scholarly journals Autonomous Navigation Framework for Intelligent Robots Based on a Semantic Environment Modeling

2020 ◽  
Vol 10 (9) ◽  
pp. 3219 ◽  
Author(s):  
Sung-Hyeon Joo ◽  
Sumaira Manzoor ◽  
Yuri Goncalves Rocha ◽  
Sang-Hyeon Bae ◽  
Kwang-Hee Lee ◽  
...  
Keyword(s):  
Autonomous Navigation ◽  
Action Planning ◽  
Environment Modeling ◽  
Modeling Framework ◽  
Intelligent Robots ◽  
Semantic Models ◽  
Autonomous Robot Navigation ◽  
Environment Maps ◽  
Implicit And Explicit ◽  
And Behavior

Humans have an innate ability of environment modeling, perception, and planning while simultaneously performing tasks. However, it is still a challenging problem in the study of robotic cognition. We address this issue by proposing a neuro-inspired cognitive navigation framework, which is composed of three major components: semantic modeling framework (SMF), semantic information processing (SIP) module, and semantic autonomous navigation (SAN) module to enable the robot to perform cognitive tasks. The SMF creates an environment database using Triplet Ontological Semantic Model (TOSM) and builds semantic models of the environment. The environment maps from these semantic models are generated in an on-demand database and downloaded in SIP and SAN modules when required to by the robot. The SIP module contains active environment perception components for recognition and localization. It also feeds relevant perception information to behavior planner for safely performing the task. The SAN module uses a behavior planner that is connected with a knowledge base and behavior database for querying during action planning and execution. The main contributions of our work are the development of the TOSM, integration of SMF, SIP, and SAN modules in one single framework, and interaction between these components based on the findings of cognitive science. We deploy our cognitive navigation framework on a mobile robot platform, considering implicit and explicit constraints for autonomous robot navigation in a real-world environment. The robotic experiments demonstrate the validity of our proposed framework.

scholarly journals An Improved FastSLAM System Based on Distributed Structure for Autonomous Robot Navigation

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Fu-jun Pei ◽  
Hao-yang Li ◽  
Yu-hang Cheng
Keyword(s):  
State Estimation ◽  
Autonomous Navigation ◽  
State Equation ◽  
System Equation ◽  
Distributed Structure ◽  
Mobile Vehicle ◽  
Localization And Mapping ◽  
Unscented Particle Filter ◽  
Autonomous Robot Navigation ◽  
Vehicle State Estimation

Fast simultaneous localization and mapping (FastSLAM) is an efficient algorithm for autonomous navigation of mobile vehicle. However, FastSLAM must reconfigure the entire vehicle state equation when the feature points change, which causes an exponential growth in quantities of computation and difficulties in isolating potential faults. In order to overcome these limitations, an improved FastSLAM, based on the distributed structure, is developed in this paper. There are two state estimation parts designed in this improved FastSLAM. Firstly, a distributed unscented particle filter is used to avoid reconfiguring the entire system equation in the vehicle state estimation part. Secondly, in the landmarks estimation part, the observation model is designed as a linear one to update the landmarks states by using the linear observation errors. Then, the convergence of the proposed and improved FastSLAM algorithm is given in the sense of mean square. Finally, the simulation results show that the proposed distributed algorithm could reduce the computational complexity with high accuracy and high fault-tolerance performance.

Autonomous navigation and environment modeling for MAVs in 3-D enclosed industrial environments

2013 ◽  
Vol 64 (9) ◽  
pp. 1161-1177 ◽  
Author(s):  
Qing Li ◽  
Da-Chuan Li ◽  
Qin-fan Wu ◽  
Liang-wen Tang ◽  
Yan Huo ◽  
...  
Keyword(s):  
Autonomous Navigation ◽  
Environment Modeling ◽  
Industrial Environments

scholarly journals Visual Head Counts: A Promising Method for Efficient Monitoring of Diamondback Terrapins

2019 ◽  
Author(s):  
Patricia Levasseur ◽  
Sean Sterrett ◽  
Chris Sutherland
Keyword(s):  
Count Data ◽  
Hierarchical Modeling ◽  
Spatial Scales ◽  
Promising Method ◽  
Diamondback Terrapin ◽  
Imperfect Detection ◽  
Modeling Framework ◽  
Abundance Estimates ◽  
Diamondback Terrapins ◽  
And Behavior

Generating a range-wide population status of the diamondback terrapin (Malaclemys terrapin spp.) is challenging due to a combination of species ecology and behavior, and limitations associated with traditional sampling methods. Visual counting of emergent heads offers an efficient, non-invasive and promising method for generating abundance estimates of terrapin populations across broader spatial scales and can be used to explain spatial variation in population size. We conducted repeated visual head count surveys at 38 predetermined sites along the shoreline of Wellfleet Bay in Wellfleet, Massachusetts. We analyzed the count data using a hierarchical modeling framework designed specifically to analyze repeated count data: the so-called N-mixture model. This approach allows for simultaneous modeling of imperfect detection to generate estimates of true terrapin abundance. We found detection probability was lowest when skies were overcast and when wind speed was highest. Site specific abundance varied but we found that abundance estimates were, on average, higher in unexposed sites compared to exposed sites. We demonstrate the utility of pairing visual head counts and N-mixture models as an efficient method for estimating terrapin abundance and show how the approach can be used to identifying environmental factors that influence detectability and distribution.

An Information Modeling Framework to Support Design Databases and Repositories

1997 ◽  
Author(s):  
J. W. Murdock ◽  
Simon Szykman ◽  
Ram D. Sriram
Keyword(s):  
Object Oriented ◽  
Information Modeling ◽  
Modeling Language ◽  
Modeling Framework ◽  
Geometric Information ◽  
Support Design ◽  
Object Oriented Design ◽  
Power Drill ◽  
Design Databases ◽  
And Behavior

Abstract This paper introduces an information modeling framework to support representation of design artifacts for design databases and repositories. While most artifact representations consist primarily of geometric information, the object-oriented design modeling language developed through this work enables representation of not only form, but also function and behavior. This research has resulted in the implementation of a design artifact database as well as an information browser that provides the user interface to information contained therein. The implementation is demonstrated using the representation of a power drill as an example.

DEEP-SARSA: A REINFORCEMENT LEARNING ALGORITHM FOR AUTONOMOUS NAVIGATION

2001 ◽  
Vol 12 (10) ◽  
pp. 1513-1523 ◽  
Author(s):  
M. ANDRECUT ◽  
M. K. ALI
Keyword(s):  
Reinforcement Learning ◽  
Autonomous Navigation ◽  
Learning Algorithm ◽  
Robot Navigation ◽  
Learning Algorithms ◽  
Delayed Reinforcement ◽  
Graph Searching ◽  
Ill Posed ◽  
Autonomous Robot Navigation ◽  
Reinforcement Learning Algorithm

In this paper we discuss the application of reinforcement learning algorithms to the problem of autonomous robot navigation. We show that the autonomous navigation using the standard delayed reinforcement learning algorithms is an ill posed problem and we present a more efficient algorithm for which the convergence speed is greatly improved. The proposed algorithm (Deep-Sarsa) is based on a combination between the Depth-First Search (a graph searching algorithm) and Sarsa (a delayed reinforcement learning algorithm).

scholarly journals Six Lessons for a Cogent Science of Implicit Bias and Its Criticism

2019 ◽  
Vol 14 (4) ◽  
pp. 574-595 ◽  
Author(s):  
Bertram Gawronski
Keyword(s):  
Implicit Bias ◽  
Implicit Measures ◽  
Social Discrimination ◽  
Implicit Measurement ◽  
Implicit Biases ◽  
Explicit Bias ◽  
Current Article ◽  
Implicit And Explicit ◽  
And Behavior ◽  
Over Time

Skepticism about the explanatory value of implicit bias in understanding social discrimination has grown considerably. The current article argues that both the dominant narrative about implicit bias as well as extant criticism are based on a selective focus on particular findings that fails to consider the broader literature on attitudes and implicit measures. To provide a basis to move forward, the current article discusses six lessons for a cogent science of implicit bias: (a) There is no evidence that people are unaware of the mental contents underlying their implicit biases; (b) conceptual correspondence is essential for interpretations of dissociations between implicit and explicit bias; (c) there is no basis to expect strong unconditional relations between implicit bias and behavior; (d) implicit bias is less (not more) stable over time than explicit bias; (e) context matters fundamentally for the outcomes obtained with implicit-bias measures; and (f) implicit measurement scores do not provide process-pure reflections of bias. The six lessons provide guidance for research that aims to provide more compelling evidence for the properties of implicit bias. At the same time, they suggest that extant criticism does not justify the conclusion that implicit bias is irrelevant for the understanding of social discrimination.

scholarly journals Effects of a virtual gender swap on social and temporal decision-making

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Elena Bolt ◽  
Jasmine T. Ho ◽  
Marte Roel Lesur ◽  
Alexander Soutschek ◽  
Philippe N. Tobler ◽  
...  
Keyword(s):  
Decision Making ◽  
Virtual Reality ◽  
Biological Sex ◽  
Area Of Interest ◽  
Economic Decision Making ◽  
Intertemporal Discounting ◽  
Gender Based ◽  
Implicit And Explicit ◽  
Social Decision Making ◽  
And Behavior

AbstractMounting evidence has demonstrated that embodied virtual reality, during which physical bodies are replaced with virtual surrogates, can strongly alter cognition and behavior even when the virtual body radically differs from one’s own. One particular emergent area of interest is the investigation of how virtual gender swaps can influence choice behaviors. Economic decision-making paradigms have repeatedly shown that women tend to display more prosocial sharing choices than men. To examine whether a virtual gender swap can alter gender-specific differences in prosociality, 48 men and 51 women embodied either a same- or different-gender avatar in immersive virtual reality. In a between-subjects design, we differentiated between specifically social and non-social decision-making by means of a virtually administered interpersonal and intertemporal discounting task, respectively. We hypothesized that a virtual gender swap would elicit social behaviors that stereotypically align with the gender of the avatar. To relate potential effects to changes in self-perception, we also measured implicit and explicit identification with gendered (or gender-typical) traits prior to and following the virtual experience, and used questionnaires that assessed the strength of the illusion. Contrary to our hypothesis, our results show that participants made less prosocial decisions (i.e., became more selfish) in different-gender avatars, independent of their own biological sex. Moreover, women embodying a male avatar in particular were more sensitive to temptations of immediate rewards. Lastly, the manipulation had no effects on implicit and explicit identification with gendered traits. To conclude, while we showed that a virtual gender swap indeed alters decision-making, gender-based expectancies cannot account for all the task-specific interpersonal and intertemporal changes following the virtual gender swap.

scholarly journals Collision-Free Autonomous Robot Navigation in Unknown Environments Utilizing PSO for Path Planning

2019 ◽  
Vol 9 (4) ◽  
pp. 267-282 ◽  
Author(s):  
Evan Krell ◽  
Alaa Sheta ◽  
Arun Prassanth Ramaswamy Balasubramanian ◽  
Scott A. King
Keyword(s):  
Autonomous Navigation ◽  
Optimization Problem ◽  
Robot Navigation ◽  
Path Following ◽  
Autonomous Robot ◽  
Specific Task ◽  
Swarm Optimization ◽  
Unknown Environments ◽  
Autonomous Robot Navigation ◽  
Robot Path

Abstract The autonomous navigation of robots in unknown environments is a challenge since it needs the integration of a several subsystems to implement different functionality. It needs drawing a map of the environment, robot map localization, motion planning or path following, implementing the path in real-world, and many others; all have to be implemented simultaneously. Thus, the development of autonomous robot navigation (ARN) problem is essential for the growth of the robotics field of research. In this paper, we present a simulation of a swarm intelligence method is known as Particle Swarm Optimization (PSO) to develop an ARN system that can navigate in an unknown environment, reaching a pre-defined goal and become collision-free. The proposed system is built such that each subsystem manipulates a specific task which integrated to achieve the robot mission. PSO is used to optimize the robot path by providing several waypoints that minimize the robot traveling distance. The Gazebo simulator was used to test the response of the system under various envirvector representing a solution to the optimization problem.onmental conditions. The proposed ARN system maintained robust navigation and avoided the obstacles in different unknown environments. vector representing a solution to the optimization problem.

scholarly journals USING AN LOW-COST STEREO CAMERA FOR AUTONOMOUS NAVIGATION OF MOBILE ROBOT

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 423-427
Author(s):  
A. G. Chibunichev ◽  
A. P. Makarov ◽  
E. V. Poliakova
Keyword(s):  
Mobile Robot ◽  
Autonomous Navigation ◽  
Focal Length ◽  
Low Cost ◽  
Experimental Studies ◽  
Stereo Pair ◽  
Stereo Camera ◽  
First Case ◽  
Stereo Cameras ◽  
Autonomous Robot Navigation

Abstract. The paper considers the possibility of using low-cost stereo cameras for autonomous robot navigation. An low-cost stereo camera with a focal length of 5 mm and a photo base of 6 cm was chosen for the research. Experimental studies have shown that the accuracy of determining the coordinates of object points from a pair of images obtained by such a stereo camera is sufficient for organizing autonomous navigation of the robot. In order to improve the reliability and accuracy of determining the trajectory of the robot, this paper proposes to use two stereo cameras. One is directed forward by the robot's movement, and the other is directed at the nadir. Thus, the trajectory is determined twice, independently of each other. Moreover, each case has its own algorithm for finding the homologue points. In the first case, a sparse point cloud is constructed for each stereo pair based on the selection of interesting points and their identification based on the comparison of descriptors. In addition, blunder detection of points identification are realized based on the analysis of the values of the relative orientation equations using the fundamental matrix. In the second case, when the stereo camera is pointed at the nadir, the usual method of correlation is used in the nodes of the grid specified at one image. Experimental studies have shown sufficient efficiency of autonomous navigation of mobile robot based on the use of two stereo cameras.

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