Pub Date : 2016-10-01DOI: 10.1109/IROS.2016.7759360
F. Vanegas, D. Campbell, M. Eich, Felipe Gonzalez
In this paper we describe and flight test a novel system architecture for low cost muti-rotor unmanned aerial vehicles (UAVs) for searching, tracking and following a ground target. The UAV uses only on-board sensors for localisation within a GPS-denied space with obstacles. This mission is formulated as a Partially Observable Markov Decision Process (POMDP) and uses a modular framework that runs on the Robotic Operating System (ROS). This system computes a policy for executing actions instead of way-points to navigate and avoid obstacles. Results indicate that the system is robust to overcome uncertainties in localisation of both, the aircraft and the target and avoids collisions with the obstacles.
{"title":"UAV based target finding and tracking in GPS-denied and cluttered environments","authors":"F. Vanegas, D. Campbell, M. Eich, Felipe Gonzalez","doi":"10.1109/IROS.2016.7759360","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759360","url":null,"abstract":"In this paper we describe and flight test a novel system architecture for low cost muti-rotor unmanned aerial vehicles (UAVs) for searching, tracking and following a ground target. The UAV uses only on-board sensors for localisation within a GPS-denied space with obstacles. This mission is formulated as a Partially Observable Markov Decision Process (POMDP) and uses a modular framework that runs on the Robotic Operating System (ROS). This system computes a policy for executing actions instead of way-points to navigate and avoid obstacles. Results indicate that the system is robust to overcome uncertainties in localisation of both, the aircraft and the target and avoids collisions with the obstacles.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"169 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123103035","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 : 2016-10-01DOI: 10.1109/IROS.2016.7759399
S. Park, W. Chung
Microneedle insertion is useful for elucidating the processes in living cells and their organelles. However, mechanical puncture by the needle causes traumatic damage to the cell. As a less invasive process, we have developed intracellular needle insertion using femtosecond laser cell ablation. To quickly and precisely position the spot ablated by the laser, we accurately located the needle tip in a 2D image plane. When the needle approaches the cell surface, the only accessible information is the microscope image; the vertical approach of the needle is unknown and must be detected. To this end, we propose an image process that integrates needle recognition, needle-tip localization, image focus measure, and vertical approach detection. The proposed image process was tested in 15 experimental sessions at various locations. The needle tip was reasonably and consistently positioned in the image, and the vertical approach was detected within the safe and plausible ranges.
{"title":"Localizing a needle tip using 2D microscope images and detecting vertical approach of a needle based on focus measures for intracellular microneedle insertion","authors":"S. Park, W. Chung","doi":"10.1109/IROS.2016.7759399","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759399","url":null,"abstract":"Microneedle insertion is useful for elucidating the processes in living cells and their organelles. However, mechanical puncture by the needle causes traumatic damage to the cell. As a less invasive process, we have developed intracellular needle insertion using femtosecond laser cell ablation. To quickly and precisely position the spot ablated by the laser, we accurately located the needle tip in a 2D image plane. When the needle approaches the cell surface, the only accessible information is the microscope image; the vertical approach of the needle is unknown and must be detected. To this end, we propose an image process that integrates needle recognition, needle-tip localization, image focus measure, and vertical approach detection. The proposed image process was tested in 15 experimental sessions at various locations. The needle tip was reasonably and consistently positioned in the image, and the vertical approach was detected within the safe and plausible ranges.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123169112","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 : 2016-10-01DOI: 10.1109/IROS.2016.7758088
S. S. Baishya, B. Bäuml
Attaching a flexible tactile skin to an existing robotic system is relatively easy compared to integrating most other tactile sensor designs. In this paper we show that material classification purely based on the spatio-temporal signal of a flexible tactile skin can be robustly performed in a real world setting. We compare different classification algorithms and feature sets, including features adopted and extended from previous works in tactile material classification and that are based on the signal's Fourier spectrum. Our convolutional deep learning network architecture, which we also present here, is directly fed with the raw 24000 dimensional sensor signal and performs best by a large margin, reaching a classification accuracy of up to 97.3%.
{"title":"Robust material classification with a tactile skin using deep learning","authors":"S. S. Baishya, B. Bäuml","doi":"10.1109/IROS.2016.7758088","DOIUrl":"https://doi.org/10.1109/IROS.2016.7758088","url":null,"abstract":"Attaching a flexible tactile skin to an existing robotic system is relatively easy compared to integrating most other tactile sensor designs. In this paper we show that material classification purely based on the spatio-temporal signal of a flexible tactile skin can be robustly performed in a real world setting. We compare different classification algorithms and feature sets, including features adopted and extended from previous works in tactile material classification and that are based on the signal's Fourier spectrum. Our convolutional deep learning network architecture, which we also present here, is directly fed with the raw 24000 dimensional sensor signal and performs best by a large margin, reaching a classification accuracy of up to 97.3%.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"243 23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117339724","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 : 2016-10-01DOI: 10.1109/IROS.2016.7759598
Enrique Muñoz, Yoshinori Konishi, C. Beltran, Vittorio Murino, A. D. Bue
This paper presents a method for 6D pose estimation from a single RGB image for complex texture-less objects. This class of objects are common in any environment but still challenging to deal with. This is due to the fact that the distribution of surface brightness makes difficult to compute interest points or appearance-based descriptors. Here we propose a novel part-based method using an efficient template matching approach where each template independently encodes the similarity function using a Forest trained over the templates. Moreover, accuracy is even more incremented by using a cascade of the learned forest. These templates forests together with the simplicity of the computed image features allow a quick estimate of the pose achieving real-time performance. Performance are demonstrated both on synthetic and real images with known ground truth.
{"title":"Fast 6D pose from a single RGB image using Cascaded Forests Templates","authors":"Enrique Muñoz, Yoshinori Konishi, C. Beltran, Vittorio Murino, A. D. Bue","doi":"10.1109/IROS.2016.7759598","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759598","url":null,"abstract":"This paper presents a method for 6D pose estimation from a single RGB image for complex texture-less objects. This class of objects are common in any environment but still challenging to deal with. This is due to the fact that the distribution of surface brightness makes difficult to compute interest points or appearance-based descriptors. Here we propose a novel part-based method using an efficient template matching approach where each template independently encodes the similarity function using a Forest trained over the templates. Moreover, accuracy is even more incremented by using a cascade of the learned forest. These templates forests together with the simplicity of the computed image features allow a quick estimate of the pose achieving real-time performance. Performance are demonstrated both on synthetic and real images with known ground truth.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121027149","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 : 2016-10-01DOI: 10.1109/IROS.2016.7759844
Yang Song, J. O’Kane
We describe a new decentralized algorithm for multi-robot systems to form arbitrary repeated lattice patterns. Prior work showed how to represent a desired pattern using a directed graph in which each edge is labeled with a rigid body transformation, and proposed an algorithm that accepts this graph as input and computes destinations for each robot using only local information. In this paper, we improve upon that result by describing a new algorithm, substantially different both in message passing procedure and in movement strategy, to resolve several limitations of the existing algorithm. We prove that, by executing this algorithm, the robots will form the desired lattice pattern in a bounded amount of time. We further show that, if the robots' communication graph is connected at the start of the algorithm, it will remain connected throughout the algorithm's execution. Using a simulation, we demonstrate that this algorithm works correctly for systems with dozens of autonomous robots to form various lattice patterns. Moreover, the experiments show a significant improvement in solution quality for our new algorithm compared to the previous approach.
{"title":"Forming repeating patterns of mobile robots: A provably correct decentralized algorithm","authors":"Yang Song, J. O’Kane","doi":"10.1109/IROS.2016.7759844","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759844","url":null,"abstract":"We describe a new decentralized algorithm for multi-robot systems to form arbitrary repeated lattice patterns. Prior work showed how to represent a desired pattern using a directed graph in which each edge is labeled with a rigid body transformation, and proposed an algorithm that accepts this graph as input and computes destinations for each robot using only local information. In this paper, we improve upon that result by describing a new algorithm, substantially different both in message passing procedure and in movement strategy, to resolve several limitations of the existing algorithm. We prove that, by executing this algorithm, the robots will form the desired lattice pattern in a bounded amount of time. We further show that, if the robots' communication graph is connected at the start of the algorithm, it will remain connected throughout the algorithm's execution. Using a simulation, we demonstrate that this algorithm works correctly for systems with dozens of autonomous robots to form various lattice patterns. Moreover, the experiments show a significant improvement in solution quality for our new algorithm compared to the previous approach.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127234611","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 : 2016-10-01DOI: 10.1109/IROS.2016.7759609
Mathias Bürki, Igor Gilitschenski, E. Stumm, R. Siegwart, Juan I. Nieto
In this paper, we present an online landmark selection method for distributed long-term visual localization systems in bandwidth-constrained environments. Sharing a common map for online localization provides a fleet of autonomous vehicles with the possibility to maintain and access a consistent map source, and therefore reduce redundancy while increasing efficiency. However, connectivity over a mobile network imposes strict bandwidth constraints and thus the need to minimize the amount of exchanged data. The wide range of varying appearance conditions encountered during long-term visual localization offers the potential to reduce data usage by extracting only those visual cues which are relevant at the given time. Motivated by this, we propose an unsupervised method of adaptively selecting landmarks according to how likely these landmarks are to be observable under the prevailing appearance condition. The ranking function this selection is based upon exploits landmark co-observability statistics collected in past traversals through the mapped area. Evaluation is performed over different outdoor environments, large time-scales and varying appearance conditions, including the extreme transition from day-time to night-time, demonstrating that with our appearance-dependent selection method, we can significantly reduce the amount of landmarks used for localization while maintaining or even improving the localization performance.
{"title":"Appearance-based landmark selection for efficient long-term visual localization","authors":"Mathias Bürki, Igor Gilitschenski, E. Stumm, R. Siegwart, Juan I. Nieto","doi":"10.1109/IROS.2016.7759609","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759609","url":null,"abstract":"In this paper, we present an online landmark selection method for distributed long-term visual localization systems in bandwidth-constrained environments. Sharing a common map for online localization provides a fleet of autonomous vehicles with the possibility to maintain and access a consistent map source, and therefore reduce redundancy while increasing efficiency. However, connectivity over a mobile network imposes strict bandwidth constraints and thus the need to minimize the amount of exchanged data. The wide range of varying appearance conditions encountered during long-term visual localization offers the potential to reduce data usage by extracting only those visual cues which are relevant at the given time. Motivated by this, we propose an unsupervised method of adaptively selecting landmarks according to how likely these landmarks are to be observable under the prevailing appearance condition. The ranking function this selection is based upon exploits landmark co-observability statistics collected in past traversals through the mapped area. Evaluation is performed over different outdoor environments, large time-scales and varying appearance conditions, including the extreme transition from day-time to night-time, demonstrating that with our appearance-dependent selection method, we can significantly reduce the amount of landmarks used for localization while maintaining or even improving the localization performance.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124893819","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 : 2016-10-01DOI: 10.1109/IROS.2016.7759666
Jinqiao Shi, B. He, Liwei Zhang, Jianwei Zhang
Real-time 3D mapping with MAV (Micro Aerial Vehicle) in GPS-denied environment is a challenging problem. In this paper, we present an effective vision-based 3D mapping system with 2D laser-scanner. All algorithms necessary for this system are on-board. In this system, two cameras work together with the laser-scanner for motion estimation. The distance of the points detected by laser-scanner are transformed and treated as the depth of image features, which improves the robustness and accuracy of the pose estimation. The output of visual odometry is used as an initial pose in the Iterative Closest Point (ICP) algorithm and the motion trajectory is optimized by the registration result. We finally get the MAV's state by fusing IMU with the pose estimation from mapping process. This method maximizes the utility of the point clouds information and overcomes the scale problem of lacking depth information in the monocular visual odometry. The results of the experiments prove that this method has good characteristics in real-time and accuracy.
{"title":"Vision-based real-time 3D mapping for UAV with laser sensor","authors":"Jinqiao Shi, B. He, Liwei Zhang, Jianwei Zhang","doi":"10.1109/IROS.2016.7759666","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759666","url":null,"abstract":"Real-time 3D mapping with MAV (Micro Aerial Vehicle) in GPS-denied environment is a challenging problem. In this paper, we present an effective vision-based 3D mapping system with 2D laser-scanner. All algorithms necessary for this system are on-board. In this system, two cameras work together with the laser-scanner for motion estimation. The distance of the points detected by laser-scanner are transformed and treated as the depth of image features, which improves the robustness and accuracy of the pose estimation. The output of visual odometry is used as an initial pose in the Iterative Closest Point (ICP) algorithm and the motion trajectory is optimized by the registration result. We finally get the MAV's state by fusing IMU with the pose estimation from mapping process. This method maximizes the utility of the point clouds information and overcomes the scale problem of lacking depth information in the monocular visual odometry. The results of the experiments prove that this method has good characteristics in real-time and accuracy.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125177583","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 : 2016-10-01DOI: 10.1109/IROS.2016.7759343
D. Fourie, J. Leonard, M. Kaess
We relax parametric inference to a nonparametric representation towards more general solutions on factor graphs. We use the Bayes tree factorization to maximally exploit structure in the joint posterior thereby minimizing computation. We use kernel density estimation to represent a wider class of constraint beliefs, which naturally encapsulates multi-hypothesis and non-Gaussian inference. A variety of new uncertainty models can now be directly applied in the factor graph, and have the solver recover a potentially multi-modal posterior. For example, data association for loop closure proposals can be incorporated at inference time without further modifications to the factor graph. Our implementation of the presented algorithm is written entirely in the Julia language, exploiting high performance parallel computing. We show a larger scale use case with the well known Victoria park mapping and localization data set inferring over uncertain loop closures.
{"title":"A nonparametric belief solution to the Bayes tree","authors":"D. Fourie, J. Leonard, M. Kaess","doi":"10.1109/IROS.2016.7759343","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759343","url":null,"abstract":"We relax parametric inference to a nonparametric representation towards more general solutions on factor graphs. We use the Bayes tree factorization to maximally exploit structure in the joint posterior thereby minimizing computation. We use kernel density estimation to represent a wider class of constraint beliefs, which naturally encapsulates multi-hypothesis and non-Gaussian inference. A variety of new uncertainty models can now be directly applied in the factor graph, and have the solver recover a potentially multi-modal posterior. For example, data association for loop closure proposals can be incorporated at inference time without further modifications to the factor graph. Our implementation of the presented algorithm is written entirely in the Julia language, exploiting high performance parallel computing. We show a larger scale use case with the well known Victoria park mapping and localization data set inferring over uncertain loop closures.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125855033","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 : 2016-10-01DOI: 10.1109/IROS.2016.7759553
Elis Stefansson, Yoke Peng Leong
This paper presents a technique to efficiently solve the Hamilton-Jacobi-Bellman (HJB) equation for a class of stochastic affine nonlinear dynamical systems in high dimensions. The HJB solution provides a globally optimal controller to the associated dynamical system. However, the curse of dimensionality, commonly found in robotic systems, prevents one from solving the HJB equation naively. This work avoids the curse by representing the linear HJB equation using tensor decomposition. An alternating least squares (ALS) based technique finds an approximate solution to the linear HJB equation. A straightforward implementation of the ALS algorithm results in ill-conditioned matrices that prevent approximation to a high order of accuracy. This work resolves the ill-conditioning issue by computing the solution sequentially and introducing boundary condition rescaling. Both of these additions reduce the condition number of matrices in the ALS-based algorithm. A MATLAB tool, Sequential Alternating Least Squares (SeALS), that implements the new method is developed. The performance of SeALS is illustrated using three engineering examples: an inverted pendulum, a Vertical Takeoff and Landing aircraft, and a quadcopter with state up to twelve.
{"title":"Sequential alternating least squares for solving high dimensional linear Hamilton-Jacobi-Bellman equation","authors":"Elis Stefansson, Yoke Peng Leong","doi":"10.1109/IROS.2016.7759553","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759553","url":null,"abstract":"This paper presents a technique to efficiently solve the Hamilton-Jacobi-Bellman (HJB) equation for a class of stochastic affine nonlinear dynamical systems in high dimensions. The HJB solution provides a globally optimal controller to the associated dynamical system. However, the curse of dimensionality, commonly found in robotic systems, prevents one from solving the HJB equation naively. This work avoids the curse by representing the linear HJB equation using tensor decomposition. An alternating least squares (ALS) based technique finds an approximate solution to the linear HJB equation. A straightforward implementation of the ALS algorithm results in ill-conditioned matrices that prevent approximation to a high order of accuracy. This work resolves the ill-conditioning issue by computing the solution sequentially and introducing boundary condition rescaling. Both of these additions reduce the condition number of matrices in the ALS-based algorithm. A MATLAB tool, Sequential Alternating Least Squares (SeALS), that implements the new method is developed. The performance of SeALS is illustrated using three engineering examples: an inverted pendulum, a Vertical Takeoff and Landing aircraft, and a quadcopter with state up to twelve.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"74 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125909503","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 : 2016-10-01DOI: 10.1109/IROS.2016.7759405
Tomoyasu Ichimura, K. Tadakuma, Eri Takane, M. Konyo, S. Tadokoro
Tethered robots often experience entangling of their cables with obstacles in uncertain disaster environments. This paper proposes a spherical tether handling device that unfastens a robot's tether during surveys by releasing the tether and carrying it aside. By using a differential mechanism, the device drives shells and rollers that hold the tether. On flat surfaces, the device moves forward by driving the shells. When the device climbs over steps, the rollers are driven by the differential mechanism to pull the tether automatically. After prototyping the device, we confirm the surmountability of the proposed device against steps. The results show that the device can climb a height 90.9% of its diameter. We also demonstrate a scenario to handle the tether and untangle multiple tangles in an environment with several obstacles.
{"title":"Development of a spherical tether-handling device with a coupled differential mechanism for tethered teleoperated robots","authors":"Tomoyasu Ichimura, K. Tadakuma, Eri Takane, M. Konyo, S. Tadokoro","doi":"10.1109/IROS.2016.7759405","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759405","url":null,"abstract":"Tethered robots often experience entangling of their cables with obstacles in uncertain disaster environments. This paper proposes a spherical tether handling device that unfastens a robot's tether during surveys by releasing the tether and carrying it aside. By using a differential mechanism, the device drives shells and rollers that hold the tether. On flat surfaces, the device moves forward by driving the shells. When the device climbs over steps, the rollers are driven by the differential mechanism to pull the tether automatically. After prototyping the device, we confirm the surmountability of the proposed device against steps. The results show that the device can climb a height 90.9% of its diameter. We also demonstrate a scenario to handle the tether and untangle multiple tangles in an environment with several obstacles.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126021492","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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