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Iagnemma, Karl
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Publications (10 of 106) Show all publications
Gholami Shahbandi, S., Magnusson, M. & Iagnemma, K. (2018). Nonlinear Optimization of Multimodal Two-Dimensional Map Alignment With Application to Prior Knowledge Transfer. Paper presented at 2018 IEEE International Conference on Robotics and Automation, Brisbane, Australia, May 21-25, 2018. IEEE Robotics and Automation Letters, 3(3), 2040-2047
Open this publication in new window or tab >>Nonlinear Optimization of Multimodal Two-Dimensional Map Alignment With Application to Prior Knowledge Transfer
2018 (English)In: IEEE Robotics and Automation Letters, ISSN 2377-3766, E-ISSN 1949-3045, Vol. 3, no 3, p. 2040-2047Article in journal (Refereed) Published
Abstract [en]

We propose a method based on a nonlinear transformation for nonrigid alignment of maps of different modalities, exemplified with matching partial and deformed two-dimensional maps to layout maps. For two types of indoor environments, over a dataset of 40 maps, we have compared the method to state-of-the-art map matching and nonrigid image registration methods and demonstrate a success rate of 80.41% and a mean point-to-point alignment error of 1.78 m, compared to 31.9% and 10.7 m for the best alternative method. We also propose a fitness measure that can quite reliably detect bad alignments. Finally, we show a use case of transferring prior knowledge (labels/segmentation), demonstrating that map segmentation is more consistent when transferred from an aligned layout map than when operating directly on partial maps (95.97% vs. 81.56%). © 2018 IEEE.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE, 2018
Keywords
mapping
National Category
Robotics
Identifiers
urn:nbn:se:hh:diva-36604 (URN)10.1109/LRA.2018.2806439 (DOI)
Conference
2018 IEEE International Conference on Robotics and Automation, Brisbane, Australia, May 21-25, 2018
Funder
Knowledge Foundation
Available from: 2018-04-12 Created: 2018-04-12 Last updated: 2018-05-02Bibliographically approved
David, J., Valencia, R., Philippsen, R., Bosshard, P. & Iagnemma, K. (2017). Gradient Based Path Optimization Method for Autonomous Driving. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): . Paper presented at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver CB, Canada, Sept. 24-28, 2017 (pp. 4501-4508). [Piscataway, NJ]: IEEE
Open this publication in new window or tab >>Gradient Based Path Optimization Method for Autonomous Driving
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2017 (English)In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), [Piscataway, NJ]: IEEE, 2017, p. 4501-4508Conference paper, Published paper (Refereed)
Abstract [en]

This paper discusses the possibilities of extending and adapting the CHOMP motion planner to work with a non-holonomic vehicle such as an autonomous truck with a single trailer. A detailed study has been done to find out the different ways of implementing these constraints on the motion planner. CHOMP, which is a successful motion planner for articulated robots produces very fast and collision-free trajectories. This nature is important for a local path adaptor in a multi-vehicle path planning for resolving path-conflicts in a very fast manner and hence, CHOMP was adapted. Secondly, this paper also details the experimental integration of the modified CHOMP with the sensor fusion and control system of an autonomous Volvo FH-16 truck. Integration experiments were conducted in a real-time environment with the developed autonomous truck. Finally, additional simulations were also conducted to compare the performance of the different approaches developed to study the feasibility of employing CHOMP to autonomous vehicles. ©2017 IEEE

Place, publisher, year, edition, pages
[Piscataway, NJ]: IEEE, 2017
Series
IEEE International Conference on Intelligent Robots and Systems, E-ISSN 2153-0866
Keywords
Robotics, Intelligent Transportation Systems, Autonomous Vehicle Navigation, Motion and Path Planning
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:hh:diva-34851 (URN)10.1109/IROS.2017.8206318 (DOI)978-1-5386-2682-5 (ISBN)978-1-5386-2681-8 (ISBN)978-1-5386-2683-2 (ISBN)
Conference
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver CB, Canada, Sept. 24-28, 2017
Projects
Cargo-ANTs
Funder
EU, FP7, Seventh Framework Programme, FP7-605598
Available from: 2017-08-31 Created: 2017-08-31 Last updated: 2018-01-25Bibliographically approved
David, J., Valencia, R., Philippsen, R. & Iagnemma, K. (2017). Local Path Optimizer for an Autonomous Truck in a Harbour Scenario. In: : . Paper presented at 11th Conference on Field and Service Robotics (FSR), Zürich, Switzerland, 12-15 September, 2017.
Open this publication in new window or tab >>Local Path Optimizer for an Autonomous Truck in a Harbour Scenario
2017 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Recently, functional gradient algorithms like CHOMP have been very successful in producing locally optimal motion plans for articulated robots. In this paper, we have adapted CHOMP to work with a non-holonomic vehicle such as an autonomous truck with a single trailer and a differential drive robot. An extended CHOMP with rolling constraints have been implemented on both of these setup which yielded feasible curvatures. This paper details the experimental integration of the extended CHOMP motion planner with the sensor fusion and control system of an autonomous Volvo FH-16 truck. It also explains the experiments conducted on the differential-drive robot. Initial experimental investigations and results conducted in a real-world environment show that CHOMP can produce smooth and collision-free trajectories for mobile robots and vehicles as well. In conclusion, this paper discusses the feasibility of employing CHOMP to mobile robots.

Keywords
robotics
National Category
Robotics Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:hh:diva-34850 (URN)
Conference
11th Conference on Field and Service Robotics (FSR), Zürich, Switzerland, 12-15 September, 2017
Projects
Cargo-ANTs
Funder
EU, FP7, Seventh Framework Programme, FP7-605598
Available from: 2017-08-31 Created: 2017-08-31 Last updated: 2019-01-29Bibliographically approved
Bouguelia, M.-R., Gonzalez, R., Iagnemma, K. & Byttner, S. (2017). Unsupervised classification of slip events for planetary exploration rovers. Journal of terramechanics, 73, 95-106
Open this publication in new window or tab >>Unsupervised classification of slip events for planetary exploration rovers
2017 (English)In: Journal of terramechanics, ISSN 0022-4898, E-ISSN 1879-1204, Vol. 73, p. 95-106Article in journal (Refereed) Published
Abstract [en]

This paper introduces an unsupervised method for the classification of discrete rovers' slip events based on proprioceptive signals. In particular, the method is able to automatically discover and track various degrees of slip (i.e. low slip, moderate slip, high slip). The proposed method is based on aggregating the data over time, since high level concepts, such as high and low slip, are concepts that are dependent on longer time perspectives. Different features and subsets of the data have been identified leading to a proper clustering, interpreting those clusters as initial models of the prospective concepts. Bayesian tracking has been used in order to continuously improve the parameters of these models, based on the new data. Two real datasets are used to validate the proposed approach in comparison to other known unsupervised and supervised machine learning methods. The first dataset is collected by a single-wheel testbed available at MIT. The second dataset was collected by means of a planetary exploration rover in real off-road conditions. Experiments prove that the proposed method is more accurate (up to 86% of accuracy vs. 80% for K-means) in discovering various levels of slip while being fully unsupervised (no need for hand-labeled data for training). © 2017 ISTVS

Place, publisher, year, edition, pages
Doetinchem: Elsevier, 2017
Keywords
Unsupervised learning, Clustering, Data-driven modeling, Slip, MSL rover, LATUV rover
National Category
Computer Sciences
Identifiers
urn:nbn:se:hh:diva-35169 (URN)10.1016/j.jterra.2017.09.001 (DOI)2-s2.0-85029811187 (Scopus ID)
Available from: 2017-10-09 Created: 2017-10-09 Last updated: 2018-01-13Bibliographically approved
Gonzalez, R., Byttner, S. & Iagnemma, K. (2016). Comparison of Machine Learning Approaches for Soil Embedding Detection of Planetary Exploration Rovers. In: Proceedings of the 8th ISTVS Americas Conference, Detroit, September 12-14, 2016.: . Paper presented at International Conference of the ISTVS (International Society for Terrain-Vehicle Systems), Detroit, Michigan, USA, 12-14 September, 2016.
Open this publication in new window or tab >>Comparison of Machine Learning Approaches for Soil Embedding Detection of Planetary Exploration Rovers
2016 (English)In: Proceedings of the 8th ISTVS Americas Conference, Detroit, September 12-14, 2016., 2016Conference paper, Published paper (Refereed)
Abstract [en]

This paper analyzes the advantages and limitations of known machine learning approaches to cope with the problem of incipient rover embedding detection based on propioceptive signals. In particular, two supervised learning approaches (Support Vector Machines and Feed-forward Neural Networks) are compared to two unsupervised learning approaches (K-means and Self-Organizing Maps) in order to identify various degrees of slip (e.g. low slip, moderate slip, high slip). A real dataset collected by a single-wheel testbed available at MIT has been used to validate each strategy. The SVM algorithm achieves the best performance (accuracy >95 %). However, the SOM algorithm represents a better solution in terms of accuracy and the need of hand-labeled data for training the classifier (accuracy >84 %).

Keywords
Support Vector Machine (SVM), Feed-forward Neural Network (FF-NN), K-means, Self-Organizing Map (SOM), Mars Science Laboratory (MSL) rover
National Category
Signal Processing Robotics
Identifiers
urn:nbn:se:hh:diva-32049 (URN)
Conference
International Conference of the ISTVS (International Society for Terrain-Vehicle Systems), Detroit, Michigan, USA, 12-14 September, 2016
Note

Funding: NASA

Available from: 2016-09-19 Created: 2016-09-19 Last updated: 2018-03-22Bibliographically approved
David, J., Valencia, R. & Iagnemma, K. (2016). Task Assignment and Trajectory Planning in Dynamic environments for Multiple Vehicles. In: : . Paper presented at RSS 2016 Workshop on Task and Motion Planning, Ann Arbor, Michigan, USA, June 19, 2016.
Open this publication in new window or tab >>Task Assignment and Trajectory Planning in Dynamic environments for Multiple Vehicles
2016 (English)Conference paper, Published paper (Refereed)
Abstract [en]

We consider the problem of finding collision-free trajectories for a fleet of automated guided vehicles (AGVs) working in ship ports and freight terminals. Our solution computes collision-free trajectories for a fleet of AGVs to pick up one or more containers and transport it to a given goal without colliding with other AGVs and obstacles. We propose an integrated framework for solving the goal assignment and trajectory planning problem minimizing the maximum cost overall vehicle trajectories using the classical Hungarian algorithm.To deal with the dynamics in the environment, we refine our final trajectories with CHOMP (Covariant Hamiltonianoptimization for motion planning) in order to trade off between path smoothness and dynamic obstacle avoidance.

Keywords
Multi-robot, task assignment, path planner
National Category
Robotics
Identifiers
urn:nbn:se:hh:diva-31738 (URN)
Conference
RSS 2016 Workshop on Task and Motion Planning, Ann Arbor, Michigan, USA, June 19, 2016
Projects
CargoAnts
Funder
EU, FP7, Seventh Framework Programme, 605598
Available from: 2016-08-10 Created: 2016-08-10 Last updated: 2018-03-22Bibliographically approved
Kim, Y.-J., Cheng, S., Kim, S. & Iagnemma, K. (2013). A Novel Layer Jamming Mechanism with Tunable Stiffness Capability for Minimally Invasive Surgery. IEEE Transactions on robotics, 29(4), 1031-1042
Open this publication in new window or tab >>A Novel Layer Jamming Mechanism with Tunable Stiffness Capability for Minimally Invasive Surgery
2013 (English)In: IEEE Transactions on robotics, ISSN 1552-3098, E-ISSN 1941-0468, Vol. 29, no 4, p. 1031-1042Article in journal (Refereed) Published
Abstract [en]

This paper presents a novel “layer jamming” mechanism that can achieve variable stiffness. The layer jamming mechanism exploits the friction present between layers of thin material, which can be controlled by a confining pressure. Due to the mechanism's hollow geometry, compact size, and light weight, it is well suited for various minimally invasive surgery applications, where stiffness change is required. This paper describes the concept, the mathematical model, and a tubular snake-like manipulator prototype. Various characteristics of layer jamming, such as stiffness and yield strength, are studied both theoretically and experimentally. © IEEE

Place, publisher, year, edition, pages
Piscataway, N.J.: IEEE Press, 2013
Keywords
Layer jamming, minimally invasive surgery (MIS), snake-like manipulator, tunable stiffness
National Category
Robotics
Identifiers
urn:nbn:se:hh:diva-20611 (URN)10.1109/TRO.2013.2256313 (DOI)000322836600017 ()2-s2.0-84882450817 (Scopus ID)
Available from: 2013-01-09 Created: 2013-01-09 Last updated: 2018-03-22Bibliographically approved
Anderson, S. J., Karumanchi, S. B., Iagnemma, K. & Walker, J. M. (2013). The intelligent copilot: A constraint-based approach to shared-adaptive control of ground vehicles. IEEE Intelligent Transportation Systems Magazine, 5(2), 45-54
Open this publication in new window or tab >>The intelligent copilot: A constraint-based approach to shared-adaptive control of ground vehicles
2013 (English)In: IEEE Intelligent Transportation Systems Magazine, ISSN 1939-1390, Vol. 5, no 2, p. 45-54Article in journal (Refereed) Published
Abstract [en]

This work presents a new approach to semi-autonomous vehicle hazard avoidance and stability control, based on the design and selective enforcement of constraints. This differs from traditional approaches that rely on the planning and tracking of paths and facilitates minimally-invasive control for human-machine systems. Instead of forcing a human operator to follow an automation-determined path, the constraint-based approach identifies safe homotopies, and allows the operator to navigate freely within them, introducing control action only as necessary to ensure that the vehicle does not violate safety constraints. This method evaluates candidate homotopies based on restrictiveness rather than traditional measures of path goodness, and designs and enforces requisite constraints on the human's control commands to ensure that the vehicle never leaves the controllable subset of a desired homotopy. This paper demonstrates the approach in simulation and characterizes its effect on human teleoperation of unmanned ground vehicles via a 20-user, 600-trial study on an outdoor obstacle course. Aggregated across all drivers and experiments, the constraintbased control system required an average of 43% of the available control authority to reduce collision frequency by 78% relative to traditional teleoperation, increase average speed by 26%, and moderate operator steering commands by 34%. © 2009-2012 IEEE

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Press, 2013
National Category
Robotics
Identifiers
urn:nbn:se:hh:diva-20610 (URN)10.1109/MITS.2013.2247796 (DOI)000209299100008 ()2-s2.0-84877736298 (Scopus ID)
Note

This material is based on work supported by the US ARO under contract W911NF-11-1-0046 and DARPA DSO under the M3 program.

Available from: 2013-01-09 Created: 2013-01-09 Last updated: 2018-03-22Bibliographically approved
Wiltsie, N., Lanzetta, M. & Iagnemma, K. (2012). A controllably adhesive climbing robot using magnetorheological fluid. In: 2012 IEEE Conference on Technologies for Practical Robot Applications: TePRA 2012. Paper presented at 2012 IEEE International Conference on Technologies for Practical Robot Applications, TePRA 2012, Woburn, MA, USA, 23-24 April, 2012 (pp. 91-96). Piscataway, N.J.: IEEE Press
Open this publication in new window or tab >>A controllably adhesive climbing robot using magnetorheological fluid
2012 (English)In: 2012 IEEE Conference on Technologies for Practical Robot Applications: TePRA 2012, Piscataway, N.J.: IEEE Press, 2012, p. 91-96Conference paper, Published paper (Refereed)
Abstract [en]

The novel adhesive effects of magnetorheological fluid for use in climbing robotics were experimentally measured and compared to existing theoretical models. Contrary to these models, the fluid thickness between two parallel plates was found to have little effect on the adhesive failure strength and a positive effect on time to failure. Target surface roughness was found to have a detrimental effect on pull-off adhesion and a positive effect on shearing loads. A robot capable of adhering to ceilings was designed and shown to be capable of holding 7.3 kPa of adhesive stress in both shear on rough vertical surfaces and normal force on glass sheets, demonstrating a novel form of adhesion on a wide range of surface roughnesses and orientations. © 2012 IEEE.

Place, publisher, year, edition, pages
Piscataway, N.J.: IEEE Press, 2012
Keywords
Adhesives, Magnetic separation, Magnetomechanical effects, Robots, Rough surfaces, Stress, Surface roughness, adhesives, fluids, magnetorheology, mobile robots, surface roughness, adhesive effects, adhesive failure strength, adhesive stress, controllably adhesive climbing robot, fluid thickness, glass sheets, magnetorheological fluid, normal force, parallel plates, pressure 7.3 kPa, pull-off adhesion, rough vertical surfaces, shearing loads, surface orientations, target surface roughness
National Category
Robotics
Identifiers
urn:nbn:se:hh:diva-20831 (URN)10.1109/TePRA.2012.6215660 (DOI)2-s2.0-84863676484 (Scopus ID)978-146730855-7 (ISBN)
Conference
2012 IEEE International Conference on Technologies for Practical Robot Applications, TePRA 2012, Woburn, MA, USA, 23-24 April, 2012
Available from: 2013-01-12 Created: 2013-01-12 Last updated: 2018-03-22Bibliographically approved
Kewlani, G., Crawford, J. & Iagnemma, K. (2012). A polynomial chaos approach to the analysis of vehicle dynamics under uncertainty. Vehicle System Dynamics, 50(5), 749-774
Open this publication in new window or tab >>A polynomial chaos approach to the analysis of vehicle dynamics under uncertainty
2012 (English)In: Vehicle System Dynamics, ISSN 0042-3114, E-ISSN 1744-5159, Vol. 50, no 5, p. 749-774Article in journal (Refereed) Published
Place, publisher, year, edition, pages
Colchester: Taylor & Francis, 2012
National Category
Robotics
Identifiers
urn:nbn:se:hh:diva-20731 (URN)10.1080/00423114.2011.639897 (DOI)000305032800004 ()2-s2.0-84859527453 (Scopus ID)
Available from: 2013-01-13 Created: 2013-01-12 Last updated: 2018-03-22Bibliographically approved

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