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New submissions

[ total of 6 entries: 1-6 ]
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New submissions for Thu, 22 Feb 18

[1]  arXiv:1802.07346 [pdf, other]
Title: Cooperative Robot Localization Using Event-triggered Estimation
Comments: Revised submission in review with AIAA Journal of Aerospace Information Systems (JAIS), submitted February 17, 2018
Subjects: Robotics (cs.RO); Systems and Control (cs.SY); Signal Processing (eess.SP); Applications (stat.AP)

This paper describes a novel communication-spare cooperative localization algorithm for a team of mobile unmanned robotic vehicles. Exploiting an event-based estimation paradigm, robots only send measurements to neighbors when the expected innovation for state estimation is high. Since agents know the event-triggering condition for measurements to be sent, the lack of a measurement is thus also informative and fused into state estimates. The robots use a Covariance Intersection (CI) mechanism to occasionally synchronize their local estimates of the full network state. In addition, heuristic balancing dynamics on the robots' CI-triggering thresholds ensure that, in large diameter networks, the local error covariances remains below desired bounds across the network. Simulations on both linear and nonlinear dynamics/measurement models show that the event-triggering approach achieves nearly optimal state estimation performance in a wide range of operating conditions, even when using only a fraction of the communication cost required by conventional full data sharing. The robustness of the proposed approach to lossy communications, as well as the relationship between network topology and CI-based synchronization requirements, are also examined.

[2]  arXiv:1802.07490 [pdf, other]
Title: ViTac: Feature Sharing between Vision and Tactile Sensing for Cloth Texture Recognition
Comments: 6 pages, 5 figures, Accepted for 2018 IEEE International Conference on Robotics and Automation
Subjects: Robotics (cs.RO); Computer Vision and Pattern Recognition (cs.CV); Graphics (cs.GR)

Vision and touch are two of the important sensing modalities for humans and they offer complementary information for sensing the environment. Robots are also envisioned to be of such multi-modal sensing ability. In this paper, we propose a new fusion method named Deep Maximum Covariance Analysis (DMCA) to learn a joint latent space for sharing features through vision and tactile sensing. The features of camera images and tactile data acquired from a GelSight sensor are learned by deep neural networks. But the learned features are of a high dimensionality and are redundant due to the differences in the two sensing modalities, which deteriorates the perception performance. To solve this, the learned features are paired using maximum covariance analysis. Results of the algorithm on a newly collected dataset of paired visual and tactile data relating to cloth textures show that a good recognition performance of greater than 90% can be achieved by using the proposed DMCA framework. In addition, we find that the perception performance of either vision or tactile sensing can be improved by employing the shared representation space, compared to learning from unimodal data.

[3]  arXiv:1802.07546 [pdf, other]
Title: Planning Nonlinear Access Paths for Temporal Bone Surgery
Comments: To be published in International Journal on Computer Assisted Radiology and Surgery (IJCARS), Spl. Issue IPCAI 2018
Subjects: Robotics (cs.RO)

Purpose: Interventions at the otobasis operate in the narrow region of the temporal bone where several highly sensitive organs define obstacles with minimal clearance for surgical instruments. Nonlinear trajectories for potential minimally-invasive interventions can provide larger distances to risk structures and optimized orientations of surgical instruments, thus improving clinical outcomes when compared to existing linear approaches. In this paper, we present fast and accurate planning methods for such nonlinear access paths. Methods: We define a specific motion planning problem in SE(3) = R3 x SO(3) with notable constraints in computation time and goal pose that reflect the requirements of temporal bone surgery.We then present k-RRT-Connect: two suitable motion planners based on bidirectional Rapidly-exploring Random Trees (RRT) to solve this problem efficiently. Results: The benefits of k-RRT-Connect are demonstrated on real CT data of patients. Their general performance is shown on a large set of realistic synthetic anatomies. We also show that these new algorithms outperform state of the art methods based on circular arcs or Bezier-Splines when applied to this specific problem. Conclusion: With this work we demonstrate that pre- and intra-operative planning of nonlinear access paths is possible for minimally-invasive surgeries at the otobasis.

[4]  arXiv:1802.07557 [pdf, other]
Title: The Power of Color: A Study on the Effective Use of Colored Light in Human-Robot Interaction
Subjects: Robotics (cs.RO); Human-Computer Interaction (cs.HC)

In times of more and more complex interaction techniques, we point out the powerfulness of colored light as a simple and cheap feedback mechanism. Since it is visible over a distance and does not interfere with other modalities, it is especially interesting for mobile robots. In an online survey, we asked 56 participants to choose the most appropriate colors for scenarios that were presented in the form of videos. In these scenarios a mobile robot accomplished tasks, in some with success, in others it failed because the task is not feasible, in others it stopped because it waited for help. We analyze in what way the color preferences differ between these three categories. The results show a connection between colors and meanings and that it depends on the participants' technical affinity, experience with robots and gender how clear the color preference is for a certain category. Finally, we found out that the participants' favorite color is not related to color preferences.

Replacements for Thu, 22 Feb 18

[5]  arXiv:1607.01223 (replaced) [pdf, other]
Title: B.A.T.Mobile: Leveraging Mobility Control Knowledge for Efficient Routing in Mobile Robotic Networks
Journal-ref: Globecom Workshops (GC Wkshps), 2016 IEEE
Subjects: Networking and Internet Architecture (cs.NI); Robotics (cs.RO)
[6]  arXiv:1709.07911 (replaced) [pdf, other]
Title: Avoidance of Manual Labeling in Robotic Autonomous Navigation Through Multi-Sensory Semi-Supervised Learning
Subjects: Learning (cs.LG); Robotics (cs.RO)
[ total of 6 entries: 1-6 ]
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