Publications

[1] Hu, J., Tang, Z., and Christensen, H. I. Multi-modal planning on rearrangement for stable manipulation. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (October 2023). [ bib ]
[2] Christensen, H. I., and Yanco, H. Mid-cycle Update to the National Robotics Roadmap. Tech. rep., Computing Community Consortium (CCC), Washington, DC, Mar 2023. [ bib ]
[3] Patil, R., Langley, A., and Christensen, H. Scaling up multi-agent patrolling in urban environments. In Open Architecture/Open Business Model Net-Centric Systems and Defense Transformation 2023 (2023), R. Suresh, Ed., vol. 12544, International Society for Optics and Photonics, SPIE, p. 125440G. [ bib | DOI | http ]
Keywords: game theory, multi-agent autonomy, decentralized
[4] Qiu, Y., and Christensen, H. I. 3d scene graph prediction on point clouds using knowledge graphs. In 19th IEEE CASE Conference (Auckland, NZ, Aug 2023), IEEE. [ bib ]
[5] Wang, L., Guo, R., Vuong, Q., Qin, Y., Su, H., and Christensen, H. I. A real2sim2real method for robust object grasping with neural surface reconstruction. In 19th IEEE CASE Conference (Auckland, NZ, Aug 2023), IEEE. [ bib ]
[6] D'Ambrosia, C., Aronoff-Spencer, E., Huang, E. Y., Goldhaber, N. H., Christensen, H. I., Broderick, R. C., and Appelbaum, L. G. The neurophysiology of intraoperative error: An eeg study of trainee surgeons during robotic-assisted surgery simulations. Frontiers in Neuroergonomics 3 (2023). [ bib | DOI | http ]
Surgeons operate in mentally and physically demanding workspaces where the impact of error is highly consequential. Accurately characterizing the neurophysiology of surgeons during intraoperative error will help guide more accurate performance assessment and precision training for surgeons and other teleoperators. To better understand the neurophysiology of intraoperative error, we build and deploy a system for intraoperative error detection and electroencephalography (EEG) signal synchronization during robot-assisted surgery (RAS). We then examine the association between EEG data and detected errors. Our results suggest that there are significant EEG changes during intraoperative error that are detectable irrespective of surgical experience level.
[7] D'Ambrosia, C., Spencer, E., Huang, E., Goldhaber, N., Jacobsen, G., Sandler, B., Horgan, S., Appelbaum, L., Chirstensen, H. I., and Broderick, R. The physiology of intraoperative error: Using electrokardiograms to understand operator performance during robot-assisted surgery simulations. Surgical Endoscopy (2023). [ bib ]
[8] Zhang, H., Venkatramani, S., Paz, D., Li, Q., Xiang, H., and Christensen, H. I. Probabilistic semantic mapping for autonomous driving in urban environments. Sensors 23, 14 (2023). [ bib | DOI | http ]
Statistical learning techniques and increased computational power have facilitated the development of self-driving car technology. However, a limiting factor has been the high expense of scaling and maintaining high-definition (HD) maps. These maps are a crucial backbone for many approaches to self-driving technology. In response to this challenge, we present an approach that fuses pre-built point cloud map data with images to automatically and accurately identify static landmarks such as roads, sidewalks, and crosswalks. Our pipeline utilizes semantic segmentation of 2D images, associates semantic labels with points in point cloud maps to pinpoint locations in the physical world, and employs a confusion matrix formulation to generate a probabilistic bird’s-eye view semantic map from semantic point clouds. The approach has been tested in an urban area with different segmentation networks to generate a semantic map with road features. The resulting map provides a rich context of the environment that is valuable for downstream tasks such as trajectory generation and intent prediction. Moreover, it has the potential to be extended to the automatic generation of HD maps for semantic features. The entire software pipeline is implemented in the robot operating system (ROS), a widely used robotics framework, and made available.
[9] Hoej, H. S., Christensen, H. I., Hansen, S., and Svanebjerg, E. Scan matching and probabilistic stationary global localization in an airport environment. In 18th International Conference on Automation Science and Engineering (CASE) (Mexico City, Aug. 2022), IEEE. [ bib ]
[10] Zhang, H., Liao, J.-Y., Paz, D., and Christensen, H. Robust human identity anonymization using pose estimation. In 18th International Conference on Automation Science and Engineering (CASE) (Mexico City, Aug. 2022), IEEE. [ bib ]
[11] Hu, J., and Christensen, H. I. Rotational slippage minimization in object manipulation. In 18th International Conference on Automation Science and Engineering (CASE) (Mexico City, Aug. 2022), IEEE. [ bib ]
[12] Adeleye, A., Hu, J., and Christensen, H. Putting away the groceries with precise semantic placements. In 18th International Conference on Automation Science and Engineering (CASE) (Mexico City, Aug. 2022), IEEE. [ bib ]
[13] Madhavan, S., Pal, A., and Christensen, H. I. Role of reward shaping in object-goal navigation. In CVPR (New Orleans, LA, June 2022), IEEE. [ bib ]
[14] Paz, D., Xiang, H., Liang, A., and Christensen, H. I. TridentNetV2: Lightweight graphical global plan representations for dynamic trajectory generation. In Intl Conf of Robotics and Automation (ICRA) (Philadelphia, PA, May 2022), IEEE. [ bib ]
[15] Asfour, T., Yoshida, E., Park, J., Christensen, H., and Khatib, O., Eds. Robotics Research - The 19th International Symposium ISRR, vol. 20 of SPAR. Springer Verlag, Berlin, February 2022. [ bib ]
[16] Hu, J., Adeleye, A., and Christensen, H. I. Place-and-pick-based re-grasping using unstable placement. In ISRR - Robotics Research (Geneva, CH, Sep 2022), IFRR, Springer Verlag. [ bib ]
[17] Paz, D., Zhang, H., and Christensen, H. I. TridentNet: A conditional generative model for dynamic trajectory generation. In Intelligent Autonomous Systems-16 (Singapore, June 2021). (Best paper). [ bib ]
[18] Han, Y., Liu, Y., Paz, D., and Christensen, H. I. Auto-calibration method using stop signs for urban autonomous driving applications. In International Conference on Robotics and Automation (Xian, May 2021), IEEE. [ bib ]
[19] Vuong, Q., Qin, Y., Guo, R., Wang, X., Su, H., and Christensen, H. Single rgb-d camera teleoperation for general robotic manipulation, 2021. [ bib | arXiv ]
[20] Nieto-Granda, C., Wang, S., Rogers III, J. G., and Christensen, H. I. Distributed heterogeneous multi-robot source seeking using information based sampling with visual recognition. In 17th International Symposium on Experimental Robotics. (Malta, Nov 2021), SPAR, Springer Verlag. [ bib ]
[21] Parashar, P., Naik, A., Hu, J., and Christensen, H. I. A hierarchical model to enable plan reuse and repair in assembly domains. In IEEE Conference on Automation Science and Engineering (Lyon, France, Aug 2021), pp. 387--394. [ bib | DOI ]
[22] Langley, A., Dhiman, V., and Christensen, H. Heterogeneous multi-robot adversarial patrolling using polymatrix games. In Advances in Automation, Mechanical and Design Engineering (Cham, 2021), M. A. Laribi, G. Carbone, and Z. Jiang, Eds., Springer International Publishing. [ bib ]
[23] Vincze, M., Patten, T., Christensen, H. I., Nalpantidos, L., and Liu, M., Eds. Computer Vision Systems. No. 12899 in LNCS. Springer Verlag, Vienna, Austria, Sep 2021. [ bib ]
[24] Christensen, H., Amato, N., Yanco, H., Mataric, M., Choset, H., Drobnis, A., Goldberg, K., Grizzle, J., Hager, G., Hollerbach, J., Hutchinson, S., Krovi, V., Lee, D., Smart, B., Trinkle, J., and Sukhatme, G. A roadmap for us robotics - from internet to robotics 2020 edition. Foundations and Trends in Robotics 8, 4 (2021), 307--424. [ bib | DOI | http ]
[25] Christensen, H., Paz, D., Zhang, H., Meyer, D., Xiang, H., Han, Y., Liu, Y., Liang, A., Zhong, Z., and Tang, S. Autonomous vehicles for micro-mobility. Springer - Autonomous and Intelligent Systems (Nov 2021). [ bib ]
[26] Qui, Y. C., Pal, A., and Christensen, H. I. Target driven visual navigation exploiting object relationships. In The Conference on Robotic Learning (Boston, MA, November 2020). [ bib ]
[27] H. I. Christensen (Ed.). From internet to robotics - a US national robotics roadmap - 4th edition. Tech. rep., Computing Community Consortium & U.C. San Diego, Washington, DC, September 2020. [ bib | .pdf ]
[28] Pal, A., Mondal, S., and Christensen, H. I. “looking at the right stuff” - guided semantic-gaze for autonomous driving. In Computer Vision and Pattern Recognition (CVPR) (Seattle, WA, June 2020), IEEE/PAMI. [ bib ]
[29] Yang, G.-Z., Nelson, B., Murphy, R., Christensen, H., Collins, S., Dario, P., Goldberg, K., Ikuta, K., Jacobstein, N., Kragic, D., Taylor, R., and McNutt, M. Combating covid-19 -- the role of robotics in managing public health and infectious diseases. Science Robotics (March 2020). (Editorial). [ bib ]
[30] Paz, D., Zhang, H., Li, Q., Xiang, H., and Christensen, H. I. Probabilistic semantic mapping for urban autonomous driving applications. In International Conference on Intelligent Robots and Systems (IROS) (Las Vegas, NV, Oct 2020), IEEE/RSJ. [ bib ]
[31] Paz, D., Lai, P.-J., Chan, N., Jianf, Y., and Christensen, H. I. Autonomous vehicle benchmarking using unbiased metrics. In International Conference on Intelligent Robots and Systems (IROS) (Las Vegas, NV, Oct 2020), IEEE/RSJ. [ bib ]
[32] Dieber, B., White, R., Taurer, S., Breiling, B., Caiazza, G., Christensen, H., and Cortesi, A. Penetration testing ros. In Robot Operating System (ROS). Springer, 2020, pp. 183--225. [ bib ]
[33] D'Ambrosia, C., Christensen, H., and Arnoff-Spenncer, E. Ruling In and Ruling Out COVID-19: Computing SARS-CoV-2 infection risk from symptoms, imaging and test data. Journal of Medical Internet Research (JMIR) (Nov 2020). [ bib ]
[34] Paz, D., Lai, P.-J., Harish, S., Zhang, H., Chan, N., Hu, C., Binnani, S., and Christensen, H. Lessons learned from deploying autonomous vehicles at UC San Diego. In Field and Service Robotics (Tokyo, JP, August 2019). [ bib ]
[35] Wang, S., Liu, X., Zhao, J., and Christensen, H. Robotic reliability engineering: A story of long-term tritonbot development. In Field and Service Robotics (Tokyo, JP, August 2019). [ bib ]
[36] White, R., Caiazza, G., Jiang, C., Ou, X., Yang, Z., Cortesi, A., and Christensen, H. Network reconnaissance and vulnerability excavation of secure dds systems. In Workshop on Software Security for Internet of Things (Stockholm, Sweden, June 2019), IEEE and Euro S&P. [ bib ]
[37] Fung, N., Rogers III, J. G., Nieto-Granda, C., Christensen, H. I., Kemna, S., and Sukhatme, G. Coordinating multi-robot systems through environment partitioning for adaptive informative sampling. In Intl. Conf. Robotics and Automation (Montreal, May 2019), IEEE. [ bib ]
[38] Wang, S., Liu, X., Zhao, J., and Christensen, H. I. Rorg: Service robot software management with linux containers. In Intl. Conf. Robotics and Automation (Montreal, May 2019), IEEE. [ bib ]
[39] Li, S., and Christensen, H. I. WaveToFly: wavetofly: Control a uav using body gestures. In Intl. Conf. Robotics and Automation (Montreal, May 2019), IEEE. [ bib ]
[40] Parashar, P., Sanneman, L. M., Christensen, H. I., and Shah, J. A. Enabling efficient team cooperation by understanding modes of human-robot interactions. In Intl. Conf. Robotics and Automation (Montreal, May 2019). [ bib ]
[41] Pal, A., Nieto, C., and Christensen, H. I. DEDUCE: Diverse scEne Detection methods in Unseen Challenging Environments. In International Conference on Intelligent Robots and Systems (Macau, Oct 2019), IEEE/RSJ. [ bib ]
[42] Parashar, P., Sanneman, L., Christensen, H. I., and Shah, J. A. A taxonomy for characterizing modes of interactions in goal-driven, human-robot teams. In International Conference on Intelligent Robots and Systems (Macau, Oct 2019), IEEE/RSJ. [ bib ]
[43] White, R., Caiazza, G., Cortesi, A., Cho, Y. I., and Christensen, H. I. Black block recorder: Immutable black box logging for robots via blockchain. In International Conference on Intelligent Robots and Systems (Macau, Oct 2019), IEEE/RSJ, pp. 1--8. [ bib ]
[44] Yang, G.-Z., Full, R. J., Jacobstein, N., Fischer, P., Bellingham, J., Choset, H., Christensen, H., Dario, P., Nelson, B. J., and Taylor, R. Ten technologies of the year. Science Robotics 4 (2019). [ bib ]
[45] Wang, S., and Christensen, H. I. Tritonbot: First lessons learned from deployment of a long-term autonomy tour guide robot. In RoMan (Nanjing, China, August 2018), IEEE/RSJ. [ bib ]
[46] Sawhney, R., Li, F., Christensen, H. I., and Isbell, C. L. Purely geometric scene association and retrieval - a case for macro-scale 3d geometry. In Intl. Conf. on Robotics and Automation (Brisbane, May 2018), IEEE. [ bib ]
[47] Huamán Quispe, A., Ben Amor, H., and Christensen, H. I. A Taxonomy of Benchmark Tasks for Robot Manipulation. Springer International Publishing, Cham, 2018, pp. 405--421. [ bib | DOI | http ]
This paper presents a taxonomy of benchmark manipulation tasks for service robots. Our contributions are threefold: (1) A review of relevant literature regarding manipulation tests in the robotics domain and related fields, such as physical therapy, assistive technologies and prosthetics. (2) Guidelines to design useful testing protocols to evaluate manipulation performance. (3) A proposed general taxonomy of benchmark manipulation tasks and sample tests per each class.
[48] White, R., Caiazza, G., Christensen, H. I., and Cortesi, A. Procedurally provisioned access control for robotic systems. In RosCon (Madrid, Oct 2018). [ bib ]
[49] Nieto, C., Rogers, J., Fung, N., Kemna, S., Christensen, H. I., and Sukhatme, G. On-line Coordination Task for Multi-robot Systemsusing Adaptive Informative Sampling. In Intl. Symp. Exp. Robotics (Buenos Aires, Nov 2018), STAR, IFRR, Springer. [ bib ]
[50] Parashar, P., Goel, A., and Christensen, H. I. Using hierarchical expectations ground in percpetion for reasonign about failures during task execution. In AAAI 2018 Symposium - Real-World Systems for Long-Term Autonomy (Oct 2018). [ bib ]
[51] Berman, F., Rutenbar, R. A., Hailpern, B., Christensen, H., Davidson, S., Estrin, D., Franklin, M., Martonosi, M., Raghavan, P., Stodden, V., and Szalay, A. S. Realizing the potential of data science. Communications of the ACM 61, 4 (Apr 2018), 67--72. [ bib ]
[52] Cosgun, A., and Christensen, H. I. Context aware robot navigation using interactively built semantic maps. Paladyn. Journal of Behavioral Robotics 9, 1 (2018), 254--276. [ bib ]
[53] Price, A., Balakirsky, S., and Christensen, H. Robust grasp preimages under unknown mass and friction distributions. Integrated Computer Aided Engineering 25, 2 (Mar 2018), 99--110. [ bib ]
[54] Parashar, P., Goel, A., Sheneman, B., and Christensen, H. I. Towards lifelong adaptive agents: Using meta- reasoning for combining task planning and situated learning. The Knowledge Engineering Review 33, 18 (Oct 2018). [ bib ]
[55] Brahmbhatt, S., Christensen, H., and Hays, J. Stuffnet: Using “stuff” to improve object detection. In IEEE Winter Conference on Applications of Computer Vision (WACV) (2017). [ bib ]
[56] Shih, B., Drotman, D., Christianson, C., Huo, Z., White, R., Christensen, H. I., and Tolley, M. T. Custom soft robotic gripper sensor skins for haptic object visualization. In Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International Conference on (2017), IEEE, pp. 494--501. [ bib ]
[57] Christensen, H. I., Khan, A., Pokutta, S., and Tetali, P. Approximation and online algorithms for multidimensional bin packing: A survey. Computer Science Review (2017), --. [ bib | DOI | www: ]
Keywords: Approximation algorithms
[58] Choudhary, S., Carlone, L., Nieto, C., Rogers, J., Christensen, H. I., and Dellaert, F. Distributed mapping with privacy and communication constraints: Lightweight algorithms and object-based models. The International Journal of Robotics Research 36, 12 (2017), 1286--1311. [ bib | DOI | arXiv ]
We consider the following problem: a team of robots is deployed in an unknown environment and it has to collaboratively build a map of the area without a reliable infrastructure for communication. The backbone for modern mapping techniques is pose graph optimization, which estimates the trajectory of the robots, from which the map can be easily built. The first contribution of this paper is a set of distributed algorithms for pose graph optimization: rather than sending all sensor data to a remote sensor fusion server, the robots exchange very partial and noisy information to reach an agreement on the pose graph configuration. Our approach can be considered as a distributed implementation of a two-stage approach that already exists, where we use the Successive Over-Relaxation and the Jacobi Over-Relaxation as workhorses to split the computation among the robots. We also provide conditions under which the proposed distributed protocols converge to the solution of the centralized two-stage approach. As a second contribution, we extend the proposed distributed algorithms to work with the object-based map models. The use of object-based models avoids the exchange of raw sensor measurements (e.g. point clouds or RGB-D data) further reducing the communication burden. Our third contribution is an extensive experimental evaluation of the proposed techniques, including tests in realistic Gazebo simulations and field experiments in a military test facility. Abundant experimental evidence suggests that one of the proposed algorithms (the Distributed Gauss–Seidel method) has excellent performance. The Distributed Gauss–Seidel method requires minimal information exchange, has an anytime flavor, scales well to large teams (we demonstrate mapping with a team of 50 robots), is robust to noise, and is easy to implement. Our field tests show that the combined use of our distributed algorithms and object-based models reduces the communication requirements by several orders of magnitude and enables distributed mapping with large teams of robots in real-world problems. The source code is available for download at https://cognitiverobotics.github.io/distributed-mapper/
[59] Christensen, H. I., Okamura, A., Kumar, V., Hager, G., and Choset, H. Next generation robotics. Tech. rep., Computing Community Consortium, Washington, DC, June 2016. [ bib | .pdf ]
[60] Choudhary, S., Carlone, L., Nieto, C., Rogers III, J., Christensen, H. I., and Dellaert, F. Distributed trajectory estimation with privacy and communication constraints: a two-stage distributed gauss-seidel approach. In Intl. Conf of Robotics and Automation (ICRA) (Stockholm, May 2016), IEEE. [ bib ]
[61] Kunz, T., Thomaz, A., and Christensen, H. Hierarchical rejection sampling for informed kinodynamic planning in high-dimensional spaces. In Intl. Conf of Robotics and Automation (ICRA) (Stockholm, May 2016), IEEE. [ bib ]
[62] Price, A., Balakirsky, S., Bobick, A., and Christensen, H. Affordance-feasible planning with manipulator wrench spaces. In Intl. Conf of Robotics and Automation (ICRA) (Stockholm, May 2016), IEEE. [ bib ]
[63] Huaman, A., Ben-Amor, H., and Christensen, H. I. Combining arm and hand metrics for sensible grasp modeling. In Conf. on Automation Science and Engineering (CASE) (Austin, TX, Aug 2016), IEEE. [ bib ]
[64] Cosgun, A., Sisbot, A., and Christensen, H. I. Anticipatory robot path planning in human environments. In The 25th IEEE International Symposium on Robot and Human Interactive Communication (New York, NY, Aug 2016), IEEE. [ bib ]
[65] Scholz, J., Jindal, N., Levihn, M., Isbell, C., and Christensen, H. I. Navigation among movable obstacles with learned dynamic constraints. In International Conference on Intelligent Robots and Systems (Daejeon, Korea, Oct 2016), IEEE/RSJ. [ bib ]
[66] Lee, K., Joo, S., and Christensen, H. I. An assembly sequence generation of a product family for robot programming. In International Conference on Intelligent Robots and Systems (Daejeon, Korea, Oct 2016), IEEE/RSJ. [ bib ]
[67] Murali, V., Nieto, C., Choudhary, S., and Christensen, H. I. Active planning based extrinsic calibration of exteroceptive sensors in unkown environments. In International Conference on Intelligent Robots and Systems (Daejeon, Korea, Oct 2016), IEEE/RSJ. [ bib ]
[68] Choudhary, S., Carlone, L., Nieto, C., Rogers, J., Liu, Z., Christensen, H. I., and Dellaert, F. Multi robot object-based SLAM. In Intl. Symp. on Experimental Robotics (Tokyo, JP, Oct 2016), IFRR. [ bib ]
[69] Zafar, M., and Christensen, H. I. Whole body control of wheeled inverted pendulum humanoids. In Intl. Conf. on Humanoid Robotics (Cancun, MX, Nov 2016), IEEE-RAS, pp. 89--95. [ bib ]
[70] White, R., Christensen, H. I., and Quigley, M. SROS: Securing ROS over the wire, in the graph and through the kernel. In Humanoids 2016 (Cancun, Nov 2016), IEEE/RSJ. [ bib ]
[71] Dantam., N., H. B, A., Christensen, H., and Stilman, M. Online camera registration for robot manipulation. In Experimental Robotics, STAR. Springer Verlag, 2016, pp. 179--194. [ bib ]
[72] Dogar, M., Knepper, R. A., Spielberg, A., Choi, C., Christensen, H. I., and Rus, D. Towards coordinated precision assembly with robot teams. In Experimental Robotics, STAR. Springer Verlag, 2016, pp. 655--669. [ bib ]
[73] Choi, C., and Christensen, H. I. Rgb-d object pose estimation in unstructured environments. Robotics and Autonomous Systems 75, 1 (January 2016), 595--613. [ bib | www: ]
[74] Hager, G., Rus, D., Kumar, V., and Christensen, H. I. Towards a science of autonomy for physical systems. Tech. rep., Computing Community Consortium, Washington, DC, October 2015. [ bib | http ]
[75] Scholz, J., Levihn, M., Isbell, C., Christensen, H., and Stilman, M. Learning non-holonomic object models for mobile manipulation. In ICRA (Seattle, WA, May 2015), IEEE. [ bib ]
[76] Quispe, A. H., Melville, B., Erdogan, C., Amor, H. B., Christensen, H., and Stilman, M. Efficient manipulation planning with basic primitives. In ICRA (Seattle, WA, May 2015), IEEE. [ bib ]
[77] Choudhary, S., Indelman, V., Christensen, H. I., and Dellaert, F. Information based reduced landmark slam. In ICRA (Seatle, WA, May 2015), IEEE. [ bib ]
[78] Nieto-Granda, C., Choudhary, S., Rogers III, J. G., Twigg, J. N., Murali, V., and Christensen, H. I. Towards contextual awareness in robot mapping: extracting semantic hierarchy from point cloud data. In Unmanned Systems Technology XVII (Baltimore, MD, April 2015), vol. 9468, SPIE. [ bib ]
[79] Hickson, S., Essa, I., and Christensen, H. I. Semantic instance labeling leveraging hierarchical segmentation. In Winter Conference on Applications of Computer Vision (WACV) (Hawaii, Jan 2015), IEEE. [ bib ]
[80] Brahmbhatt, S., Ben-Amor, H., and Christensen, H. I. Occlusion aware object localization, segmentation and pose estimation. In British Machine Vision Conference (Swansea, UK, Sep 2015). [ bib | http ]
[81] Choudhary, S., Carlone, L., Christensen, H. I., and Dellaert, F. Exactly sparse memory efficient SLAM using the multi-block alternating direction method of multipliers. In IEEE/RSJ International Conference on Intelligent Robots and Systems (Hamburg, DE, Sep 2015), IEEE/RSJ. [ bib ]
[82] Quispe, A. H., Ben-Amor, H., and Christensen, H. A taxonomy of benchmark tasks for bimanual manipulators. In Intl. Conf. Robotics Research (Italy, Sep 2015), IFRR. [ bib ]
[83] Levihn, M., and Christensen, H. I. Using environment objects as tools in unknown environments. In Intl. Conf. on Humanoid Robots (Seoul, KR, Nov 2015), IEEE-RAS. [ bib ]
[84] Christensen, H. I., and Khatib, O., Eds. Robotics Research, vol. 100 of STAR. Springer Verlag, Heidelberg/New York, Dec 2015. [ bib ]
[85] M.Dogar, R.A.Knepper, A.Spielberg, C.Choi, H.I.Christensen, and D.Rus. Multi-scale assembly with robot teams. International Journal of Robotics Research 34, 13 (Jul 2015), 1645--1659. [ bib | http ]
[86] Gomez, J. M., Caputo, B., Cazorla, M., Christensen, H. I., Fornoni, M., Garcìa-Varea, I., and Pronobis, A. The robot vision challenge: Where are we after 5 editions? IEEE Robotics and Automation Magazine 22, 4 (Dec 2015), 146--156. [ bib ]
[87] Dantam, N., Ben-Amor, H., Christensen, H., and Stilman, M. Online camera registration for robot manipulation. In Proceedings of the 2014 International Symposium on Experimental Robotics (ISER) (Marocco, June 2014), IFRR, Springer Verlag. [ bib ]
[88] Hickson, S., Birchfield, S., Essa, I., and Christensen, H. Efficient Hierarchical Graph-Based Segmentation of RGBD Videos. In Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2014), IEEE Computer Society. [ bib ]
[89] Piliouras, G., Nieto-Granda, C., Christensen, H., and Shamma, J. Persistent patterns: Multi-agent learning beyond equilibrium and utility. In 13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS2014) (2014). [ bib ]
[90] Pippin, C., and Christensen, H. I. Trust modeling in multi-robot patrolling. In ICRA (Hong Kong, Jun 2014), IEEE/RSJ. [ bib ]
[91] Trevor, A. J. B., Rogers III, J. G., and Christensen, H. I. Omnimapper: A modular multimodal mapping framework. In ICRA (Hong Kong, Jun 2014), IEEE/RSJ. [ bib ]
[92] Cosgun, A., Sisbot, E. A., and Christensen, H. I. Vibro-tactile belt interface for robotic human navigation. In ICRA (Hong Kong, Jun 2014), IEEE/RSJ. [ bib ]
[93] Huckaby, J., and Christensen, H. I. Modeling robot assembly tasks in manufacturing using SysML. In ISR/Robotik (Munich, DE, Jun 2014), IFR. [ bib ]
[94] Nieto-Granda, C., Choudhary, S., Rogers, J. G., Twigg, J., Murali, V., and Christensen, H. I. Object guided autonomous exploration for mobile robots in indoor environments. In SPIE Defense+Security (Baltimore, MD, Apr 2014), SPIE, pp. 90840--90846. [ bib ]
[95] Huckaby, J., and Christensen, H. I. A Case for SysML in Robotics. In International Conference on Automation Science and Engineering (CASE) (Taipei, TW, Aug 2014), IEEE, pp. 333--338. [ bib ]
[96] Portugal, D., Pippin, C., Rocha, R. P., and Christensen, H. I. Finding optimal routes for multi-robot patrolling in generic graphs. In IROS-2014 (Chicago, IL, Sep 2014), IEEE-RAS / RSJ. [ bib ]
[97] Choudhary, S., Trevor, A. J. B., Christensen, H. I., and Dellaert, F. SLAM with object discovery, modeling and mapping. In IROS-2014 (Chicago, IL, Sep 2014), IEEE/RSJ. [ bib ]
[98] Dantam, N., Amor, H. B., Christensen, H., and Stilman, M. Online multi-camera registration for bimanual workspace trajectories. In Proceedings of the International Conference on Humanoid Robots (HUMANOIDS) (Barcelona, ES, Nov 2014), IEEE/RSJ. [ bib ]
[99] Nieto-Granda, C., Trevor, A. J., Rogers, J. G., Cunningham, A., Paluri, M., Michael, N., Dellaert, F., Christensen, H. I., and Kumar, V. Effects of sensory precision on mobile robot localization and mapping. In Experimental Robotics, STAR. Springer Verlag, Heidelberg/New York, Jan 2014, pp. 433--446. [ bib ]
[100] Nieto-Granda, C., III, J. G. R., and Christensen, H. I. Coordination strategies for multi-robot exploration and mapping. Intl. Jour. of Robotics Research 33, 4 (2014), 519--533. [ bib ]
[101] Sawhney, R., Christensen, H. I., and Bradski, G. R. Anisotropic agglomerative adaptive mean-shift. CoRR abs/1411.4102 (2014). [ bib | http ]
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In this report, we present a robotic sample introduction/ionization system for mass spectrometry (MS) for spot analysis and imaging of non-planar surfaces. The system operates by probing the sample surface with an acupuncture needle, followed by direct plasma chemical ionization time-of-flight MS.
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[168] Wu, J., Rehg, J., and Christensen, H. I. Visual Place Categorization: Problem, Dataset, and Algorithm. In IEEE/RSJ Intl. Conf. on Intell. Robots and Systems (St. Louis, MO, Oct. 2009), IEEE. [ bib ]
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Keywords: domestic robot, user study
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[332] Christensen, H. I., Horstmann, J., and Rasmussen, T. A control theoretic approach to active vision. In Proceedings from the Second Asian Conference on Computer Vision (Dec. 1995), IEEE, IEEE Computer Society, pp. 364--369. [ bib ]
[333] Pirjanian, P., and Christensen, H. I. Hierarchical control for navigation using heterogenuous models. In Modelling and Planning for Sensor Based Intellignet Robot Systems, H. Bunke, T. Kanade, and H. Noldemeier, Eds., vol. Vol 21 of Series in Machine Perception and Artificial Intelligence. World Scientific Press, Singapore, Nov. 1995, pp. 344--361. Proc. from Schloss Dagstuhl meeting on Environmental Modelling. [ bib ]
[334] Kosecka, J., and Christensen, H. I. Experiments in behaviour composition. In Proceedings from The International Symposium on Intelligent Robotic Systems 95 (Pisa, July 1995), pp. 1--8. [ bib ]
[335] Faymann, J., Rivlin, E., and Christensen, H. I. The active vision shell. In Proceedings of the Third International Symposium on Intelligent Robotic Systems'95, SIRS-95 (July 1995), pp. 315--322. [ bib ]
[336] Sinclair, D., Christensen, H. I., and Rothwell, C. Using the relation between a plane projectivity and the fundamental matrix. In Proceedings of the 9th SCIA (June 1995), Swedish Society for Automated Image Analysis., pp. 181--188. [ bib | .pdf ]
[337] Madsen, C. B., and Christensen, H. I. Modelling and testing the stability of edge segment; length and orientation. In Proceedings of the 9th Scandinavian Conference on Image Analysis (June 1995), Swedish Society for Automated Image Analysis, pp. 1011--1019. [ bib ]
[338] Causse, O., and Christensen, H. I. Hierarchical control design based on petri-net modelling for an autonomous for mobile robot. In Proceedings from the Intelligent Autonomous Systems IV (Mar. 1995). [ bib ]
[339] Košecká, J., Christensen, H. I., and Bajcsy, R. Discrete event modeling of visually guided behaviors. Intl. Jour. on Computer Vision, Special Issue on Qualitative Vision 8, 2 (Mar. 1995), 179--191. [ bib ]
[340] Crowley, J. L., and Christensen, H. I., Eds. Vision as Process. EEC Basic Research Series. Springer Verlag, Jan. 1995. [ bib | .html ]
[341] Christensen, H. I., and Granum, E. Control of perception. In Vision as Process, J. L. Crowley and H. I. Christensen, Eds., EEC Basic Research Series. Springer Verlag, Jan. 1995, pp. 323--346. [ bib ]
[342] Madsen, C. B., and Christensen, H. I. Modelling and testing the stability of edge segments: Length and orientation. World Scientific Press, Singapore, 1995, ch. Chapter 1., pp. 1--15. [ bib ]
[343] Kirkeby, N. O., and Christensen, H. I. A Vision Programmers Workbench. Springer Verlag, Heidelberg, 1995, pp. 57--71. [ bib ]
[344] Christensen, H. I., Granum, E., and Crowley, J. L. System Integration and Control. EEC Basic Research Series. Springer Verlag, Heidelberg., 1995, pp. 9--22. [ bib ]
[345] Madsen, C. B., and Christensen, H. I. Determining angles with a movable observer. In Proceedings of the 12th IAPR International Conference on Pattern Recognition : Conference A: Computer Vision and Image Processing (Oct. 1994), P. Storms, Ed., vol. 1, IEEE Computer Society Press, pp. 280--284. [ bib | .pdf ]
[346] Pirjanian, P., Blaasvær, H., and Christensen, H. I. Amor: An autonomous mobile robot navigation system. IEEE, International Conference on Systems, Man and Cybernetics 3 (Oct. 1994), 2266--2271. [ bib | .pdf ]
[347] Christensen, H. I., and Granum, E. Active vision - a survey. In Proceedings of the 11th European Conference on Artificial Intelligence, ECAI'94 (Aug. 1994), A. Cohn, Ed., John Wiley & Sons, pp. 1--6. [ bib ]
[348] Kristensen, S., and Christensen, H. I. Reconstruction of 3d planes with an image-enhanced estimator. In Proceedings of the International Workshop on Intelligent Robotic Systems '94. (July 1994), pp. 271--278. [ bib ]
[349] Matas, J., Christensen, H. I., Kittler, J., Illingworth, J., and Nguyen, L. Constraining Visual Expectations Using a Grammar of Scene Events. World Scientific, Bratislava, July 1994, ch. 1, pp. 1--12. [ bib ]
[350] Christensen, H. I., and Madsen, C. B. Purposive reconstruction. CVGIP: Image Understanding 60 (July 1994), 103--108. [ bib ]
[351] Madsen, C. B., and Christensen, H. I. Reactive view planning for quantification of local geometry. In Proceedings from IEEE Conference on Computer Vision and Pattern Recognition, Seattle, Washington (June 1994), pp. 823--828. [ bib | .pdf ]
[352] Madsen, C. B., and Christensen, H. I. Localizing un-calibrated, reactive camera motion in an object centered coordinate system. In Proceedings: IEEE Workshop on Visual Behaviours. (June 1994), IEEE, pp. 119--123. [ bib | .pdf ]
[353] Liang, J., Christensen, H. I., and Jensen, F. V. Qualitative recognition using bayes reasoning. In Proceedings from Pattern Recognition in Practice IV (June 1994), Elsevier Publishers. [ bib ]
[354] Dickinson, S. J., Jasiobedzki, P., Olofsson, G., and Christensen, H. I. Qualitative tracking of 3-d objects using active contour networks. In Proceedings from The International Conference on Computer Vision and Pattern Recognition. (June 1994), K. W. Bowyer, Ed., IEEE, pp. 812--817. [ bib | .pdf ]
[355] Andersen, C. S., and Christensen, H. I. Using multiple cues for controlling and agile camera head. In Proceedings from The IAPR Workshop on Visual Behaviours, Seattle 1994. (June 1994), IEEE Computer Society, pp. 97--101. [ bib | .pdf ]
[356] Dickinson, S. J., Christensen, H. I., Tsotsos, J., and Olofsson, G. Active object recognition integrating attention and viewpoint control. In Proceedings from the Third European Conference on Computer Vision, Stockholm (May 1994), J.-O. Eklundh, Ed., vol. 801 of Lecture Notes in Computer Science, Springer Verlag, pp. 3--14. [ bib ]
[357] Kirkeby, N. O. S., and Christensen, H. I. The Vision Programmers Workbench (VIPWOB), vol. Vol 11 of Series in Machine Perception and Artificial Intelligence. World Scientific, Singapore, Mar. 1994, pp. 195--224. [ bib ]
[358] Crowley, J. L., and Christensen, H. I. Vision as Process: Integration and Control of a Real Time Active Vision System. Series in Machine Perception and Artificial Intelligence. World Scientific, Singapore, Mar. 1994, pp. 127--155. [ bib ]
[359] Christensen, H. I., and Crowley, J. L., Eds. Experimental Environments in Computer Vision and Image Analysis, vol. Vol 11 of Series in Machine Perception and Artificial Intelligence. World Scientific Press, Feb. 1994. [ bib ]
[360] Andreasen, S., and Christensen, H. I. Image and Signal Processing - Synopsis. Year Book of Medical Informatics - 1994. Schattauer, 1994, pp. 263--265. [ bib ]
[361] Christensen, H., Kirkeby, N., Kristensen, S., and Knudsen, L. Model-driven vision for in-door navigation. Robotics and Autonomous Systems 12 (1994), 199--207. [ bib | .pdf ]
[362] Eggert, D. W., Bowyer, K. W., Dyer, C. R., Christensen, H. I., and Goldgof, D. B. The scale space aspect graph. IEEE Transactions on Pattern Analysis and Machine Intelligence 14 (Dec. 1993), 1114--1130. [ bib | .pdf ]
[363] Kristensen, S., and Christensen, H. I. Continuous reconstruction of scene objects. In Proceedings from Conference on Sensor Fusion VI, Boston, 1993 (Sept. 1993), P. S. Schenker, Ed., vol. 2059, SPIE, pp. 272--281. [ bib ]
[364] Crowley, J. L., and Christensen, H. I. Vision as process: Integration and control of a real time active vision system. In Proceedings of the Swiss Vision 93 (Sept. 1993), pp. 1--8. [ bib ]
[365] Christensen, H. I., Kirkeby, N. O. S., Kristensen, S., and Knudsen, L. F. Model-driven vision for in-door navigation. In Proceedings from Conference on Sensor Fusion VI, Boston, 1993 (Sept. 1993), P. S. Schenker, Ed., vol. 2059, SPIE, pp. 408--419. [ bib ]
[366] Christensen, H. I., Kirkeby, N. O., Kristensen, S., and Knudsen, L. F. Active vision for robot navigation. In Proceedings from IRS'93, Zakopane, Poland. Polish Academy of Science, July 1993, pp. 44--56. [ bib ]
[367] Sørensen, E., and Christensen, H. I. Monitoring of road traffic. In Proceedings of the 8th Scandinavian Conference on Image Analysis (=SCIA 93) (May 1993), K. A. Høgda, B. Braathen, and K. Heia, Eds., vol. 2, NOBIM, pp. 1085--1091. [ bib ]
[368] Madsen, C. B., and Christensen, H. I. Qualitative scene models from sparse 3d data. In Proceedings of the 8th Scandinavian Conference on Image Analysis (May 1993), K. A. Høgda, B. Braathen, and K. Heia, Eds., vol. 1, IAPR, NOBIM, pp. 427--433. [ bib ]
[369] Kristensen, S., Henrik, H. M. N., and Christensen, H. I. Cooperative depth extraction. In Proceedings of the 8th Scandinavian Conference on Image Analysis (May 1993), K. A. Høgda, B. Braathen, and K. Heia, Eds., vol. 1, NOBIM, pp. 321--328. [ bib ]
[370] Jones, J. P., Dorum, O. H., Andersen, C. S., Jacobsen, S. B., Jensen, M. S., Kirkeby, N. O. S., Kristensen, S., Madsen, C. B., Nielsen, H. M., Sørensen, E., Sørensen, J. J., and Christensen, H. I. Experiments in mobile robot navigation and range imaging. In Proceedings of the 8th Scandinavian Conference on Image Analysis. (May 1993), K. A. Høgda, B. Braathen, and K. Heia, Eds., vol. 1, NOBIM, pp. 371--387. [ bib ]
[371] Dickinson, S. J., Olofsson, G., and Christensen, H. I. Qualitative prediction in active recognition. In Proceedings of the 8th Scandinavian Conference on Image Analysis (May 1993), K. A. Høgda, B. Braathen, and K. Heia, Eds., vol. 1, NOBIM, Norwegian Society for Image Processing and Pattern Recognition, pp. 337--344. [ bib ]
[372] Bergem, O., Andersen, C. S., and Christensen, H. I. Using match uncertainty in the kalman filter for a sonar based positioning system. In Proceedings of the 8th Scandinavian Conference on Image Analysis. (May 1993), K. A. Høgda, B. Braathen, and K. Heia, Eds., vol. 1, NOBIM, pp. 405--410. [ bib | .pdf ]
[373] Christensen, H. I., Bowyer, K. W., and Bunke, H., Eds. Active Robot Vision: Camera Heads, Model Based Navigation and Reactive Control, vol. 7. World Scientific Publishers, Feb. 1993. [ bib ]
[374] Christensen, H. I. A low-cost robot camera head. Intl. Jour. of Pattern Recognition and Artificial Intelligence. Special issue on Active Robot Vision: Camera Heads, Model Based Navigation and Reactive Control 7 (Feb. 1993), 69--87. [ bib ]
[375] Christensen, H. I., Andersen, C. S., and Granum, E. Control of percpetion in dynamic vision. In Mobile Robotics III (Bostom, MA, Oct. 1992), SPIE. [ bib | .pdf ]
[376] Andersen, C. S., Christensen, H. I., Kirkeby, N. O. S., Knudsen, L. F., and Madsen, C. B. Vinav, et system for vision støttet navigation. In Proceedings Nordic Summer School on Active Vision and Geometric Modeling, Aalborg, 1992 (Sept. 1992), H. I. Christensen, Ed., Laboratory of Image Analysis, pp. 251--257. [ bib ]
[377] Christensen, H. I., Ed. Proceedings Nordic Summer School on Active Vision and Geometric Modeling. AUC Press, Aalborg, Denmark, Sept. 1992. [ bib ]
[378] Eggert, D. W., Bowyer, K. W., Dyer, C. R., Christensen, H. I., and Goldgof, D. B. The scale space aspect graph. In Proceedings from the IEEE Conference on Computer Vision and Pattern Recognition, June 1992, Urbana, Illinois (June 1992), pp. 335--340. [ bib | .pdf ]
[379] Granum, E., Christensen, H. I., Crowley, J. L., Chehikian, A., Eklundh, J.-O., Granlund, G., Kittler, J., and Illingworth, J. Vision as process. In Proceedings of ESPRIT DAY at the Second European Conference on Computer Vision 1992 (May 1992), P. V. Hove, Ed., CEC DG, Commission of the European Communities (=CEC), pp. 1--10. [ bib ]
[380] Jensen, F. V., Christensen, H. I., and Nielsen, J. Bayesian methods for interpretation and control in multi-agent vision systems. In Proceedings of SPIE Conference on Application of AI X: Machine Vision and Robotics (Apr. 1992), K. W. Bowyer, Ed., vol. 1708, SPIE, pp. 536--548. [ bib ]
[381] Christensen, H. I. The auc robot camera head. In Proceedings of SPIE Conference on Application of Artificial Intelligence X : Machine Vision and Robotics (Apr. 1992), K. W. Bowyer, Ed., vol. 1708, SPIE, pp. 26--33. [ bib ]
[382] Andersen, C. S., Madsen, C. B., Sørensen, J. J., Kirkeby, N. O. S., Jones, J. P., and Christensen, H. I. Laser range guided robot vehicle. In Proceedings of the Second Nordic Workshop on Industrial Machine Vision (1992), pp. 1--6. [ bib ]
[383] Eggert, D. W., Bowyer, K. W., Dyer, C. R., Christensen, H. I., and Goldgof, D. B. Applying the scale space concept to perspective projection aspect graphs. In Theory and Applications of Image Analysis - Selected Papers from 7th Scandinavian Conference on Image Analysis., P. Johansen and S. I. Olsen, Eds. World Scientific Publishers, 1992, pp. 48--62. [ bib ]
[384] Andersen, C. S., Madsen, C. B., Sørensen, J. J., Kirkeby, N. O. S., Jones, J. P., and Christensen, H. I. Navigation using range images on a mobile robot. Robotics and Autonomous Systems 10 (1992), 147--160. [ bib ]
[385] Madsen, C. B., Kirkeby, N. O. S., and Christensen, H. I. A graph based approach to 3d qualitative scene modelling. In Proceedings of the 7th Scandinavian Conference on Image Analysis (Aug. 1991), P. Johansen and S. Olsen, Eds., vol. 1, IAPR, Pattern Recognition Society of Denmark, pp. 324--337. [ bib ]
[386] Knudsen, C. B., and Christensen, H. I. On methods for efficient pyramid construction. In Proceedings of the 7th Scandinavian Conference on Image Anal (Aug. 1991), P. Johansen and S. Olsen, Eds., vol. 1, IAPR, Pattern Recognition Society of Denmark, pp. 29--39. [ bib ]
[387] Andersen, C. S., , Sørensen, J. J., and Christensen, H. I. An analysis of three depth recovery techniques. In Proceedings of the 7'th Scandinavian Conference on Image Analysis. (Aug. 1991), P. Johansen and S. Olsen, Eds., vol. 1, Pattern Recognition Society of Denmark ., pp. 114--126. [ bib ]
[388] Granum, E., and Christensen, H. I. Basic control issues in a continuously operating vision system. In Proc. ESPRIT BR Workshop on Control of Perception in Active Vision, 2nd ECCV (Apr. 1990). [ bib ]
[389] Granum, E., and Christensen, H. I. Dynamic robot vision. In Traditional and Non-Traditional Robotic Sensors., T. Henderson, Ed., vol. 63 of NATO ASI Series F. Springer Verlag, Mar. 1990, pp. 57--71. [ bib ]
[390] Christensen, H. I. Aspects of Real-Time Image Sequence Analysis. PhD thesis, Aalborg University, Aug. 1989. [ bib ]
[391] Christensen, H. I. Concurrent processing for real time motion detection. In Proceedings of the 6th Scandinavian Conference on Image Analysis (June 1989), M. Pietkäinen, Ed., vol. II, Pattern Recognition Society of Finland, pp. 1164 -- 1171. [ bib ]
[392] Christensen, H. I. Concurrent spatio-temporal image analysis. In Proc. Fourth Conference on Concurrent Hypercube Computers (May 1989), ACM, pp. 991--994. [ bib ]
[393] Christensen, H. I., and Jones, J. P. Concurrent multi-resolution image analysis. In Proc. Fourth Conference on Hypercube Concurrent Computers and Applications (May 1989), ACM, pp. 1031--1038. [ bib ]
[394] Granum, E., and Christensen, H. I. On principles of motion analysis in real time. In Image Processing II. Proceedings of SPIE Topical Conference on Image Processing, Hamburg, 1988 (1989), P. J. S. Hutzler and A. Oosterlinck, Eds., vol. 1027, SPIE-The International Society for Optical Engineering, pp. 113--120. [ bib ]
[395] Granum, E., and Christensen, H. I. Methods for real-time motion analysis. In Proc. 2nd Hungarian Workshop on Image Analysis (June 1988), Hungarian Academy of Science, pp. 95--107. [ bib ]
[396] Christensen, H. I., and Granum, E. On multi scale motion analysis. In Proceedings fra NOBIM-konferansen 1988 (June 1988), Rapport, Norsk Regnesentral, pp. 83--87. [ bib ]
[397] Christensen, H. I., and Granum, E. On Token-Matching in Real-Time Motion Analysis, vol. 301 of LNCS. Springer Verlag, Heidelberg, Mar. 1988, pp. 448--457. [ bib ]
[398] Christensen, H. I. Monitoring moving objects in real-time. M.Sc. thesis, Aalborg University, Aalborg, Denmark, June 1987. [ bib ]

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