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A behavioral robotics Approach to Radiation Mapping Using Adaptive Sampling

APPLIED SCIENCES-BASEL 2025年第4期15卷 2050-2050页

作者： Adams, Joel Cintas, Brendon Sung, Nakwon Abrahao, Anthony Lagos, Leonel Mcdaniel, Dwayne Florida Int Univ Fac Mech Engn Miami FL 33199 USA

Radiation mapping is a desirable task to automate because of the inherent risks involved and its tedious nature. A novel system was designed to address this by combining various existing technologies, utilizing behavior-based robotics and Bayesian optimization. The system uses a quadruped robot equipped with a manipulator and gamma detector to take measurements at locations that are selected based on the uncertainty of a surrogate model used to estimate the true radiation field. The robot uses input from the world with depth cameras to avoid collisions with the robot's body, and unreachable points for the end effector are addressed by both allowing for a soft collision with the environment to occur, prompting the system to abandon that point, and varying the exploration tendency of the optimization based on consecutive collisions. This approach provides unique traversability and adaptability over other strategies in the literature. Experiments were performed by placing a Cesium-137 source on the ground and varying geometric setups and an optimization parameter demonstrating the adaptability to diverse environments and the increased robustness resulting from the designed behavior. The results additionally demonstrate that dynamically adjusting the optimization algorithm's exploration tendency based on the arm's collision history improves the system's ability to navigate cluttered environments and construct accurate radiation maps without getting stuck in unreachable areas.

关键词： behavioral robotics radiation mapping Bayesian optimization adaptive sampling manipulators

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Mereogeometry Based Approach for behavioral robotics 1

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International Joint Conference on Rough Sets (IJCRS)

作者： Gnys, Piotr Polish Japanese Acad Informat Technol Dept Comp Sci Ul Koszykowa 86 PL-02008 Warsaw Poland

In this paper we will attempt to create simple behavioral agent with reasoning based in mereogeometry. Main purpose of this research is to check if mereogeometry is viable approach for writing low level behavioral sys... 详细信息

ISBN: (数字)9783319608402

ISBN: (纸本)9783319608402;9783319608396

关键词： Mereology Mereogeometry Rough mereology behavioral robotics Flocking

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A Reference Architecture for Social Head Gaze Generation in Social robotics

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INTERNATIONAL JOURNAL OF SOCIAL robotics 2015年第5期7卷 601-616页

作者： Srinivasan, Vasant Murphy, Robin R. Bethel, Cindy L. Texas A&M Univ Dept Comp Sci & Engn College Stn TX 77843 USA Mississippi State Univ Dept Comp Sci & Engn Mississippi State MS 39762 USA

This article outlines a reference architecture for social head gaze generation in social robots. The architecture discussed here is grounded in human communication, based on behavioral robotics theory, and captures the commonalities, essence, and experience of 32 previous social robotics implementations of social head gaze. No such architecture currently exists, but such an architecture is needed to: (1) serve as a template for creating or re-engineering systems, (2) provide analyses and understanding of different systems, and (3) provide a common lexicon and taxonomy that facilitates communication across various communities. A constructed reference architecture and the Software Architecture Analysis Method (SAAM) are used to evaluate, improve, and re-engineer two existing head gaze system architectures (Human-Robot Collaboration architecture and Robot Behavior Toolkit architecture). SAAM shows that no existing architecture incorporated the summation of functionalities found in the 32 studies. SAAM suggests several architectural improvements so that the two existing architectures can better support adaptation to a new environment and extension of capability. The resulting reference architecture guides the implementation of social head gaze in a rescue robot for the purpose of victim management in urban search and rescue (US&R). Using the proposed reference architecture will benefit social robotics because it will simplify the principled implementations of head gaze generation and allow for comparisons between such implementations.

关键词： Reference architecture Social head gaze behavioral robotics Human-robot interaction

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Maze exploration behaviors using an integrated evolutionary robotics environment

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robotics AND AUTONOMOUS SYSTEMS 2004年第3期46卷 159-173页

作者： Nelson, AL Grant, E Galeotti, JM Rhody, S N Carolina State Univ Dept Elect & Comp Engn CRIM Raleigh NC 27695 USA

This paper presents results generated with a new evolutionary robotics (ER) simulation environment and its complementary real mobile robot colony research test-bed. Neural controllers producing mobile robot maze searching and exploration behaviors using binary tactile sensors as inputs were evolved in a simulated environment and subsequently transferred to and tested on real robots in a physical environment. There has been a considerable amount of proof-of-concept and demonstration research done in the field of ER control in recent years, most of which has focused on elementary behaviors such as object avoidance and homing. Artificial neural networks (ANN) are the most commonly used evolvable controller paradigm found in current ER literature. Much of the research reported to date has been restricted to the implementation of very simple behaviors using small ANN controllers. In order to move beyond the proof-of-concept stage our ER research was designed to train larger more complicated ANN controllers, and to implement those controllers on real robots quickly and efficiently. To achieve this a physical robot test-bed that includes a colony of eight real robots with advanced computing and communication abilities was designed and built. The real robot platform has been coupled to a simulation environment that facilitates the direct wireless transfer of evolved neural controllers from simulation to real robots (and vice versa). We believe that it is the simultaneous development of ER computing systems in both the simulated and the physical worlds that will produce advances in mobile robot colony research. Our simulation and training environment development focuses on the definition and training of our new class of ANNs, networks that include multiple hidden layers, and time-delayed and recurrent connections. Our physical mobile robot design focuses on maximizing computing and communications power while minimizing robot size, weight, and energy usage. The simulation and

关键词： evolutionary robotics behavioral robotics evolutionary neural networks Distributed robotics robot colonies

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Enhanced Robot Speech Recognition Using Biomimetic Binaural Sound Source Localization

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2019年第1期30卷 138-150页

作者： Davila-Chacon, Jorge Liu, Jindong Wermter, Stefan Univ Hamburg Knowledge Technol Grp Dept Informat Vogt Kolln Str 30 D-22527 Hamburg Germany Imperial Coll London Dept Comp South Kensington Campus London SW7 2AZ England

Inspired by the behavior of humans talking in noisy environments, we propose an embodied embedded cognition approach to improve automatic speech recognition (ASR) systems for robots in challenging environments, such as with ego noise, using binaural sound source localization (SSL). The approach is verified by measuring the impact of SSL with a humanoid robot head on the performance of an ASR system. More specifically, a robot orients itself toward the angle where the signal-to-noise ratio (SNR) of speech is maximized for one microphone before doing an ASR task. First, a spiking neural network inspired by the midbrain auditory system based on our previous work is applied to calculate the sound signal angle. Then, a feedforward neural network is used to handle high levels of ego noise and reverberation in the signal. Finally, the sound signal is fed into an ASR system. For ASR, we use a system developed by our group and compare its performance with and without the support from SSL. We test our SSL and ASR systems on two humanoid platforms with different structural and material properties. With our approach we halve the sentence error rate with respect to the common downmixing of both channels. Surprisingly, the ASR performance is more than two times better when the angle between the humanoid head and the sound source allows sound waves to be reflected most intensely from the pinna to the ear microphone, rather than when sound waves arrive perpendicularly to the membrane.

关键词： Automatic speech recognition behavioral robotics binaural sound source localization (SSL) bioinspired neural architectures

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VisionBug: A hexapod robot controlled by stereo cameras

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AUTONOMOUS ROBOTS 2002年第3期13卷 259-276页

作者： Chow, YH Chung, R Chinese Univ Hong Kong Dept Automat & Comp Aided Engn Sha Tin Hong Kong Peoples R China

A six-legged robot system demonstrating reactive behaviors of simple organisms-walking between two walls, steering around obstacles, making turns at corners, and making U-turns at pathway dead-ends-is described. The system, named VisionBug, uses no active range sensor but only a stereo pair of cameras for sensing the surroundings. The system assumes the surroundings to be consisting of mostly a ground surface, although the surface could have a varying geometric relationship with the robot due to the jiggling nature of legged motion. By the use of the image-to-image mapping induced to the stereo images by the ground surface, the system is able to avoid explicit 3D reconstruction and the use of optical flow altogether in locating through-ways. Specifically, it regards image features not respecting the ground-induced mapping as obstacles, and express the obstacles in terms of a 2D distribution on the ground. Based on the distribution information, which is further time-delay compensated, a simple fuzzy control mechanism is used to command the legged motion. Experiments show that the system is effective for demonstrating the above-mentioned behaviors in textured environment, at a speed fast enough for many applications.

关键词： legged robot behavioral robotics stereo visually guided locomotion fuzzy control

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Evolution of neural controllers for competitive game playing with teams of mobile robots

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robotics AND AUTONOMOUS SYSTEMS 2004年第3期46卷 135-150页

作者： Nelson, AL Grant, E Henderson, TC N Carolina State Univ Dept Elect & Comp Engn Ctr Robot & Intelligent Machines Raleigh NC 27695 USA Univ Utah Sch Comp Salt Lake City UT 84112 USA

In this work, we describe the evolutionary training of artificial neural network controllers for competitive team game playing behaviors by teams of real mobile robots. This research emphasized the development of methods to automate the production of behavioral robot controllers. We seek methods that do not require a human designer to define specific intermediate behaviors for a complex robot task. The work made use of a real mobile robot colony (EVolutionary roBOTs) and a closely coupled computer-based simulated training environment. The acquisition of behavior in an evolutionary robotics system was demonstrated using a robotic version of the game Capture the Flag. In this game, played by two teams of competing robots, each team tries to defend its own goal while trying to 'attack' another goal defended by the other team. Robot neural controllers relied entirely on processed video data for sensing of their environment. Robot controllers were evolved in a simulated environment using evolutionary training algorithms. In the evolutionary process, each generation consisted of a competitive tournament of games played between the controllers in an evolving population. Robot controllers were selected based on whether they won or lost games in the course of a tournament. Following a tournament, the neural controllers were ranked competitively according to how many games they won and the population was propagated using a mutation and replacement strategy. After several hundred generations, the best performing controllers were transferred to teams of real mobile robots, where they exhibited behaviors similar to those seen in simulation including basic navigation, the ability to distinguish between different types of objects, and goal tending behaviors. (C) 2004 Elsevier B.V. All rights reserved.

关键词： evolutionary robotics robot colonies mobile robots evolutionary neural computing behavioral robotics

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A dynamic computational model of motivation based on self-determination theory and CANN

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INFORMATION SCIENCES 2019年 476卷 319-336页

作者： Chame, Hendry Ferreira Mota, Fernanda Pinto da Costa Botelho, Silvia Silva Univ Fed Rio Grande FURG Programa Posgrad Modelagem Computac Ctr Ciencias Computac C3 Rio Grande Brazil

The hierarchical model of intrinsic and extrinsic motivation (HMIEM) is a framework based on the principles of self-determination theory (SDT) which describes human motivation from a multilevel perspective, and integrates knowledge on personality and social psychological determinants of motivation and its consequences. Although over the last decades HMIEM has grounded numerous correlational studies in diverse fields, it is conceptually defined as a schematic representation of the dynamics of motivation, that is not suitable for human and artificial agents research based on tracking. In this work we propose an analytic description named dynamic computational model of motivation (DCMM), inspired by HMIEM and based on continuous attractor neural networks, which consists in a computational framework of motivation. In DCMM the motivation state is represented within a self-determination continuum with recurrent feedback connections, receiving inputs from heterogeneous layers. Through simulations we show the modeling of complete scenarios in DCMM. A field study with faculty subjects illustrates how DCMM can be provided with data from SDT constructs observations. We believe that DCMM is relevant for investigating unresolved issues in HMIEM, and potentially interesting to related fields, including psychology, artificial intelligence, behavioral and developmental robotics, and educational technology. (C) 2018 Elsevier Inc. All rights reserved.

关键词： Self-determination theory Neural networks Motivation HMIEM CANN Tracking behavioral robotics Educational technology

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A colony of robots using vision sensing and evolved neural controllers

A colony of robots using vision sensing and evolved neural c...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Nelson, AL Grant, E Barlow, GJ Henderson, TC N Carolina State Univ Dept Elect & Comp Engn Ctr Robot & Intelligence Machines Raleigh NC 27695 USA

ISBN: (纸本)0780378601

This paper describes the development and testing of a new evolutionary robotics research test bed. The test bed consists of a colony of small computationally powerful mobile robots that use evolved neural network controllers and vision based sensors to generate team game-playing behaviors. The vision based sensors function by converting video images into range and object color data. Large evolvable neural network controllers use these sensor data to control mobile robots. The networks require 150 individual input connections to accommodate the processed video sensor data. Using evolutionary computing methods, the neural network based controllers were evolved to play the competitive team game Capture the Flag with teams of mobile robots. Neural controllers were evolved in simulation and transferred to real robots for physical verification. Sensor signals in the simulated environment are formatted to duplicate the processed real video sensor values rather than the raw video images. Robot controllers receive sensor signals and send actuator commands of the same format, whether they are driving physical robots in a real environment or simulated robots agents in an artificial environment. Evolved neural controllers can be transferred directly to the real mobile robots for testing and evaluation. Experimental results generated with this new evolutionary robotics research test bed are presented.

关键词： evolutionary robotics robot colonies mobile robots evolutionary neural computing behavioral robotics vision robot vision

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Meta-level control under uncertainty for handling multiple consumable resources of robots

Meta-level control under uncertainty for handling multiple c...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Le Gloannec, S Mouaddib, AI Charpillet, F Univ Caen GREYC F-14032 Caen France

ISBN: (纸本)0780389123

Most of works on planning under uncertainty in AI assumes rather simple action models, which do not consider multiple resources. This assumption is not reasonable for many applications such as planetary rovers or robotics which much cope with uncertainty about the duration of tasks, the energy, and the data storage. In this paper, we outline an approach to control the operation of an autonomous rover which operates under multiple resource constraints. We consider a directed acyclic graph of progressive processing tasks with multiple resources, for which an optimal policy is obtained by solving a corresponding Markov Decision Process (MDP). Computing an optimal policy for an MDP with multiple resources makes the search space large. We cannot calculate this optimal policy at run-time. The approach developed in this paper overcomes this difficulty by combining: decomposition of a large MDP into smaller ones, compression of the state space by exploiting characteristics of the multiple resources constraint, construction of local policies for the decomposed MDPs using state space discretization and resource compression, and recomposition of the local policies to obtain a near optimal global policy. Finally, we present first experimental results showing the feasibility and performances of our approach.

关键词： supervisory control agents and agent based systems behavioral robotics mobile robotics

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