Pub Date : 2017-10-01DOI: 10.1109/IRIS.2017.8250154
Karthik Sivarama Krishnan, A. Saha, Srinath Ramachandran, Shitij Kumar
Gesture Recognition is the most recent development in the field of Bio Robotics. The proposed paper focuses on presenting a low cost sensor based human gesture recognition for the game of Hand Cricket. Hand cricket is a popular game in south Asian countries which involves the use of human finger gestures to score. This game is generally played between two players. Each player has a pre-defined gestures for the scores one, two, three, four and six. Both the players are made to wear the Myo armband. Myo armband is used to capture the Bio-potentials triggered during every muscle action. The various gestures performed in this game triggers various muscle group signals. A data set is created by collecting the eight channel bio potentials for every gesture made by both the players. The obtained data set is pre-processed and feature extracted. Now the Machine Learning techniques are performed in the data set to classify all the five different gestures with maximum accuracy. Support Vector Machine (SVM) gave the maximum accuracy to the classify the data set of both the players. The efficiency obtained for both the players are 92% and 84%. The proposed system is made to train with the data set obtained by the two players and the game is played in real time with the help of two MATLAB in two computers. Along with the classification of data, the scores of the individual player is calculated and displayed. With the scores being displayed, we can determine the player who scored the highest and the winner of the game can be determined.
{"title":"Recognition of human arm gestures using Myo armband for the game of hand cricket","authors":"Karthik Sivarama Krishnan, A. Saha, Srinath Ramachandran, Shitij Kumar","doi":"10.1109/IRIS.2017.8250154","DOIUrl":"https://doi.org/10.1109/IRIS.2017.8250154","url":null,"abstract":"Gesture Recognition is the most recent development in the field of Bio Robotics. The proposed paper focuses on presenting a low cost sensor based human gesture recognition for the game of Hand Cricket. Hand cricket is a popular game in south Asian countries which involves the use of human finger gestures to score. This game is generally played between two players. Each player has a pre-defined gestures for the scores one, two, three, four and six. Both the players are made to wear the Myo armband. Myo armband is used to capture the Bio-potentials triggered during every muscle action. The various gestures performed in this game triggers various muscle group signals. A data set is created by collecting the eight channel bio potentials for every gesture made by both the players. The obtained data set is pre-processed and feature extracted. Now the Machine Learning techniques are performed in the data set to classify all the five different gestures with maximum accuracy. Support Vector Machine (SVM) gave the maximum accuracy to the classify the data set of both the players. The efficiency obtained for both the players are 92% and 84%. The proposed system is made to train with the data set obtained by the two players and the game is played in real time with the help of two MATLAB in two computers. Along with the classification of data, the scores of the individual player is calculated and displayed. With the scores being displayed, we can determine the player who scored the highest and the winner of the game can be determined.","PeriodicalId":213724,"journal":{"name":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116864696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/IRIS.2017.8250129
T. Liu, Haisong Gu, Dongyan Wang
Home appliance manufacturing involves a lot of human operations due to variety of products and sizes, and lower cost requirements. Applying traditional inspection solutions to home appliances faces three challenging issues: 1)hard to handle different sizes of objects from big refrigerators to small kettles with fixed camera setting; 2)heavy engineering and tuning work for different inspection tasks; 3)high cost of stand-alone inspection system. This paper proposes a camera mounted robot solution with self-learning and edge/cloud visual inspection architecture. Firstly the 4 DoF robot arm with novel controlling strategy uses a single camera to handle variety of objects. For different inspection tasks, a machine learning based approach removes the complicated and tedious works for engineering and parameter tuning. Lastly, an edge/cloud computing framework puts limited tasks on cheap edge devices at manufacturing side and reduces the total cost.
{"title":"Visual inspection system for smart manufacture of home appliances","authors":"T. Liu, Haisong Gu, Dongyan Wang","doi":"10.1109/IRIS.2017.8250129","DOIUrl":"https://doi.org/10.1109/IRIS.2017.8250129","url":null,"abstract":"Home appliance manufacturing involves a lot of human operations due to variety of products and sizes, and lower cost requirements. Applying traditional inspection solutions to home appliances faces three challenging issues: 1)hard to handle different sizes of objects from big refrigerators to small kettles with fixed camera setting; 2)heavy engineering and tuning work for different inspection tasks; 3)high cost of stand-alone inspection system. This paper proposes a camera mounted robot solution with self-learning and edge/cloud visual inspection architecture. Firstly the 4 DoF robot arm with novel controlling strategy uses a single camera to handle variety of objects. For different inspection tasks, a machine learning based approach removes the complicated and tedious works for engineering and parameter tuning. Lastly, an edge/cloud computing framework puts limited tasks on cheap edge devices at manufacturing side and reduces the total cost.","PeriodicalId":213724,"journal":{"name":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114366660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/IRIS.2017.8250131
J. Gul, K. Kim, J. Lim, Y. Doh, K. Choi
The outstanding swim characteristics of the frog have inspired the development of artificial robotic swimmer, featuring synchronous swim capabilities, which could be of significant engineering interest in underwater applications. The Underwater synchronous swim is challenging because drag on the oars increases as the square of their speed. In frogs, as leg muscles shorten faster, the force capacity falls and drag force increases. In this paper, key features of frog's synchronous swim are reproduced by running 2D simulations which fully exploit the Fluid-Structure Interaction interface of COMSOL. Velocity, displacement, lift and drag forces in 2D space are studied. Unlike previous FSI underwater robotics studies in which much efforts are put on fluid dynamics, here muscles contraction is simulated by using the notion of pre-strain, emphasizing the kinematical role of muscle and the generation of movement. Based on these parameters, a soft frog robot embedded with shape memory alloy is fabricated using multilayer 3D printing technology. Flex Sensor encapsulated with Atomic Layer Deposition (ALD) is included in the limbs of soft frog robot to read the angle in real time. A proper synchronous movement of a frog-like body is reproduced by defining the pattern of muscles activation.
{"title":"FSI modeling of frog inspired soft robot embedded with ALD encapsulated flex sensor for underwater synchronous swim","authors":"J. Gul, K. Kim, J. Lim, Y. Doh, K. Choi","doi":"10.1109/IRIS.2017.8250131","DOIUrl":"https://doi.org/10.1109/IRIS.2017.8250131","url":null,"abstract":"The outstanding swim characteristics of the frog have inspired the development of artificial robotic swimmer, featuring synchronous swim capabilities, which could be of significant engineering interest in underwater applications. The Underwater synchronous swim is challenging because drag on the oars increases as the square of their speed. In frogs, as leg muscles shorten faster, the force capacity falls and drag force increases. In this paper, key features of frog's synchronous swim are reproduced by running 2D simulations which fully exploit the Fluid-Structure Interaction interface of COMSOL. Velocity, displacement, lift and drag forces in 2D space are studied. Unlike previous FSI underwater robotics studies in which much efforts are put on fluid dynamics, here muscles contraction is simulated by using the notion of pre-strain, emphasizing the kinematical role of muscle and the generation of movement. Based on these parameters, a soft frog robot embedded with shape memory alloy is fabricated using multilayer 3D printing technology. Flex Sensor encapsulated with Atomic Layer Deposition (ALD) is included in the limbs of soft frog robot to read the angle in real time. A proper synchronous movement of a frog-like body is reproduced by defining the pattern of muscles activation.","PeriodicalId":213724,"journal":{"name":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125412161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/IRIS.2017.8250134
R. French, Michalis Benakis, H. Marin-Reyes
Emerging through an industry-academia collaboration between the University of Sheffield and VBC Instrument Engineering Ltd, a proposed robotic solution for remanufacturing of jet engine compressor blades is under ongoing development, producing the first tangible results for evaluation. Having successfully overcome concept adaptation, funding mechanisms, design processes, with research and development trials, the stage of concept optimization and end-user application has commenced. A variety of new challenges is emerging, with multiple parameters requiring control and intelligence. An interlinked collaboration between operational controllers, Quality Assurance (QA) and Quality Control (QC) systems, databases, safety and monitoring systems, is creating a complex network, transforming the traditional manual re-manufacturing method to an advanced intelligent modern smart-factory. Incorporating machine vision systems for characterization, inspection and fault detection, alongside advanced real-time sensor data acquisition for monitoring and evaluating the welding process, a huge amount of valuable industrial data is produced. Information regarding each individual blade is combined with data acquired from the system, embedding data analytics and the concept of “Internet of Things” (IoT) into the aerospace re-manufacturing industry. The aim of this paper is to give a first insight into the challenges of the development of an Industry 4.0 prototype system and an evaluation of first results of the operational prototype.
{"title":"Intelligent sensing for robotic re-manufacturing in aerospace — An industry 4.0 design based prototype","authors":"R. French, Michalis Benakis, H. Marin-Reyes","doi":"10.1109/IRIS.2017.8250134","DOIUrl":"https://doi.org/10.1109/IRIS.2017.8250134","url":null,"abstract":"Emerging through an industry-academia collaboration between the University of Sheffield and VBC Instrument Engineering Ltd, a proposed robotic solution for remanufacturing of jet engine compressor blades is under ongoing development, producing the first tangible results for evaluation. Having successfully overcome concept adaptation, funding mechanisms, design processes, with research and development trials, the stage of concept optimization and end-user application has commenced. A variety of new challenges is emerging, with multiple parameters requiring control and intelligence. An interlinked collaboration between operational controllers, Quality Assurance (QA) and Quality Control (QC) systems, databases, safety and monitoring systems, is creating a complex network, transforming the traditional manual re-manufacturing method to an advanced intelligent modern smart-factory. Incorporating machine vision systems for characterization, inspection and fault detection, alongside advanced real-time sensor data acquisition for monitoring and evaluating the welding process, a huge amount of valuable industrial data is produced. Information regarding each individual blade is combined with data acquired from the system, embedding data analytics and the concept of “Internet of Things” (IoT) into the aerospace re-manufacturing industry. The aim of this paper is to give a first insight into the challenges of the development of an Industry 4.0 prototype system and an evaluation of first results of the operational prototype.","PeriodicalId":213724,"journal":{"name":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134555291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/IRIS.2017.8250120
Mustafa A. Ghazi, David P. Miller
We propose a performance model for a monocular vision-based motion capture system. Such a system can use uniquely patterned augmented reality (AR) markers worn on the body. Two key factors in evaluating such a system are tracking accuracy and blurring effects. Past work involving AR markers has emphasized other factors such as detection rate or pixel error. In cases where accuracy has been studied, it has been done only for specific systems. In contrast, our model is more general and can accommodate different types of cameras and marker sizes. Our model can also simulate a marker worn on a moving limb. Preliminary experiments show that our model has the potential to accurately predict real-world performance.
{"title":"Monocular vision-based motion capture system: A performance model","authors":"Mustafa A. Ghazi, David P. Miller","doi":"10.1109/IRIS.2017.8250120","DOIUrl":"https://doi.org/10.1109/IRIS.2017.8250120","url":null,"abstract":"We propose a performance model for a monocular vision-based motion capture system. Such a system can use uniquely patterned augmented reality (AR) markers worn on the body. Two key factors in evaluating such a system are tracking accuracy and blurring effects. Past work involving AR markers has emphasized other factors such as detection rate or pixel error. In cases where accuracy has been studied, it has been done only for specific systems. In contrast, our model is more general and can accommodate different types of cameras and marker sizes. Our model can also simulate a marker worn on a moving limb. Preliminary experiments show that our model has the potential to accurately predict real-world performance.","PeriodicalId":213724,"journal":{"name":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134620083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/IRIS.2017.8250152
Rugayah Hashim, H. Yussof
In caring for special needs children, for example, those with autism, there should be alternatives for the parents and guardians of these children. In this instance, aside from fellow humans, care robots should be considered. Therefore, this review paper synthesizes the results from several primary literature on the feasibility of using robots to care for children with special needs. Digesting and summarizing on the literature reviewed within this scope, it is not currently feasible for robots to care for children much so for those with special needs. More concrete evidences are required for parents and guardians to put faith in a machine as a replacement for a human care giver.
{"title":"Feasibility of care robots for children with special needs: A review","authors":"Rugayah Hashim, H. Yussof","doi":"10.1109/IRIS.2017.8250152","DOIUrl":"https://doi.org/10.1109/IRIS.2017.8250152","url":null,"abstract":"In caring for special needs children, for example, those with autism, there should be alternatives for the parents and guardians of these children. In this instance, aside from fellow humans, care robots should be considered. Therefore, this review paper synthesizes the results from several primary literature on the feasibility of using robots to care for children with special needs. Digesting and summarizing on the literature reviewed within this scope, it is not currently feasible for robots to care for children much so for those with special needs. More concrete evidences are required for parents and guardians to put faith in a machine as a replacement for a human care giver.","PeriodicalId":213724,"journal":{"name":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134393779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/IRIS.2017.8250122
F. Alaieri, André Vellino
Autonomous bots and robots (we label “(ro)bots”), ranging from shopping assistant chatbots to self-driving cars are already able to make decisions that have ethical consequences. As more such machines make increasingly complex and significant decisions, we need to know that their decisions are trustworthy and ethically justified so that users, manufacturers and lawmakers can understand how these decisions are made and which ethical principles were brought to bear in making them. Understanding how such decisions are made is particularly important in the case where a (ro)bot is a self-improving, selflearning type of machine whose choices and decisions are based on past experience, given that they may not be entirely predictable ahead of time or explainable after the fact. This paper presents a model that decomposes the stages of ethical decision making into their elementary components with a view to enabling stakeholders to allocate the responsibility for such choices.
{"title":"A decision making model for ethical (ro)bots","authors":"F. Alaieri, André Vellino","doi":"10.1109/IRIS.2017.8250122","DOIUrl":"https://doi.org/10.1109/IRIS.2017.8250122","url":null,"abstract":"Autonomous bots and robots (we label “(ro)bots”), ranging from shopping assistant chatbots to self-driving cars are already able to make decisions that have ethical consequences. As more such machines make increasingly complex and significant decisions, we need to know that their decisions are trustworthy and ethically justified so that users, manufacturers and lawmakers can understand how these decisions are made and which ethical principles were brought to bear in making them. Understanding how such decisions are made is particularly important in the case where a (ro)bot is a self-improving, selflearning type of machine whose choices and decisions are based on past experience, given that they may not be entirely predictable ahead of time or explainable after the fact. This paper presents a model that decomposes the stages of ethical decision making into their elementary components with a view to enabling stakeholders to allocate the responsibility for such choices.","PeriodicalId":213724,"journal":{"name":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","volume":"36 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132365557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/IRIS.2017.8250145
Jonqlan Lin, C. Y. Wu, Julian Chang
In this work, a multi-degrees-of-freedom (MDOF) cable-suspended robot that can perform pick-up-and-place tasks in large workspaces with weighty loads is designed. The proposed cable-suspended parallel robot comprises a rigid frame and an end-effector that is suspended from eight cables — four upper cables and four lower cables. The lengths of the cables are computed from the given positions of the suspended end-effector using a kinematic model. However, most multicable-driven robots struggle with interference among the cables, requiring a complicated control methodology to find a target goal. Owing to this issue with cable-driven parallel robots, the whole control structure decomposes positioning control missions and allocates them into upper- and lower- level. The upper-control is responsible for tracking the suspended endeffector to the target region. The lower-level control makes fine positional modifications. Experimental results demonstrate that the hybrid control mode significantly improves positioning performance. The broad variety of issues that are presented in this work apply to aerostats, towing cranes, locomotion interfaces, and large-scale manufacturing that require cable- suspended parallel robots.
{"title":"Implementation and control for an MDOF cable-suspended parallel robot","authors":"Jonqlan Lin, C. Y. Wu, Julian Chang","doi":"10.1109/IRIS.2017.8250145","DOIUrl":"https://doi.org/10.1109/IRIS.2017.8250145","url":null,"abstract":"In this work, a multi-degrees-of-freedom (MDOF) cable-suspended robot that can perform pick-up-and-place tasks in large workspaces with weighty loads is designed. The proposed cable-suspended parallel robot comprises a rigid frame and an end-effector that is suspended from eight cables — four upper cables and four lower cables. The lengths of the cables are computed from the given positions of the suspended end-effector using a kinematic model. However, most multicable-driven robots struggle with interference among the cables, requiring a complicated control methodology to find a target goal. Owing to this issue with cable-driven parallel robots, the whole control structure decomposes positioning control missions and allocates them into upper- and lower- level. The upper-control is responsible for tracking the suspended endeffector to the target region. The lower-level control makes fine positional modifications. Experimental results demonstrate that the hybrid control mode significantly improves positioning performance. The broad variety of issues that are presented in this work apply to aerostats, towing cranes, locomotion interfaces, and large-scale manufacturing that require cable- suspended parallel robots.","PeriodicalId":213724,"journal":{"name":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132518169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/IRIS.2017.8250146
B. Stanciulescu, Romain Ceolato Onera, C. Nicodeme, Saïd el Fassi
The transport industry is subject to a lot of improvement aiming to autonomous transportation systems. Railway is also concerned. An autonomous vehicle must be able to perceive and analyze its environment with a view to being able to adapt its driving. In this paper we focus on the wheel-rail contact analysis, and the adherence evaluation, as it conditions loads of variables such as braking, traction and maximum speed. It also has an impact on security distance between trains. Adherence can be degraded by the presence of pollution on the rail surface. We present an imaging system, using a multispectral camera, capable of detecting and recognizing pollutant. The pollution is then associated to an adherence coefficient.
{"title":"Wheel-rail contact analysis system using spectral signatures for train automation and traffic management","authors":"B. Stanciulescu, Romain Ceolato Onera, C. Nicodeme, Saïd el Fassi","doi":"10.1109/IRIS.2017.8250146","DOIUrl":"https://doi.org/10.1109/IRIS.2017.8250146","url":null,"abstract":"The transport industry is subject to a lot of improvement aiming to autonomous transportation systems. Railway is also concerned. An autonomous vehicle must be able to perceive and analyze its environment with a view to being able to adapt its driving. In this paper we focus on the wheel-rail contact analysis, and the adherence evaluation, as it conditions loads of variables such as braking, traction and maximum speed. It also has an impact on security distance between trains. Adherence can be degraded by the presence of pollution on the rail surface. We present an imaging system, using a multispectral camera, capable of detecting and recognizing pollutant. The pollution is then associated to an adherence coefficient.","PeriodicalId":213724,"journal":{"name":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132363350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/IRIS.2017.8250091
Helen Harman, Keshav Chintamani, P. Simoens
Robots are being deployed in a wide range of smart environments that are equipped with sensors and actuators. These devices can provide valuable information beyond the perception range of a robot's on-board sensors, or provide additional actuators that can complement the robot's actuation abilities. Traditional robot task planners do not take these additional sensor and actuators abilities into account. This paper introduces an enhanced robotic planning framework which improves robots' ability to operate in dynamically changing environments. To keep planning time short, the amount of knowledge in the planner's world model is minimized.
{"title":"Architecture for incorporating Internet-of-Things sensors and actuators into robot task planning in dynamic environments","authors":"Helen Harman, Keshav Chintamani, P. Simoens","doi":"10.1109/IRIS.2017.8250091","DOIUrl":"https://doi.org/10.1109/IRIS.2017.8250091","url":null,"abstract":"Robots are being deployed in a wide range of smart environments that are equipped with sensors and actuators. These devices can provide valuable information beyond the perception range of a robot's on-board sensors, or provide additional actuators that can complement the robot's actuation abilities. Traditional robot task planners do not take these additional sensor and actuators abilities into account. This paper introduces an enhanced robotic planning framework which improves robots' ability to operate in dynamically changing environments. To keep planning time short, the amount of knowledge in the planner's world model is minimized.","PeriodicalId":213724,"journal":{"name":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126167550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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