from recent theory and experimental evidence in behavioral economics by distinguishing between two types of agents: a self-interested agent, who behaves as modeled in the traditional agency literature; and a congruent agent, who cares about the principal’s payoff, which can be viewed as a form of “social” preferences in behavioral economics and a form of clan control resulting from “socialization” in organization theory. Corresponding to Ouchi’s (1979) view of organizational control, we analytically investigate conditions under which outcome-based control, behavior-based control, and clan control are optimal. We highlight four key dimensions, outcome uncertainty, behavior uncertainty, task uncertainty, the degree of congruence, in determining the optimal control strategy. Furthermore, we expand to four types of control and perform a simulation analysis that extends our analytical results.

행동기반 다개체 로봇 시스템을 이용한 환경감시 알고리즘

This paper proposes an environment monitoring algorithm using a behavior-based multiple robot system. This paper handles an escort and a boundary-tracking especially. Unlike previous research works, the proposed environment monitoring system which is based on the behavior-based multiple robot control allows the system to employ the reusable code and general algorithm. Also, the proposed method can be applied to cheaper process with low performances. In the proposed method, escort and boundary-tracking missions are constructed by weighted sum of predefined basic behaviors after redefining the basic behaviors in previous works and introducing the novel basic behavior. Simulation results of the proposed method are included to demonstrate the practical application of the proposed algorithm.

Self-assembly control and experiments in swarm modular robots

This paper presents a self-assembly control strategy for the swarm modular robots. Simulated and physical experiments are conducted based on the Sambot platform, which is a novel self-assembly modular robot having the characteristics of both the chain-type and the mobile self-reconfigurable robots. Multiple Sambots can autonomously move and connect with one another through self-assembly to form robotic organisms. The configuration connection state table is used to describe the configuration of the robotic structure. A directional self-assembly control model is proposed to perform the self-assembly experiments. The self-assembly process begins with one Sambot as the seed, and then the Docking Sambots use a behavior-based controller to achieve connection with the seed Sambot. The controller is independent of the target configuration. The seed and connected Sambots execute a configuration comparison algorithm to control the growth of the robotic structure. Furthermore, the simultaneous self-assembly of multiple Sambots is discussed. For multiple configurations, self-assembly experiments are conducted in simulation platform and physical platform of Sambot. The experimental results verify the effectiveness and scalability of the self-assembly algorithms.

Decentralized coordinated control for multiple spacecraft formation maneuvers

We investigate the decentralized coordinated control problem by looking into local information exchange among formation flying spacecraft regarding formation maneuvers. The nonlinear dynamics that describes the motion of formation flying spacecraft relative to a reference spacecraft is considered for the general case, in which the reference spacecraft is in an ideal elliptical orbit. With the novel use of consensus algorithms combined with behavior-based control, coordinated formation controllers are proposed for three schemes: (i) with full state feedback; (ii) without velocity measurements; (iii) and with external disturbances and parametric uncertainty. The three algorithms used in the schemes can achieve both formation maneuvering and formation keeping, as well as consider actuator saturation. Numerous simulations demonstrate the effectiveness of the proposed control schemes.

Allosteric Antagonism of Insect Odorant Receptor Ion Channels

BackgroundAt a molecular level, insects utilize members of several highly divergent and unrelated families of cell-surface chemosensory receptors for detection of volatile odorants. Most odors are detected via a family of odorant receptors (ORs), which form heteromeric complexes consisting of a well-conserved OR co-receptor (Orco) ion channel and a non-conserved tuning OR that provides coding specificity to each complex. Orco functions as a non-selective cation channel and is expressed in the majority of olfactory receptor neurons (ORNs). As the destructive behaviors of many insects are principally driven by olfaction, Orco represents a novel target for behavior-based control strategies. While many natural and synthetic odorants have been shown to agonize Orco/Or complexes, only a single direct Orco modulator, VUAA1, has been described. In an effort to identify additional Orco modulators, we have investigated the structure/activity relationships around VUAA1.ResultsA search of our compound library identified several VUAA1 analogs that were selected for evaluation against HEK cells expressing Orco from the malaria vector Anopheles gambiae (AgOrco). While the majority of compounds displayed no activity, many of these analogs possess no intrinsic efficacy, but instead, act as competitive VUAA1 antagonists. Using calcium mobilization assays, patch clamp electrophysiology, and single sensillum in vivo recording, we demonstrate that one such candidate, VU0183254, is a specific allosteric modulator of OR signaling, capable of broadly inhibiting odor-mediated OR complex activation.ConclusionsWe have described and characterized the first Orco antagonist, that is capable of non-competitively inhibiting odorant-evoked activation of OR complexes, thereby providing additional insight into the structure/function of this unique family of ligand-gated ion channels. While Orco antagonists are likely to have limited utility in insect control programs, they represent important pharmacological tools that will facilitate the investigation of the molecular mechanisms underlying insect olfactory signal transduction.