Publications

2020

  • [1]
    Visual Memorability for Robotic Interestingness via Unsupervised Online Learning.
    By Wang, C., Wang, W., Qiu, Y., Hu, Y. and Scherer, S.
    In European Conference on Computer Vision (ECCV) 2020.

  • [2]
    A Unified 3D Mapping Framework Using a 3D or 2D LiDAR.
    By Zhen, W. and Scherer, S.
    In International Symposium on Experimental Robotics, pp. 702–711, 2020.

  • [3]
    Autonomous aerial cinematography in unstructured environments with learned artistic decision-making.
    By Bonatti, R., Wang, W., Ho, C., Ahuja, A., Gschwindt, M., Camci, E., Kayacan, E., Choudhury, S. and Scherer, S.
    In Journal of Field Robotics, Jan. 2020.

  • [4]
    Autonomous Drone Cinematographer: Using Artistic Principles to Create Smooth, Safe, Occlusion-Free Trajectories for Aerial Filming.
    By Bonatti, R., Zhang, Y., Choudhury, S., Wang, W. and Scherer, S.
    In International Symposium on Experimental Robotics, pp. 119–129, 2020.

  • [5]
    Monocular Camera Localization in Prior LiDAR Maps with 2D-3D Line Correspondences.
    By Yu, H., Zhen, W., Yang, W., Zhang, J. and Scherer, S.
    In arXiv.org, Apr. 2020.

  • [6]
    Precision UAV Landing in Unstructured Environments.
    By Pluckter, K. and Scherer, S.
    In International Symposium on Experimental Robotics, pp. 177–187, 2020.

  • [7]
    TartanAir: A Dataset to Push the Limits of Visual SLAM.
    By Wang, W., Zhu, D., Wang, X., Hu, Y., Qiu, Y., Wang, C., Hu, Y., Kapoor, A. and Scherer, S.
    In arXiv.org, Mar. 2020.

  • 2019

  • [1]
    A Joint Optimization Approach of LiDAR-Camera Fusion for Accurate Dense 3-D Reconstructions.
    By Zhen, W., Hu, Y., Liu, J. and Scherer, S.
    In IEEE Robotics and Automation Letters, vol. 4, no. 4, pp. 3585–3592, Oct. 2019.

  • [2]
    A Stereo Algorithm for Thin Obstacles and Reflective Objects.
    By Keller, J. and Scherer, S.
    In arXiv.org, Oct. 2019.

  • [3]
    Aerial Contact Sensing for Improved Inspection of Transportation Infrastructure.
    By Scherer, S.
    pp. 1–11, Aug. 2019.

  • [4]
    ALFA: A Dataset for UAV Fault and Anomaly Detection.
    By Keipour, A., Mousaei, M. and Scherer, S.
    Jul. 2019.

  • [5]
    Automatic real-time anomaly detection for autonomous aerial vehicles.
    By Keipour, A., Mousaei, M. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, vol. 2019-May, pp. 5679–5685, Jun. 2019.

  • [6]
    CubeSLAM: Monocular 3-D Object SLAM.
    By Yang, S. and Scherer, S.
    In IEEE Transactions on Robotics, vol. 35, no. 4, pp. 925–938, Jun. 2019.

  • [7]
    Decentralized Method for Sub-Swarm Deployment and Rejoining.
    By Chandarana, M., Luo, W., Lewis, M., Sycara, K. and Scherer, S.
    In Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, pp. 1209–1214, 2019.

  • [8]
    Deep-Learning Assisted High-Resolution Binocular Stereo Depth Reconstruction.
    By Hu, Y., Zhen, W. and Scherer, S.
    In arXiv.org, Nov. 2019.

  • [9]
    Estimating the localizability in tunnel-like environments using LiDAR and UWB.
    By Zhen, W. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automationvol. 2019-May, , pp. 4903–4908, 2019.

  • [10]
    High performance and safe flight of full-scale helicopters from takeoff to landing with an ensemble of planners.
    By Choudhury, S., Dugar, V., Maeta, S., MacAllister, B., Arora, S., Althoff, D. and Scherer, S.
    In Journal of Field Robotics, vol. 36, no. 8, pp. 1275–1332, Dec. 2019.

  • [11]
    Improved generalization of heading direction estimation for aerial filming using semi-supervised regression.
    By Wang, W., Ahuja, A., Zhang, Y., Bonatti, R. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automationvol. 2019-May, , pp. 5901–5907, 2019.

  • [12]
    Learning Visuomotor Policies for Aerial Navigation Using Cross-Modal Representations.
    By Bonatti, R., Madaan, R., Vineet, V., Scherer, S. and Kapoor, A.
    In arXiv:1909.06993v1 [cs.CV], Sep. 2019.

  • [13]
    LiDAR Enhanced Structure-from-Motion.
    By Zhen, W., Hu, Y., Yu, H. and Scherer, S.
    In arXiv.org, Nov. 2019.

  • [14]
    Line-based Camera Pose Estimation in Point Cloud of Structured Environments.
    By Yu, H., Zhen, W., Yang, W. and Scherer, S.
    In arXiv.org, Nov. 2019.

  • [15]
    Monocular object and plane slam in structured environments.
    By Yang, S. and Scherer, S.
    In IEEE Robotics and Automation Letters, vol. 4, no. 4, pp. 3145–3152, 2019.

  • [16]
    Multi-view reconstruction of wires using a catenary model.
    By Madaan, R., Kaess, M. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automationvol. 2019-May, , pp. 5657–5664, 2019.

  • 2018

  • [1]
    Achieving Robust Localization in Geometrically Degenerated Tunnels.
    By Zhen, W. and Scherer, S.
    In Workshop on Challenges and Opportunities for Resilient Collective Intelligence in Subterranean Environments, Pittsburgh, Pa2018.

  • [2]
    An efficient global energy optimization approach for robust 3D plane segmentation of point clouds.
    By Dong, Z., Yang, B., Hu, P. and Scherer, S.
    In ISPRS Journal of Photogrammetry and Remote Sensing, vol. 137, pp. 112–133, Mar. 2018.

  • [3]
    Bayesian active edge evaluation on expensive graphs.
    By Choudhury, S., Srinivasa, S. and Scherer, S.
    In IJCAI International Joint Conference on Artificial Intelligence, vol. 2018-July, pp. 4890–4897, Nov. 2018.

  • [4]
    Data-driven planning via imitation learning.
    By Choudhury, S., Bhardwaj, M., Arora, S., Kapoor, A., Ranade, G., Scherer, S. and Dey, D.
    In International Journal of Robotics Research, vol. 37, no. 13-14, pp. 1632–1672, Dec. 2018.

  • [5]
    Determining Effective Swarm Sizes for Multi-Job Type Missions.
    By Chandarana, M., Lewis, M., Sycara, K. and Scherer, S.
    In IEEE International Conference on Intelligent Robots and Systems, pp. 4848–4853, 2018.

  • [6]
    DROAN - Disparity-Space Representation for Obstacle Avoidance: Enabling Wire Mapping Avoidance.
    By Dubey, G., Madaan, R. and Scherer, S.
    In IEEE International Conference on Intelligent Robots and Systems, pp. 6311–6318, 2018.

  • [7]
    Hierarchical registration of unordered TLS point clouds based on binary shape context descriptor.
    By Dong, Z., Yang, B., Liang, F., Huang, R. and Scherer, S.
    In ISPRS Journal of Photogrammetry and Remote Sensing, vol. 144, pp. 61–79, Oct. 2018.

  • [8]
    Hindsight is Only 50/50: Unsuitability of MDP based Approximate POMDP Solvers for Multi-resolution Information Gathering.
    By Arora, S., Choudhury, S. and Scherer, S.
    In arXiv.org, Apr. 2018.

  • [9]
    Integrating kinematics and environment context into deep inverse reinforcement learning for predicting off-road vehicle trajectories.
    By Zhang, Y., Wang, W., Bonatti, R., Maturana, D. and Scherer, S.
    In Conference on Robot Learning2018.

  • [10]
    Joint Point Cloud and Image Based Localization for Efficient Inspection in Mixed Reality.
    By Das, M.P., Dong, Z. and Scherer, S.
    In IEEE International Conference on Intelligent Robots and Systems, pp. 6357–6363, Nov. 2018.

  • [11]
    Monocular and Stereo Cues for Landing Zone Evaluation for Micro UAVs.
    By Garg, R., Yang, S. and Scherer, S.
    In arXiv.org, Dec. 2018.

  • [12]
    Open Problems in Robotic Anomaly Detection.
    By Gupta, R., Kurtz, Z.T., Scherer, S. and Smereka, J.M.
    In arXiv.org, Sep. 2018.

  • [13]
    Path Planning for Unmanned Fixed-Wing Aircraft in Uncertain Wind Conditions Using Trochoids.
    By Schopferer, S., Lorenz, J.S., Keipour, A. and Scherer, S.
    In 2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018, Dallas, TX, pp. 503–512, 2018.

  • [14]
    Positioning error analysis of least squares method for wireless sensor networks.
    By Tian, X., Zhen, W., Scherer, S. and Lu, X.
    In 50th International Symposium on Robotics, ISR 2018, pp. 143–146, 2018.

  • [15]
    Real-Time Semantic Mapping for Autonomous Off-Road Navigation.
    By Maturana, D., Chou, P.-W., Uenoyama, M. and Scherer, S.
    In Field and Service Robotics,
    Springer, Cham, 2018, pp. pp. 335–350

  • [16]
    Robust image-based crack detection in concrete structure using multi-scale enhancement and visual features.
    By Liu, X., Ai, Y. and Scherer, S.
    In Proceedings - International Conference on Image Processing, ICIPvol. 2017-September, , pp. 2304–2308, 2018.

  • [17]
    Season-Invariant Semantic Segmentation with a Deep Multimodal Network.
    By Kim, D.-K., Maturana, D., Uenoyama, M. and Scherer, S.
    In Field and Service Robotics,
    Springer, Cham, 2018, pp. pp. 255–270

  • [18]
    Swarm size planning tool for multi-job type missions.
    By Chandarana, M., Lewis, M., Allen, B.D., Sycara, K. and Scherer, S.
    In 2018 Aviation Technology, Integration, and Operations Conference2018.

  • [19]
    Toward delay-tolerant multiple-unmanned aerial vehicle scheduling system using Multi-strategy Coevolution algorithm.
    By Khosiawan, Y., Scherer, S. and Nielsen, I.
    In Advances in Mechanical Engineering, vol. 10, no. 12, p. 168781401881523, Dec. 2018.

  • [20]
    Visual Place Recognition in Long-term and Large-scale Environment based on CNN Feature.
    By Zhu, J., Ai, Y., Tian, B., Cao, D. and Scherer, S.
    In IEEE Intelligent Vehicles Symposium, Proceedingsvol. 2018-June, , pp. 1679–1685, 2018.

  • 2017

  • [1]
    A multi-sensor fusion MAV state estimation from long-range stereo, IMU, GPS and barometric sensors.
    By Song, Y., Nuske, S. and Scherer, S.
    In Sensors (Switzerland), vol. 17, no. 1, p. 11, Dec. 2017.

  • [2]
    A \kappaiTE in the wind: Smooth trajectory optimization in a moving reference frame.
    By Dugar, V., Choudhury, S. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Singapore, Singapore, pp. 109–116, 2017.

  • [3]
    Adaptive information gathering via imitation learning.
    By Choudhury, S., Kapoor, A., Ranade, G., Scherer, S. and Dey, D.
    In Robotics: Science and Systems, vol. 13, May 2017.

  • [4]
    Direct monocular odometry using points and lines.
    By Yang, S. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, pp. 3871–3877, Mar. 2017.

  • [5]
    DROAN - Disparity-space representation for obstacle AvoidaNce.
    By Dubey, G., Arora, S. and Scherer, S.
    In IEEE International Conference on Intelligent Robots and Systems, Vancouvervol. 2017-September, , pp. 1324–1330, 2017.

  • [6]
    Improving stochastic policy gradients in continuous control with deep reinforcement learning using the beta distribution.
    By Chou, P.W., Maturana, D. and Scherer, S.
    In 34th International Conference on Machine Learning, ICML 2017, Sydneyvol. 2, , pp. 1386–1396, 2017.

  • [7]
    Learning Heuristic Search via Imitation.
    By Bhardwaj, M., Choudhury, S. and Scherer, S.
    In CoRL, 2017.

  • [8]
    Looking forward: A semantic mapping system for scouting with micro-aerial vehicles.
    By Maturana, D., Arora, S. and Scherer, S.
    In IEEE International Conference on Intelligent Robots and Systemsvol. 2017-September, , pp. 6691–6698, 2017.

  • [9]
    Near-optimal edge evaluation in explicit generalized binomial graphs.
    By Choudhury, S., Javdani, S., Srinivasa, S. and Scherer, S.
    In Advances in Neural Information Processing Systems, vol. 2017-December, pp. 4632–4642, Jun. 2017.

  • [10]
    Obstacle Avoidance through Deep Networks based Intermediate Perception.
    By Yang, S., Konam, S., Ma, C., Rosenthal, S., Veloso, M. and Scherer, S.
    In arXiv.org, Apr. 2017.

  • [11]
    Randomized algorithm for informative path planning with budget constraints.
    By Arora, S. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Singapore, Singapore, pp. 4997–5004, 2017.

  • [12]
    Robust Autonomous Flight in Constrained and Visually Degraded Shipboard Environments.
    By Fang, Z., Yang, S., Jain, S., Dubey, G., Roth, S., Maeta, S., Nuske, S., Zhang, Y. and Scherer, S.
    In Journal of Field Robotics, vol. 34, no. 1, pp. 25–52, Jan. 2017.

  • [13]
    Robust localization and localizability estimation with a rotating laser scanner.
    By Zhen, W., Zeng, S. and Soberer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Singapore, Singapore, pp. 6240–6245, 2017.

  • [14]
    Robust Localization of an Arbitrary Distribution of Radioactive Sources for Aerial Inspection.
    By Shah, D. and Scherer, S.
    In arXiv.org, Oct. 2017.

  • [15]
    Semantic 3D occupancy mapping through efficient high order CRFs.
    By Yang, S., Huang, Y. and Scherer, S.
    In IEEE International Conference on Intelligent Robots and Systems, Vancouvervol. 2017-September, , pp. 590–597, 2017.

  • [16]
    Smooth trajectory optimization in Wind: First results on a full-scale helicopter.
    By Dugar, V., Choudhury, S. and Scherer, S.
    In Annual Forum Proceedings - AHS International, Fort Worth, TX, pp. 2924–2932, 2017.

  • [17]
    Wire detection using synthetic data and dilated convolutional networks for unmanned aerial vehicles.
    By Madaan, R., Maturana, D. and Scherer, S.
    In IEEE International Conference on Intelligent Robots and Systems, Vancouvervol. 2017-September, , pp. 3487–3494, 2017.

  • 2016

  • [1]
    A framework for optimal repairing of vector field-based motion plans.
    By Pereira, G.A.S., Choudhury, S. and Scherer, S.
    In 2016 International Conference on Unmanned Aircraft Systems, ICUAS 2016, Washington, D.C., pp. 261–266, 2016.

  • [2]
    Constrained CHOMP using Dual Projected Newton Method.
    By Choudhury, S. and Scherer, S.
    Carnegie Mellon University, Pittsburgh, PA
    Technical Report #April, 2016

  • [3]
    Detecting cars in aerial photographs with a hierarchy of deconvolution nets.
    By Chakraborty, S., Maturana, D. and Scherer, S.
    Carnegie Mellon University, Pittsburgh, PA
    Technical Report #CMU-RI-TR-16-60, 2016

  • [4]
    Kinodynamic Motion Planning on Vector Fields using RRT *.
    By Pereira, G.A.S., Choudhury, S. and Scherer, S.
    Carnegie Mellon University, Pittsburgh, PA
    Technical Report #CMU-RI-TR-16-17, 2016

  • [5]
    List prediction applied to motion planning.
    By Tallavajhula, A., Choudhury, S., Scherer, S. and Kelly, A.
    In Proceedings - IEEE International Conference on Robotics and Automation, Stockholm, Swedenvol. 2016-June, , pp. 213–220, 2016.

  • [6]
    Modeling and Control of Coaxial UAV with Swashplate Controlled Lower Propeller.
    By Lee, R., Sreenath, K. and Scherer, S.
    Carnegie Mellon University, Pittsburgh, PA
    Technical Report #June, 2016

  • [7]
    Nonholonomic Motion Planning in Partially Unknown Environments Using Vector Fields and Optimal Planners.
    By Pereira, G.A.S., Choudhury, S. and Scherer, S.
    In Congresso Brasileiro de Automatica (CBA), Vitoria, Brazil2016.

  • [8]
    Pop-up SLAM: Semantic monocular plane SLAM for low-texture environments.
    By Yang, S., Song, Y., Kaess, M. and Scherer, S.
    In IEEE International Conference on Intelligent Robots and Systems, Daejeon, Koreavol. 2016-November, , pp. 1222–1229, 2016.

  • [9]
    Real-time 3D scene layout from a single image using Convolutional Neural Networks.
    By Yang, S., Maturana, D. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Stockholm, Swedenvol. 2016-June, , pp. 2183–2189, 2016.

  • [10]
    Regionally accelerated batch informed trees (RABIT∗): A framework to integrate local information into optimal path planning.
    By Choudhury, S., Gammell, J.D., Barfoot, T.D., Srinivasa, S.S.D. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Stockholm, Swedenvol. 2016-June, , pp. 4207–4214, 2016.

  • 2015

  • [1]
    3D Convolutional Neural Networks for landing zone detection from LiDAR.
    By Maturana, D. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Seattle, WA, USAvol. 2015-June, no. June, , pp. 3471–3478, 2015.

  • [2]
    Autonomous exploration and motion planning for an unmanned aerial vehicle navigating rivers.
    By Nuske, S., Choudhury, S., Jain, S., Chambers, A., Yoder, L., Scherer, S., Chamberlain, L., Cover, H. and Singh, S.
    In Journal of Field Robotics, vol. 32, no. 8, pp. 1141–1162, 2015.

  • [3]
    Autonomous river exploration.
    By Jain, S., Nuske, S., Chambers, A., Yoder, L., Cover, H., Chamberlain, L., Scherer, S. and Singh, S.
    In Springer Tracts in Advanced Robotics, Brisbanne, Australiavol. 105, , pp. 93–106, 2015.

  • [4]
    Autonomous Semantic Exploration Using Unmanned Aerial Vehicles.
    By Arora, S., Dubey, G., Jain, S., Maturana, D., Song, Y., Nuske, S. and Scherer, S.
    In Workshop on Vision-based Control and Navigation of Small Lightweight UAVs, IROS 20152015.

  • [5]
    Connected invariant sets for high-speed motion planning in partially-known environments.
    By Althoff, D. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Seattle, WA, USAvol. 2015-June, no. June, , pp. 3279–3285, 2015.

  • [6]
    Emergency maneuver library - Ensuring safe navigation in partially known environments.
    By Arora, S., Choudhury, S., Althoff, D. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Seattle, WA, USAvol. 2015-June, no. June, , pp. 6431–6438, 2015.

  • [7]
    High-precision Autonomous Flight in Constrained Shipboard Environments.
    By Yang, S., Fang, Z., Jain, S., Dubey, G., Maeta, S., Roth, S., Scherer, S., Zhang, Y. and Nuske, S.
    Carnegie Mellon University, Pittsburgh, PA
    Technical Report #CMU-RI-TR-16-17, Feb-2015

  • [8]
    Mixed-Initiative Control of a Roadable Air Vehicle for Non-Pilots.
    By Dorneich, M.C., Letsu-Dake, E., Singh, S., Scherer, S., Chamberlain, L. and Bergerman, M.
    In Journal of Human-Robot Interaction, vol. 4, no. 3, p. 38, Jan. 2015.

  • [9]
    Multi-Scale Convolutional Architecture for Semantic Segmentation.
    By Raj, A., Maturana, D. and Scherer, S.
    Carnegie Mellon University, Pittsburgh, PA
    Technical Report #September, Oct-2015

  • [10]
    Online safety verification of trajectories for unmanned flight with offline computed robust invariant sets.
    By Althoff, D., Althoff, M. and Scherer, S.
    In IEEE International Conference on Intelligent Robots and Systems, Hamburg, Germanyvol. 2015-December, , pp. 3470–3477, 2015.

  • [11]
    PASP: Policy based approach for sensor planning.
    By Arora, S. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Seattle, WAvol. 2015-June, no. June, , pp. 3479–3486, 2015.

  • [12]
    Real-time onboard 6DoF localization of an indoor MAV in degraded visual environments using a RGB-D camera.
    By Fang, Z. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Seattle, WA, USAvol. 2015-June, no. June, , pp. 5253–5259, 2015.

  • [13]
    Recognition of human group activity for video analytics.
    By Ju, J., Yang, C., Scherer, S. and Ko, H.
    In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9315
    Y.-S. Ho, J. Sang, Y. M. Ro, J. Kim, and F. Wu, Eds.
    Cham: Springer, 2015, pp. pp. 161–169

  • [14]
    The Dynamics Projection Filter (DPF) - Real-time nonlinear trajectory optimization using projection operators.
    By Choudhury, S. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Seattle, WA, USAvol. 2015-June, no. June, , pp. 644–649, 2015.

  • [15]
    The planner ensemble: Motion planning by executing diverse algorithms.
    By Choudhury, S., Arora, S. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Seattle, WA, USAvol. 2015-June, no. June, , pp. 2389–2395, 2015.

  • [16]
    Theoretical limits of speed and resolution for kinodynamic planning in a poisson forest.
    By Choudhury, S., Scherer, S. and Bagnell, J.A.
    In Robotics: Science and Systems, vol. 11, 2015.

  • [17]
    VoxNet: A 3D Convolutional Neural Network for real-time object recognition.
    By Maturana, D. and Scherer, S.
    In IEEE International Conference on Intelligent Robots and Systems, Hamburg, Germanyvol. 2015-December, , pp. 922–928, 2015.

  • 2014

  • [1]
    A principled approach to enable safe and high performance maneuvers for autonomous rotorcraft.
    By Arora, S., Choudhury, S., Althoff, D. and Scherer, S.
    In Annual Forum Proceedings - AHS International, Montreal, CANvol. 4, , pp. 3228–3236, 2014.

  • [2]
    Experimental study of odometry estimation methods using RGB-D cameras.
    By Fang, Z. and Scherer, S.
    In IEEE International Conference on Intelligent Robots and Systems, Chicago, IL, pp. 680–687, 2014.

  • [3]
    Learning Motion Planning Assumptions.
    By Vemula, A., Choudhury, S. and Scherer, S.
    Carnegie Mellon University, Pittsburgh, PA
    Technical Report #August, Aug-2014

  • [4]
    Robust multi-sensor fusion for micro aerial vehicle navigation in GPS-degraded/denied environments.
    By Chambers, A., Scherer, S., Yoder, L., Jain, S., Nuske, S. and Singh, S.
    In Proceedings of the American Control Conference, Portland, OR, pp. 1892–1899, 2014.

  • [5]
    The planner ensemble and trajectory executive: A high performance motion planning system with guaranteed safety.
    By Choudhury, S., Arora, S. and Scherer, S.
    In Annual Forum Proceedings - AHS International, Montreal, CANvol. 4, , pp. 2872–2891, 2014.

  • [6]
    Visual Odometry in Smoke Occluded Environments.
    By Agarwal, A., Maturana, D. and Scherer, S.
    Carnegie Mellon University, Pittsburgh, PA
    Technical Report #CMU-RI-TR-15-07, Jul-2014

  • 2013

  • [1]
    Autonomous emergency landing of a helicopter: Motion planning with hard time-constraints.
    By Choudhury, S., Scherer, S. and Singh, S.
    In Annual Forum Proceedings - AHS International, Phoenix, AZvol. 3, , pp. 2236–2249, 2013.

  • [2]
    First results in detecting and avoiding frontal obstacles from a monocular camera for micro unmanned aerial vehicles.
    By Mori, T. and Scherer, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, pp. 1750–1757, 2013.

  • [3]
    Infrastructure-free shipdeck tracking for autonomous landing.
    By Arora, S., Jain, S., Scherer, S., Nuske, S., Chamberlain, L. and Singh, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, pp. 323–330, 2013.

  • [4]
    Robocopters to the rescue.
    By Cooper, E.
    In IEEE Spectrum, vol. 50, no. 10, pp. 28–33, 2013.

  • [5]
    RRT*-AR: Sampling-based alternate routes planning with applications to autonomous emergency landing of a helicopter.
    By Choudhury, S., Scherer, S. and Singh, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, pp. 3947–3952, 2013.

  • [6]
    Sparse Tangential Network (SPARTAN): Motion planning for micro aerial vehicles.
    By Cover, H., Choudhury, S., Scherer, S. and Singh, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, pp. 2820–2825, 2013.

  • 2012

  • [1]
    Autonomous landing at unprepared sites by a full-scale helicopter.
    By Scherer, S., Chamberlain, L. and Singh, S.
    In Robotics and Autonomous Systems, vol. 60, no. 12, pp. 1545–1562, Dec. 2012.

  • [2]
    First results in autonomous landing and obstacle avoidance by a full-scale helicopter.
    By Scherer, S., Chamberlain, L. and Singh, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, St. Paul, MN, pp. 951–956, 2012.

  • [3]
    Realtime alternate routes planning: the rrt*-ar algorithm.
    By Choudhury, S., Scherer, S. and Singh, S.
    Carnegie Mellon University, Pittsburgh, PA
    Technical Report #December, 2012

  • [4]
    River mapping from a flying robot: State estimation, river detection, and obstacle mapping.
    By Scherer, S., Rehder, J., Achar, S., Cover, H., Chambers, A., Nuske, S. and Singh, S.
    In Autonomous Robots, vol. 33, no. 1-2, pp. 189–214, 2012.

  • 2011

  • [1]Low-Altitude Operation of Unmanned Rotorcraft, PhD thesis, The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, 2011
  • [2]
    Multiple-objective motion planning for unmanned aerial vehicles.
    By Scherer, S. and Singh, S.
    In IEEE International Conference on Intelligent Robots and Systems, San Francisco, CA, pp. 2207–2214, 2011.

  • [3]
    Navigation and Control for Micro Aerial Vehicles in GPS-Denied Environments.
    By Molero, R., Scherer, S. and Chamberlain, L.J.
    Carnegie Mellon University, Pittsburgh, PA
    Technical Report #CMU-RI-TR-10-08, Jun-2011

  • [4]
    Perception for a river mapping robot.
    By Chambers, A., Achar, S., Nuske, S., Rehder, J., Kitt, B., Chamberlain, L., Haines, J., Scherer, S. and Singh, S.
    In IEEE International Conference on Intelligent Robots and Systems, San Francisco, CA, pp. 227–234, 2011.

  • [5]
    Self-aware helicopters: Full-scale automated landing and obstacle avoidance in unmapped environments.
    By Chamberlain, L., Scherer, S. and Singh, S.
    In Annual Forum Proceedings - AHS International, Virginia Beachvol. 4, , pp. 3210–3219, 2011.

  • [6]
    Self-supervised segmentation of river scenes.
    By Achar, S., Sankaran, B., Nuske, S., Scherer, S. and Singh, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Shanghai, China, pp. 6227–6232, 2011.

  • 2010

  • [1]
    Online assessment of landing sites.
    By Scherer, S., Chamberlain, L. and Singh, S.
    In AIAA Infotech at Aerospace 2010, Atlanta2010.

  • 2009

  • [1]
    Efficient C-space and cost function updates in 3D for unmanned aerial vehicles.
    By Scherer, S., Ferguson, D. and Singh, S.
    In Proceedings - IEEE International Conference on Robotics and Automation, Kobe, Japan, pp. 2049–2054, 2009.

  • 2008

  • [1]
    A practical approach to robotic design for the DARPA Urban Challenge.
    By Patz, B.J., Papelis, Y., Pillat, R., Stein, G. and Harper, D.
    Pittsburgh, PA
    Technical Report #8, Apr-2008

  • [2]
    Flying fast and low among obstacles: Methodology and experiments.
    By Scherer, S., Singh, S., Chamberlain, L. and Elgersma, M.
    In International Journal of Robotics Research, Rome, Italyvol. 27, no. 5, , pp. 549–574, 2008.

  • [3]
    Flying fast and low among obstacles: Methodology and experiments.
    By Scherer, S., Singh, S., Chamberlain, L. and Elgersma, M.
    In International Journal of Robotics Research, vol. 27, no. 5, pp. 549–574, 2008.

  • 2007

    2006

  • [1]
    Learning obstacle avoidance parameters from operator behavior.
    By Hamner, B., Singh, S. and Scherer, S.
    In Journal of Field Robotics, vol. 23, no. 11-12, pp. 1037–1058, 2006.

  • [2]
    Learning to drive among obstacles.
    By Hamner, B., Scherer, S. and Singh, S.
    In IEEE International Conference on Intelligent Robots and Systems, Beijing, China, pp. 2663–2669, 2006.

  • [3]
    Learning to drive among obstacles.
    By Hamner, B., Scherer, S. and Singh, S.
    In IEEE International Conference on Intelligent Robots and Systems, pp. 2663–2669, 2006.

  • 2005

  • [1]
    Model checking of robotic control systems.
    By Scherer, S., Lerda, F. and Clarke, E.M.
    In European Space Agency, (Special Publication) ESA SP, Munich, Germanyno. 603, , pp. 371–378, 2005.