behavior-based robotics is a novel approach to robotic programming whereby multiple behaviors execute in parallel using a multilayer architecture, organized by priority. However, in certain architectures, such as the ...
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ISBN:
(纸本)9781509047673
behavior-based robotics is a novel approach to robotic programming whereby multiple behaviors execute in parallel using a multilayer architecture, organized by priority. However, in certain architectures, such as the subsumption architecture pioneered by Rodney Brooks, only one such behavior can be active at a time, requiring their coordination. Supporting such architectures requires hardware/software resources for multithreaded support for behaviors to execute concurrently. This makes behavior-based programming inaccessible to small educational robotics platforms usually powered by a uniprocessor (single-threaded) execution model. In this paper, we present an approach employed for an introductory Mobile robotics course at the University of Nebraska-Lincoln that allows our students to both learn and implement behavior-based robotic programming using the C language on a uniprocessor-based mobile robotics platform known as the CEENBoT. This allows students to learn about robot programming using physical, situated robots, using a valuable language employed in embedded systems, supporting common goals of ECE programs, instead of relying on uncommon languages that have fallen into disuse and are quickly becoming obsolete. Results obtained from end-of-semester surveys are shown to demonstrate that students value the behavior-based elements of the course above other unique features it has to offer.
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 a...
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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.
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 coupl...
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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.
One of the core challenges of long-term autonomy is the environmental dynamics that agents must interact with. Some of these dynamics are driven by reliable cyclic processes, and thus are predictable. The most dominan...
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One of the core challenges of long-term autonomy is the environmental dynamics that agents must interact with. Some of these dynamics are driven by reliable cyclic processes, and thus are predictable. The most dominant of these is the daily solar cycle, which drives both natural phenomena like weather, as well as the activity of animals and humans. Circadian clocks are a widespread solution in nature to help organisms adapt to these dynamics, and demonstrate that many organisms benefit from maintaining simple models of their environments and how they change. Drawing inspiration from circadian systems, this work models relevant environmental states as times series, allowing for forecasts of the state to be generated without any knowledge of the underlying physics. These forecasts are treated as special percepts in a behavior-based architecture;providing estimates of the future state rather than measurements of the current state. They are incorporated into an ethologically based action-selection mechanism, where they influence the activation levels of behaviors. The approach was validated on a simulated agricultural task: a solar-powered agent monitoring pest populations. By using the artificial circadian system to leverage the forecasted state, the agent was able to improve performance and energy management.
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 anim...
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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.
Search and rescue (SAR) is one of the foremost issues in disaster management. A robust SAR mechanism can significantly reduce the number of causalities. This paper presents a behaviorbased model for a swarm of small ...
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Search and rescue (SAR) is one of the foremost issues in disaster management. A robust SAR mechanism can significantly reduce the number of causalities. This paper presents a behaviorbased model for a swarm of small robots to perform an efficient SAR operation in an unknown environment. The swarm is guided by a dynamically selected virtual leader (VL). A self-contained dynamic goal-seeking mechanism, using behavior-based approach, is designed to search targets (victims). Under the leadership of VL, the proposed model retains the integrity of the swarm while driving it from its current position to referenced goals. Fuzzy logic has been used to design constituent behavioral modules, namely obstacle avoidance, alignnient, and inter-robot cohesion. The model has been simulated to validate its efficiency and the findings reveal that robots moving as a swarm are more effective in the SAR process as compared to multiple single robots.
Departing from the conventional view of the reasons for the behavior of living systems, this research presents a radical and unique view of that behavior, as the observed side effects of a hierarchical set of simple, ...
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Departing from the conventional view of the reasons for the behavior of living systems, this research presents a radical and unique view of that behavior, as the observed side effects of a hierarchical set of simple, continuous, and dynamic negative feedback control systems, by way of an experimental model implemented on a real-world autonomous robotic rover. Rather than generating specific output from input, the systems control their perceptual inputs by varying output. The variables controlled do not exist in the environment, but are entirely internal perceptions constructed as a result of the layout and connections of the neural architecture. As the underlying processes are independent of the domain, the architecture is universal and thus has significant implications not only for understanding natural living systems, but also for the development of robotics systems. The central process of perceptual control has the potential to unify the behavioral sciences and is proposed as the missing behavioral principle of Artificial Life.
In this manuscript, we propose an approach that allows a team of robots to create new (emergent) behaviors at execution time. Basically, we improve the approach called N-Learning used for self-programming of robots in...
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In this manuscript, we propose an approach that allows a team of robots to create new (emergent) behaviors at execution time. Basically, we improve the approach called N-Learning used for self-programming of robots in a team, by modifying and extending its functioning structure. The basic capability of behavior sharing is increased by the catching of emergent behaviors at run time. With this, all robots are able not only to share existing knowledge, here represented by blocks of codes containing desired behaviors but also to creating new behaviors as well. Experiments with real robots are presented in order to validate our approach. The experiments demonstrate that after the human-robot interaction with one robot using Program by Demonstration, this robot generates a new behavior at run time and teaches a second robot that performs the same learned behavior through this improved version of the N-learning system.
An approach for the verification of autonomous behavior-based robotic missions has been developed in a collaborative effort between Fordham University and Georgia Tech. This paper addresses the step after verification...
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ISBN:
(纸本)9783319419596;9783319419589
An approach for the verification of autonomous behavior-based robotic missions has been developed in a collaborative effort between Fordham University and Georgia Tech. This paper addresses the step after verification, how to present this information to users. The verification of robotic missions is inherently probabilistic, opening the possibility of misinterpretation by operators. A human study was performed to test three different displays (numeric, graphic, and symbolic) for summarizing the verification results. The displays varied by format and specificity. Participants made decisions about high-risk robotic missions using a prototype interface. Consistent with previous work, the type of display had no effect. The displays did not reduce the time participants took compared to a control group with no summary, but did improve the accuracy of their decisions. Participants showed a strong preference for more specific data, heavily using the full verification results. based on these results, a different display paradigm is suggested.
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