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Robotics

New submissions

[ total of 14 entries: 1-14 ]
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New submissions for Wed, 16 Jan 19

[1]  arXiv:1901.04588 [pdf, other]
Title: Optimal Needle Diameter, Shape, and Path in Autonomous Suturing
Comments: 2 pages, 2 figures, 2017 SoCal Robotics Symposium
Subjects: Robotics (cs.RO)

Needle shape, diameter, and path are critical parameters that directly affect suture depth and tissue trauma in autonomous suturing. This paper presents an optimization-based approach to specify these parameters. Given clinical suturing guidelines, a kinematic model of needle-tissue interaction was developed to quantify suture parameters and constraints. The model was further used to formulate constant curvature needle path planning as a nonlinear optimization problem. The optimization results were confirmed experimentally with the Raven II surgical system. The proposed needle path planning algorithm guarantees minimal tissue trauma and complies with a wide range of suturing requirements.

[2]  arXiv:1901.04782 [pdf, other]
Title: Learning Autonomous Exploration and Mapping with Semantic Vision
Comments: Accepted at IVSP 2019
Subjects: Robotics (cs.RO)

We address the problem of autonomous exploration and mapping for a mobile robot using visual inputs. Exploration and mapping is a well-known and key problem in robotics, the goal of which is to enable a robot to explore a new environment autonomously and create a map for future usage. Different to classical methods, we propose a learning-based approach this work based on semantic interpretation of visual scenes. Our method is based on a deep network consisting of three modules: semantic segmentation network, mapping using camera geometry and exploration action network. All modules are differentiable, so the whole pipeline is trained end-to-end based on actor-critic framework. Our network makes action decision step by step and generates the free space map simultaneously. To our best knowledge, this is the first algorithm that formulate exploration and mapping into learning framework. We validate our approach in simulated real world environments and demonstrate performance gains over competitive baseline approaches.

[3]  arXiv:1901.04933 [pdf, ps, other]
Title: Sensorless Hand Guidance using Microsoft Hololens
Comments: Accepted to HRI2019 - Late Breaking reports
Subjects: Robotics (cs.RO)

Hand guidance of robots has proven to be a useful tool both for programming trajectories and in kinesthetic teaching. However hand guidance is usually relegated to robots possessing joint-torque sensors (JTS). Here we propose to extend hand guidance to robots lacking those sensors through the use of an Augmented Reality (AR) device, namely Microsoft's Hololens. Augmented reality devices have been envisioned as a helpful addition to ease both robot programming and increase situational awareness of humans working in close proximity to robots. We reference the robot by using a registration algorithm to match a robot model to the spatial mesh. The in-built hand tracking capabilities are then used to calculate the position of the hands relative to the robot. By decomposing the hand movements into orthogonal rotations we achieve a completely sensorless hand guidance without any need to build a dynamic model of the robot itself. We did the first tests our approach on a commonly used industrial manipulator, the KUKA KR-5.

Cross-lists for Wed, 16 Jan 19

[4]  arXiv:1901.04473 (cross-list from cs.SY) [pdf, other]
Title: Adaptive Guidance with Reinforcement Meta-Learning
Comments: arXiv admin note: substantial text overlap with arXiv:1810.08719
Subjects: Systems and Control (cs.SY); Robotics (cs.RO)

This paper proposes a novel adaptive guidance system developed using reinforcement meta-learning with a recurrent policy and value function approximator. The use of recurrent network layers allows the deployed policy to adapt real time to environmental forces acting on the agent. We compare the performance of the DR/DV guidance law, an RL agent with a non-recurrent policy, and an RL agent with a recurrent policy in four difficult tasks with unknown but highly variable dynamics. These tasks include a safe Mars landing with random engine failure and a landing on an asteroid with unknown environmental dynamics. We also demonstrate the ability of a recurrent policy to navigate using only Doppler radar altimeter returns, thus integrating guidance and navigation.

[5]  arXiv:1901.04780 (cross-list from cs.CV) [pdf, other]
Title: DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion
Subjects: Computer Vision and Pattern Recognition (cs.CV); Robotics (cs.RO)

A key technical challenge in performing 6D object pose estimation from RGB-D image is to fully leverage the two complementary data sources. Prior works either extract information from the RGB image and depth separately or use costly post-processing steps, limiting their performances in highly cluttered scenes and real-time applications. In this work, we present DenseFusion, a generic framework for estimating 6D pose of a set of known objects from RGB-D images. DenseFusion is a heterogeneous architecture that processes the two data sources individually and uses a novel dense fusion network to extract pixel-wise dense feature embedding, from which the pose is estimated. Furthermore, we integrate an end-to-end iterative pose refinement procedure that further improves the pose estimation while achieving near real-time inference. Our experiments show that our method outperforms state-of-the-art approaches in two datasets, YCB-Video and LineMOD. We also deploy our proposed method to a real robot to grasp and manipulate objects based on the estimated pose.

Replacements for Wed, 16 Jan 19

[6]  arXiv:1309.7666 (replaced) [pdf]
Title: Dynamic Sliding Mode Control based on Fractional calculus subject to uncertain delay based chaotic pneumatic robot
Comments: 8 pages, 9 figures, will be submitted in journal
Subjects: Robotics (cs.RO); Systems and Control (cs.SY)
[7]  arXiv:1609.07720 (replaced) [pdf, other]
Title: SegMatch: Segment based loop-closure for 3D point clouds
Comments: 8 pages, 8 figures
Subjects: Robotics (cs.RO)
[8]  arXiv:1804.09557 (replaced) [pdf, other]
Title: SegMap: 3D Segment Mapping using Data-Driven Descriptors
Subjects: Robotics (cs.RO); Computer Vision and Pattern Recognition (cs.CV)
[9]  arXiv:1805.01831 (replaced) [pdf, other]
Title: A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Drones
Comments: 14 pages, 13 figures, 5 tables, 2 listings, under review on IEEE Internet of Things Journal (IEEE IOTJ)
Subjects: Robotics (cs.RO); Artificial Intelligence (cs.AI); Neural and Evolutionary Computing (cs.NE); Signal Processing (eess.SP)
[10]  arXiv:1809.00075 (replaced) [pdf, other]
Title: Semantic Mapping for Orchard Environments by Merging Two-Sides Reconstructions of Tree Rows
Comments: 33 pages, 31 figures, 6 tables. arXiv admin note: substantial text overlap with arXiv:1804.05905
Subjects: Robotics (cs.RO)
[11]  arXiv:1809.04230 (replaced) [pdf, other]
Title: Trajectory Generation for Multiagent Point-To-Point Transitions via Distributed Model Predictive Control
Comments: 8 pages, 7 figures
Journal-ref: IEEE Robotics and Automation Letters, vol. 4, iss. 2, pp. 375-382, 2019
Subjects: Robotics (cs.RO); Multiagent Systems (cs.MA)
[12]  arXiv:1808.00177 (replaced) [pdf, other]
Title: Learning Dexterous In-Hand Manipulation
Comments: 15 pages, 10 figures, minor typos fixed
Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Robotics (cs.RO); Machine Learning (stat.ML)
[13]  arXiv:1811.09656 (replaced) [pdf, other]
Title: Hierarchical visuomotor control of humanoids
Comments: Accepted as a conference paper at ICLR 2019
Subjects: Artificial Intelligence (cs.AI); Robotics (cs.RO)
[14]  arXiv:1811.11711 (replaced) [pdf, other]
Title: Neural probabilistic motor primitives for humanoid control
Comments: Accepted as a conference paper at ICLR 2019
Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Robotics (cs.RO)
[ total of 14 entries: 1-14 ]
[ showing up to 2000 entries per page: fewer | more ]

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