We propose an active learning architecture for robots, capable of organizing its learning process to achieve a field of complex tasks by learning sequences of motor policies, called Intrinsically Motivated Procedure Babbling (IM-PB). The learner can generalize over its experience to continuously learn new tasks. It chooses actively what and how to learn based by empirical measures of its own progress. In this paper, we are considering the learning of a set of interrelated tasks outcomes hierarchically organized. We introduce a framework called ""procedures", which are sequences of policies defined by the combination of previously learned skills. Our algorithmic architecture uses the procedures to autonomously discover how to combine simple skills to achieve complex goals. It actively chooses between 2 strategies of goal-directed exploration: exploration of the policy space or the procedural space. We show on a simulated environment that our new architecture is capable of tackling the learning of complex motor policies, to adapt the complexity of its policies to the task at hand. We also show that our ""procedures"" framework helps the learner to tackle difficult hierarchical tasks.
{"title":"Learning a Set of Interrelated Tasks by Using Sequences of Motor Policies for a Strategic Intrinsically Motivated Learner","authors":"Nicolas Duminy, S. Nguyen, D. Duhaut","doi":"10.1109/IRC.2018.00061","DOIUrl":"https://doi.org/10.1109/IRC.2018.00061","url":null,"abstract":"We propose an active learning architecture for robots, capable of organizing its learning process to achieve a field of complex tasks by learning sequences of motor policies, called Intrinsically Motivated Procedure Babbling (IM-PB). The learner can generalize over its experience to continuously learn new tasks. It chooses actively what and how to learn based by empirical measures of its own progress. In this paper, we are considering the learning of a set of interrelated tasks outcomes hierarchically organized. We introduce a framework called \"\"procedures\", which are sequences of policies defined by the combination of previously learned skills. Our algorithmic architecture uses the procedures to autonomously discover how to combine simple skills to achieve complex goals. It actively chooses between 2 strategies of goal-directed exploration: exploration of the policy space or the procedural space. We show on a simulated environment that our new architecture is capable of tackling the learning of complex motor policies, to adapt the complexity of its policies to the task at hand. We also show that our \"\"procedures\"\" framework helps the learner to tackle difficult hierarchical tasks.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123741921","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}
Robots are given more and more challenging tasks in domains such as transport and delivery, farming or health. Software is key components for robots, and ROS is a popular open-source middleware for writing robotics applications. Code quality matters a lot because a poorly written software is much more likely to contain bugs and will be harder to maintain over time. Within a code base, finding faulty patterns takes a lot of time and money. We propose a framework to search automatically user-provided faulty code patterns. This framework is based on FO++, a temporal extension of first-order logic, and Pangolin, a verification engine for C++ programs. We formalized with FO++ five faulty patterns related to ROS and embedded systems. We analyzed with Pangolin 25 ROS packages looking for occurrences of these patterns and found a total of 218 defects. To prevent the faulty patterns from arising in new ROS packages, we propose a design pattern, and we show how Pangolin can be used to enforce it.
{"title":"Improving Code Quality in ROS Packages Using a Temporal Extension of First-Order Logic","authors":"D. Come, Julien Brunel, D. Doose","doi":"10.1109/IRC.2018.00010","DOIUrl":"https://doi.org/10.1109/IRC.2018.00010","url":null,"abstract":"Robots are given more and more challenging tasks in domains such as transport and delivery, farming or health. Software is key components for robots, and ROS is a popular open-source middleware for writing robotics applications. Code quality matters a lot because a poorly written software is much more likely to contain bugs and will be harder to maintain over time. Within a code base, finding faulty patterns takes a lot of time and money. We propose a framework to search automatically user-provided faulty code patterns. This framework is based on FO++, a temporal extension of first-order logic, and Pangolin, a verification engine for C++ programs. We formalized with FO++ five faulty patterns related to ROS and embedded systems. We analyzed with Pangolin 25 ROS packages looking for occurrences of these patterns and found a total of 218 defects. To prevent the faulty patterns from arising in new ROS packages, we propose a design pattern, and we show how Pangolin can be used to enforce it.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114148954","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}
Although mereotopological relationship theories and their qualification problems have been extensively studied in R^2, the qualification of mereotopological relations in R^3 remains challenging. This is due to the limited availability of topological operators and high costs of boundary intersection tests. In this paper, a novel qualification technique for mereotopological relations in R^3 is presented. Our technique rapidly computes RCC-8 base relations using precomputed signed distance fields, and makes no assumptions with regards to complexity or representation method of the spatial entities under consideration.
{"title":"Rapid Qualification of Mereotopological Relationships Using Signed Distance Fields","authors":"R. Schubotz, Christian Vogelgesang, D. Rubinstein","doi":"10.1109/IRC.2018.00031","DOIUrl":"https://doi.org/10.1109/IRC.2018.00031","url":null,"abstract":"Although mereotopological relationship theories and their qualification problems have been extensively studied in R^2, the qualification of mereotopological relations in R^3 remains challenging. This is due to the limited availability of topological operators and high costs of boundary intersection tests. In this paper, a novel qualification technique for mereotopological relations in R^3 is presented. Our technique rapidly computes RCC-8 base relations using precomputed signed distance fields, and makes no assumptions with regards to complexity or representation method of the spatial entities under consideration.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130470427","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}
Dinh-Khanh Ho, K. B. Chehida, Benoît Miramond, M. Auguin
An increasing demand on the autonomy of mobile robotic platforms requires adaptive on-line decisions reacting to the dynamic and unpredictable working environment with respect to the robotic mission requirements. These decisions are constrained by the limited computing resources and the energy that the mobile robot can carry. Moreover, in a multi-mission robotic context, these decisions must ensure a minimal quality of service (QoS) for each mission. This decision making problem leverages a characterization and monitoring phase of the system (computing and energy) resources and the robotic missions. In this article, we characterize, monitor and analyze our mobile robotic platform and an autonomous navigation mission as the principal mission of a mobile robot. The results of real experimentations on our robotic platform are analyzed and they highlight the necessity for an efficient mission manager.
{"title":"Towards a Multi-mission QoS and Energy Manager for Autonomous Mobile Robots","authors":"Dinh-Khanh Ho, K. B. Chehida, Benoît Miramond, M. Auguin","doi":"10.1109/IRC.2018.00057","DOIUrl":"https://doi.org/10.1109/IRC.2018.00057","url":null,"abstract":"An increasing demand on the autonomy of mobile robotic platforms requires adaptive on-line decisions reacting to the dynamic and unpredictable working environment with respect to the robotic mission requirements. These decisions are constrained by the limited computing resources and the energy that the mobile robot can carry. Moreover, in a multi-mission robotic context, these decisions must ensure a minimal quality of service (QoS) for each mission. This decision making problem leverages a characterization and monitoring phase of the system (computing and energy) resources and the robotic missions. In this article, we characterize, monitor and analyze our mobile robotic platform and an autonomous navigation mission as the principal mission of a mobile robot. The results of real experimentations on our robotic platform are analyzed and they highlight the necessity for an efficient mission manager.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130873663","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}
Preetham Chalasani, A. Deguet, P. Kazanzides, R. Taylor
Robotic surgical systems have contributed greatly to the advancement of minimally invasive surgery (MIS). More specifically, telesurgical robots have provided enhanced dexterity to surgeons performing MIS procedures. However, current robotic teleoperated systems have only limited situational awareness of the patient anatomy and surgical environment that would typically be available to a surgeon in an open surgery. Although the endoscopic view enhances the visualization of the anatomy, perceptual understanding of the environment and anatomy is still lacking due to the absence of sensory feedback. To address these limitations, we present an algorithmic software framework to provide Complementary Situational Awareness (CSA) in a surgical assistant. This framework aims at improving the human-robot relationship by providing elaborate guidance and sensory feedback capabilities for the surgeon in complex MIS procedures. Unlike traditional teleoperation, this framework enables the user to telemanipulate the situational model in a virtual environment and uses that information to command the slave robot with appropriate admittance gains and environmental constraints. Simultaneously, the situational model is updated based on interaction of the slave robot with the task space environment. We provide various high-level and mid-level components to provide CSA and illustrate the necessary capabilities required for any robotic platform to readily incorporate CSA. We also demonstrate the use of our framework for constrained model-mediated teleoperation using the open-source da Vinci Research Kit (dVRK) hardware.
{"title":"A Computational Framework for Complementary Situational Awareness (CSA) in Surgical Assistant Robots","authors":"Preetham Chalasani, A. Deguet, P. Kazanzides, R. Taylor","doi":"10.1109/IRC.2018.00011","DOIUrl":"https://doi.org/10.1109/IRC.2018.00011","url":null,"abstract":"Robotic surgical systems have contributed greatly to the advancement of minimally invasive surgery (MIS). More specifically, telesurgical robots have provided enhanced dexterity to surgeons performing MIS procedures. However, current robotic teleoperated systems have only limited situational awareness of the patient anatomy and surgical environment that would typically be available to a surgeon in an open surgery. Although the endoscopic view enhances the visualization of the anatomy, perceptual understanding of the environment and anatomy is still lacking due to the absence of sensory feedback. To address these limitations, we present an algorithmic software framework to provide Complementary Situational Awareness (CSA) in a surgical assistant. This framework aims at improving the human-robot relationship by providing elaborate guidance and sensory feedback capabilities for the surgeon in complex MIS procedures. Unlike traditional teleoperation, this framework enables the user to telemanipulate the situational model in a virtual environment and uses that information to command the slave robot with appropriate admittance gains and environmental constraints. Simultaneously, the situational model is updated based on interaction of the slave robot with the task space environment. We provide various high-level and mid-level components to provide CSA and illustrate the necessary capabilities required for any robotic platform to readily incorporate CSA. We also demonstrate the use of our framework for constrained model-mediated teleoperation using the open-source da Vinci Research Kit (dVRK) hardware.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127336960","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}
Robotic materials are multi-robot systems formulated to leverage the low-order computation and actuation of the constituents to manipulate the high-order behavior of the entire material. We study the behaviors of ensembles composed of smart active particles, smarticles. Smarticles are small, low cost robots equipped with basic actuation and sensing abilities that are individually incapable of rotating or displacing. We demonstrate that a "supersmarticle", composed of many smarticles constrained within a bounding membrane, can harness the internal collisions of the robotic material among the constituents and the membrane to achieve diffusive locomotion. The emergent diffusion can be directed by modulating the robotic material properties in response to a light source, analogous to biological phototaxis. The light source introduces asymmetries within the robotic material, resulting in modified populations of interaction modes and dynamics which ultimately result in supersmarticle biased locomotion. We present experimental methods and results for the robotic material which moves with a directed displacement in response to a light source.
{"title":"Locomoting Robots Composed of Immobile Robots","authors":"Ross Warkentin, W. Savoie, D. Goldman","doi":"10.1109/IRC.2018.00047","DOIUrl":"https://doi.org/10.1109/IRC.2018.00047","url":null,"abstract":"Robotic materials are multi-robot systems formulated to leverage the low-order computation and actuation of the constituents to manipulate the high-order behavior of the entire material. We study the behaviors of ensembles composed of smart active particles, smarticles. Smarticles are small, low cost robots equipped with basic actuation and sensing abilities that are individually incapable of rotating or displacing. We demonstrate that a \"supersmarticle\", composed of many smarticles constrained within a bounding membrane, can harness the internal collisions of the robotic material among the constituents and the membrane to achieve diffusive locomotion. The emergent diffusion can be directed by modulating the robotic material properties in response to a light source, analogous to biological phototaxis. The light source introduces asymmetries within the robotic material, resulting in modified populations of interaction modes and dynamics which ultimately result in supersmarticle biased locomotion. We present experimental methods and results for the robotic material which moves with a directed displacement in response to a light source.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116288382","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}
Autonomous mobile robots must be equipped with appropriate planification and control navigation systems in order to obtain robust behaviours. This study aims at dealing with this kind of problems when implementing on a two wheeled mobile robot. The planning navigation system uses our previously proposed reliable and safe navigation planning algorithm based on the incremental sampling-based planning algorithm, e.g., the widely-used Rapidly-exploring Random Tree (RRT), while the control navigation level consists in a go to goal controller strategy. Through experiments, we demonstrate the usefulness of robust navigation planner in an autonomous navigation schemes, where uncertain localization has to be taken into account.
自主移动机器人必须配备适当的平面化和控制导航系统，才能获得鲁棒性行为。本研究的目的是在两轮移动机器人上实现这类问题。规划导航系统采用我们之前提出的基于增量采样规划算法的可靠安全的导航规划算法，如广泛使用的快速探索随机树(rapid - explore Random Tree, RRT)，而控制导航层则采用go - to - goal控制器策略。通过实验，我们证明了鲁棒导航规划器在自主导航方案中的实用性，其中必须考虑不确定的定位。
{"title":"Reliable Navigation Planning Implementation on a Two-Wheeled Mobile Robot","authors":"Élise Crepon, A. Panchea, Alexandre Chapoutot","doi":"10.1109/IRC.2018.00035","DOIUrl":"https://doi.org/10.1109/IRC.2018.00035","url":null,"abstract":"Autonomous mobile robots must be equipped with appropriate planification and control navigation systems in order to obtain robust behaviours. This study aims at dealing with this kind of problems when implementing on a two wheeled mobile robot. The planning navigation system uses our previously proposed reliable and safe navigation planning algorithm based on the incremental sampling-based planning algorithm, e.g., the widely-used Rapidly-exploring Random Tree (RRT), while the control navigation level consists in a go to goal controller strategy. Through experiments, we demonstrate the usefulness of robust navigation planner in an autonomous navigation schemes, where uncertain localization has to be taken into account.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124225043","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}
P. Papadakis, Christopher Lohr, Marin Lujak, Abir-Beatrice Karami, I. Kanellos, G. Lozenguez, A. Fleury
In this work, we set the bases of the integration of ambient intelligence (AmI) with mobile robot teams (MRT), aiming to enhance ambient assisted living services addressing a variety of tasks. We argue that people with reduced mobility can benefit from a synergy between AmI and MRT in various aspects. Towards this direction, we identify principal functionalities such an integrated system should provide in connection to relevant previous works and the way by which synergy could be accomplished, from low-level behavioural to higher-level task planning of a multi-layered system architecture.
{"title":"System Design for Coordinated Multi-robot Assistance Deployment in Smart Spaces","authors":"P. Papadakis, Christopher Lohr, Marin Lujak, Abir-Beatrice Karami, I. Kanellos, G. Lozenguez, A. Fleury","doi":"10.1109/IRC.2018.00068","DOIUrl":"https://doi.org/10.1109/IRC.2018.00068","url":null,"abstract":"In this work, we set the bases of the integration of ambient intelligence (AmI) with mobile robot teams (MRT), aiming to enhance ambient assisted living services addressing a variety of tasks. We argue that people with reduced mobility can benefit from a synergy between AmI and MRT in various aspects. Towards this direction, we identify principal functionalities such an integrated system should provide in connection to relevant previous works and the way by which synergy could be accomplished, from low-level behavioural to higher-level task planning of a multi-layered system architecture.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129576393","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}
M. Devanne, S. Nguyen, O. Rémy-Néris, Beatrice Le Gales-Garnett, G. Kermarrec, A. Thépaut
The rising number of the elderly incurs growing concern about healthcare, and in particular rehabilitation healthcare. Assistive technology and assistive robotics in particular may help to improve this process. We develop a robot coach capable of demonstrating rehabilitation exercises to patients, watch a patient carry out the exercises and give him feedback so as to improve his performance and encourage him. The HRI of the system is based on our study with a team of rehabilitation therapists and with the target population. The system relies on human motion analysis. We develop a method for learning a probabilistic representation of ideal movements from expert demonstrations. A Gaussian Mixture Model is employed from position and orientation features captured using a Microsoft Kinect v2. For assessing patients' movements, we propose a real-time multi-level analysis to both temporally and spatially identify and explain body part errors. This analysis combined with a classification algorithm allows the robot to provide coaching advice to make the patient improve his movements. The evaluation on three rehabilitation exercises shows the potential of the proposed approach for learning and assessing kinaesthetic movements.
{"title":"A Co-design Approach for a Rehabilitation Robot Coach for Physical Rehabilitation Based on the Error Classification of Motion Errors","authors":"M. Devanne, S. Nguyen, O. Rémy-Néris, Beatrice Le Gales-Garnett, G. Kermarrec, A. Thépaut","doi":"10.1109/IRC.2018.00074","DOIUrl":"https://doi.org/10.1109/IRC.2018.00074","url":null,"abstract":"The rising number of the elderly incurs growing concern about healthcare, and in particular rehabilitation healthcare. Assistive technology and assistive robotics in particular may help to improve this process. We develop a robot coach capable of demonstrating rehabilitation exercises to patients, watch a patient carry out the exercises and give him feedback so as to improve his performance and encourage him. The HRI of the system is based on our study with a team of rehabilitation therapists and with the target population. The system relies on human motion analysis. We develop a method for learning a probabilistic representation of ideal movements from expert demonstrations. A Gaussian Mixture Model is employed from position and orientation features captured using a Microsoft Kinect v2. For assessing patients' movements, we propose a real-time multi-level analysis to both temporally and spatially identify and explain body part errors. This analysis combined with a classification algorithm allows the robot to provide coaching advice to make the patient improve his movements. The evaluation on three rehabilitation exercises shows the potential of the proposed approach for learning and assessing kinaesthetic movements.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133056542","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}
Autonomous mobile robots need to be equipped with appropriate planification and control navigation systems in order to obtain safe behaviours. This study aims at implementing on a two wheeled mobile robot a robust autonomous navigation planning algorithm, which guarantees a safe and reliable path. By making use of all facilities which the robot operating system (ROS) middleware and the open motion planning library (OMPL) can offer, we implement on a mobile robot platform an autonomous architecture adapted to our problem. The planning navigation system makes use of the widely-used Rapidly-exploring Random Tree (RRT) algorithm, while the control navigation level is based on the go-to-goal strategy. As a novelty, our previously proposed reliable and safe navigation planning algorithm based on RRT principles and solved in an interval analysis framework, e.g., BoxRRT, is tested on a mobile robot platform. Through experiments, the interest of using such a robust navigation planner on an autonomous navigation architecture with uncertain localization is presented.
{"title":"Reliable Motion Plannning for a Mobile Robot","authors":"Élise Crepon, A. Panchea, Alexandre Chapoutot","doi":"10.1109/IRC.2018.00085","DOIUrl":"https://doi.org/10.1109/IRC.2018.00085","url":null,"abstract":"Autonomous mobile robots need to be equipped with appropriate planification and control navigation systems in order to obtain safe behaviours. This study aims at implementing on a two wheeled mobile robot a robust autonomous navigation planning algorithm, which guarantees a safe and reliable path. By making use of all facilities which the robot operating system (ROS) middleware and the open motion planning library (OMPL) can offer, we implement on a mobile robot platform an autonomous architecture adapted to our problem. The planning navigation system makes use of the widely-used Rapidly-exploring Random Tree (RRT) algorithm, while the control navigation level is based on the go-to-goal strategy. As a novelty, our previously proposed reliable and safe navigation planning algorithm based on RRT principles and solved in an interval analysis framework, e.g., BoxRRT, is tested on a mobile robot platform. Through experiments, the interest of using such a robust navigation planner on an autonomous navigation architecture with uncertain localization is presented.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128090105","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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