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Robotics, Volume 5, Issue 4 (December 2016)

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Research

Open AccessArticle Towards Bio-Inspired Chromatic Behaviours in Surveillance Robots
Robotics 2016, 5(4), 20; doi:10.3390/robotics5040020
Received: 30 June 2016 / Revised: 21 September 2016 / Accepted: 26 September 2016 / Published: 29 September 2016
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Abstract
The field of Robotics is ever growing at the same time as posing enormous challenges. Numerous works has been done in biologically inspired robotics emulating models, systems and elements of nature for the purpose of solving traditional robotics problems. Chromatic behaviours are abundant
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The field of Robotics is ever growing at the same time as posing enormous challenges. Numerous works has been done in biologically inspired robotics emulating models, systems and elements of nature for the purpose of solving traditional robotics problems. Chromatic behaviours are abundant in nature across a variety of living species to achieve camouflage, signaling, and temperature regulation. The ability of these creatures to successfully blend in with their environment and communicate by changing their colour is the fundamental inspiration for our research work. In this paper, we present dwarf chameleon inspired chromatic behaviour in the context of an autonomous surveillance robot, “PACHONDHI”. In our experiments, we successfully validated the ability of the robot to autonomously change its colour in relation to the terrain that it is traversing for maximizing detectability to friendly security agents and minimizing exposure to hostile agents, as well as to communicate with fellow cooperating robots. Full article
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Open AccessArticle Towards an Explanation Generation System for Robots: Analysis and Recommendations
Robotics 2016, 5(4), 21; doi:10.3390/robotics5040021
Received: 10 May 2016 / Revised: 29 August 2016 / Accepted: 26 September 2016 / Published: 13 October 2016
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Abstract
A fundamental challenge in robotics is to reason with incomplete domain knowledge to explain unexpected observations and partial descriptions extracted from sensor observations. Existing explanation generation systems draw on ideas that can be mapped to a multidimensional space of system characteristics, defined by
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A fundamental challenge in robotics is to reason with incomplete domain knowledge to explain unexpected observations and partial descriptions extracted from sensor observations. Existing explanation generation systems draw on ideas that can be mapped to a multidimensional space of system characteristics, defined by distinctions, such as how they represent knowledge and if and how they reason with heuristic guidance. Instances in this multidimensional space corresponding to existing systems do not support all of the desired explanation generation capabilities for robots. We seek to address this limitation by thoroughly understanding the range of explanation generation capabilities and the interplay between the distinctions that characterize them. Towards this objective, this paper first specifies three fundamental distinctions that can be used to characterize many existing explanation generation systems. We explore and understand the effects of these distinctions by comparing the capabilities of two systems that differ substantially along these axes, using execution scenarios involving a robot waiter assisting in seating people and delivering orders in a restaurant. The second part of the paper uses this study to argue that the desired explanation generation capabilities corresponding to these three distinctions can mostly be achieved by exploiting the complementary strengths of the two systems that were explored. This is followed by a discussion of the capabilities related to other major distinctions to provide detailed recommendations for developing an explanation generation system for robots. Full article
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Open AccessArticle Deployment Environment for a Swarm of Heterogeneous Robots
Robotics 2016, 5(4), 22; doi:10.3390/robotics5040022
Received: 8 June 2016 / Revised: 10 September 2016 / Accepted: 26 September 2016 / Published: 26 October 2016
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Abstract
The objective of this work is to develop a framework that can deploy and provide coordination between multiple heterogeneous agents when a swarm robotic system adopts a decentralized approach; each robot evaluates its relative rank among the other robots in terms of travel
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The objective of this work is to develop a framework that can deploy and provide coordination between multiple heterogeneous agents when a swarm robotic system adopts a decentralized approach; each robot evaluates its relative rank among the other robots in terms of travel distance and cost to the goal. Accordingly, robots are allocated to the sub-tasks for which they have the highest rank (utility). This paper provides an analysis of existing swarm control environments and proposes a software environment that facilitates a rapid deployment of multiple robotic agents. The framework (UBSwarm) exploits our utility-based task allocation algorithm. UBSwarm configures these robots and assigns the group of robots a particular task from a set of available tasks. Two major tasks have been introduced that show the performance of a robotic group. This robotic group is composed of heterogeneous agents. In the results, a premature example that has prior knowledge about the experiment shows whether or not the robots are able to accomplish the task. Full article
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Open AccessArticle Auto-Calibration Methods of Kinematic Parameters and Magnetometer Offset for the Localization of a Tracked Mobile Robot
Robotics 2016, 5(4), 23; doi:10.3390/robotics5040023
Received: 5 August 2016 / Revised: 10 October 2016 / Accepted: 27 October 2016 / Published: 1 November 2016
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Abstract
This paper describes an automatic calibration procedure adopted to improve the localization of an outdoor mobile robot. The proposed algorithm estimates, by using an extended Kalman filter, the main kinematic parameters of the vehicles, such as the wheel radii and the wheelbase as
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This paper describes an automatic calibration procedure adopted to improve the localization of an outdoor mobile robot. The proposed algorithm estimates, by using an extended Kalman filter, the main kinematic parameters of the vehicles, such as the wheel radii and the wheelbase as well as the magnetometer offset. Several trials have been performed to validate the proposed strategy on a tracked electrical mobile robot. The mobile robot is aimed to be adopted as a tool to help humanitarian demining operations. Full article
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Open AccessArticle A Matlab-Based Testbed for Integration, Evaluation and Comparison of Heterogeneous Stereo Vision Matching Algorithms
Robotics 2016, 5(4), 24; doi:10.3390/robotics5040024
Received: 5 July 2016 / Revised: 31 October 2016 / Accepted: 4 November 2016 / Published: 9 November 2016
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Abstract
Stereo matching is a heavily researched area with a prolific published literature and a broad spectrum of heterogeneous algorithms available in diverse programming languages. This paper presents a Matlab-based testbed that aims to centralize and standardize this variety of both current and prospective
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Stereo matching is a heavily researched area with a prolific published literature and a broad spectrum of heterogeneous algorithms available in diverse programming languages. This paper presents a Matlab-based testbed that aims to centralize and standardize this variety of both current and prospective stereo matching approaches. The proposed testbed aims to facilitate the application of stereo-based methods to real situations. It allows for configuring and executing algorithms, as well as comparing results, in a fast, easy and friendly setting. Algorithms can be combined so that a series of processes can be chained and executed consecutively, using the output of a process as input for the next; some additional filtering and image processing techniques have been included within the testbed for this purpose. A use case is included to illustrate how these processes are sequenced and its effect on the results for real applications. The testbed has been conceived as a collaborative and incremental open-source project, where its code is accessible and modifiable, with the objective of receiving contributions and releasing future versions to include new algorithms and features. It is currently available online for the research community. Full article
(This article belongs to the Special Issue Robotics and 3D Vision)
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Open AccessArticle Improving Robot Mobility by Combining Downward-Looking and Frontal Cameras
Robotics 2016, 5(4), 25; doi:10.3390/robotics5040025
Received: 4 October 2016 / Revised: 9 November 2016 / Accepted: 15 November 2016 / Published: 28 November 2016
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Abstract
This paper presents a novel attempt to combine a downward-looking camera and a forward-looking camera for terrain classification in the field of off-road mobile robots. The first camera is employed to identify the terrain beneath the robot. This information is then used to
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This paper presents a novel attempt to combine a downward-looking camera and a forward-looking camera for terrain classification in the field of off-road mobile robots. The first camera is employed to identify the terrain beneath the robot. This information is then used to improve the classification of the forthcoming terrain acquired from the frontal camera. This research also shows the usefulness of the Gist descriptor for terrain classification purposes. Physical experiments conducted in different terrains (quasi-planar terrains) and different lighting conditions, confirm the satisfactory performance of this approach in comparison with a simple color-based classifier based only on frontal images. Our proposal substantially reduces the misclassification rate of the color-based classifier (∼10% versus ∼20%). Full article
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Open AccessArticle Complete Coverage Path Planning for a Multi-UAV Response System in Post-Earthquake Assessment
Robotics 2016, 5(4), 26; doi:10.3390/robotics5040026
Received: 10 October 2016 / Revised: 11 November 2016 / Accepted: 17 November 2016 / Published: 2 December 2016
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Abstract
This paper presents a post-earthquake response system for a rapid damage assessment. In this system, multiple Unmanned Aerial Vehicles (UAVs) are deployed to collect the images from the earthquake site and create a response map for extracting useful information. It is an extension
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This paper presents a post-earthquake response system for a rapid damage assessment. In this system, multiple Unmanned Aerial Vehicles (UAVs) are deployed to collect the images from the earthquake site and create a response map for extracting useful information. It is an extension of well-known coverage path problem (CPP) that is based on the grid pattern map decomposition. In addition to some linear strengthening techniques, two mathematic formulations, 4-index and 5-index models, are proposed in the approach and coded in GAMS (Cplex solver). They are tested on a number of problems and the results show that the 5-index model outperforms the 4-index model. Moreover, the proposed system could be significantly improved by the solver-generated cuts, additional constraints, and the variable branching priority extensions. Full article
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Open AccessArticle Terrain Perception in a Shape Shifting Rolling-Crawling Robot
Robotics 2016, 5(4), 19; doi:10.3390/robotics5040019
Received: 30 July 2016 / Revised: 26 August 2016 / Accepted: 2 September 2016 / Published: 27 September 2016
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Abstract
Terrain perception greatly enhances the performance of robots, providing them with essential information on the nature of terrain being traversed. Several living beings in nature offer interesting inspirations which adopt different gait patterns according to nature of terrain. In this paper, we present
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Terrain perception greatly enhances the performance of robots, providing them with essential information on the nature of terrain being traversed. Several living beings in nature offer interesting inspirations which adopt different gait patterns according to nature of terrain. In this paper, we present a novel terrain perception system for our bioinspired robot, Scorpio, to classify the terrain based on visual features and autonomously choose appropriate locomotion mode. Our Scorpio robot is capable of crawling and rolling locomotion modes, mimicking Cebrenus Rechenburgi, a member of the huntsman spider family. Our terrain perception system uses Speeded Up Robust Feature (SURF) description method along with color information. Feature extraction is followed by Bag of Word method (BoW) and Support Vector Machine (SVM) for terrain classification. Experiments were conducted with our Scorpio robot to establish the efficacy and validity of the proposed approach. In our experiments, we achieved a recognition accuracy of over 90% across four terrain types namely grass, gravel, wooden deck, and concrete. Full article
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