Research

Imitation Learning/Learning from Demonstration/Model Learning

This research thrust is developing novel methods for imitation learning using model learning for path and motion planning. Our idea is to design learning algorithms that create re-usable models (mostly in the form of differential equations) with embedded dynamical system properties.

Sample publications:

  • I. Salehi, G. Yao, A. P. Dani, “Active Sampling based Safe Identification of Dynamical System using Extreme Learning Machines and Barrier Certificates“, IEEE International Conference on Robotics and Automation, 2019.
  • H. Ravichandar, A. P. Dani, “Learning Position and Orientation Dynamics from Demonstrations via Contraction Analysis”, Autonomous Robots, May 2018, DOI: 10.1007/s10514-018-9758-x
  • P. K. Thota, H. Ravichandar, A. P. Dani, “Learning and Synchronization of Movement Primitives for Bimanual Manipulation Tasks”, IEEE Conference on Decision and Control, 2016.
  • H. Ravichandar, A. P. Dani, “Learning Contracting Nonlinear Dynamics from Human Demonstrations for Robot Motion Planning”, ASME Dynamics, Systems and Control Conference 2015 – Best Robotics Student Paper Award
  • H. Ravichandar, P. K. Thota, A. P. Dani, “Learning Periodic Motions from Human Demonstrations using Transverse Contraction Analysis”, IEEE American Control Conference, 2016.

Human-Robot Collaboration

This research is developing methods for human intention estimation using sensor fusion, information fusion, modeling of soft information, and task prediction models.

Sample Publications:

  • H. Ravichandar, A. Kumar, A. P. Dani, K. R. Pattipati, “Learning and Predicting Sequential Tasks using Recurrent Neural Networks and Multiple Model Filtering”, AAAI Symposium on Shared Autonomy in Research and Practice, 2016, pp: 331-337.
  • H. Ravichandar, A. P. Dani, “Human Intention Inference using E-M Algorithm with Online Learning”, IEEE Transactions on Automation Science and Engineering, 2016, DOI: 10.1109/TASE.2016.2624279.
  • H. Ravichandar, A. Kumar, A. P. Dani, “Bayesian Human Intention Inference Through Multiple Model Filtering with Gaze-based Priors”, IEEE International Conference on Information Fusion, 2016.
  • H. Ravichandar, A. P. Dani, ‘Human Intention Inference using Interacting Multiple Model Filtering’, IEEE International Conference on Multisensor Fusion and Information Integration for Intelligent Systems, 2015.

GPS-denied Visual-Inertial Navigation

This research deals with designing nonlinear estimation algorithms for simultaneous localization and mapping (SLAM), 3D range estimation, object shape estimation using camera sensor.

Sample publications:

  • D. Chwa, A.P. Dani, and W. E. Dixon, “Range and Motion Estimation of Moving Objects using a Monocular Camera”, IEEE Transactions on Control Systems Technology, DOI: 10.1109/TCST.2015.2508001, 2015.
  • J. Yang, A. P. Dani, S.-J. Chung, S. Hutchinson, “Vision-based Localization and Robot-centric Mapping in Riverine Environments”, Journal of Field Robotics, DOI: 10.1002/rob.21606, 2015.
  • A.P. Dani, N. Fischer, and W. E. Dixon, “Single Camera Structure and Motion Estimation”, IEEE Transactions on Automatic Control, vol 57, No. 1, pp. 241-246, 2012.
  • A.P. Dani, N. Fischer, Z. Kan, and W. E. Dixon, “Globally Exponentially Convergent Robust Observer for Vision-based Range Estimation”, Mechatronics, Special Issue on Visual Servoing, Vol. 22, No. 4, pp. 381-389, 2012.
  • A. P. Dani, G. Panahandeh, S.-J. Chung, S. Hutchinson, “Image-moments for higher-level features based navigation”, IEEE/RSJ International Conference on Intelligent Robots & Systems, 2013, pp. 602-609.
  • J. Yang, A. P. Dani, S.-J. Chung, S. Hutchinson, “Observer Design via Hybrid Contraction Analysis for UAS Navigation in Riverine Environments”, AIAA Guidance, Navigation, and Control (GNC), 2013.
  • A. P. Dani, G. Panahandeh, S.-J. Chung, S. Hutchinson, “Image-moments for higher-level features based navigation”, IEEE/RSJ International Conference on Intelligent Robots & Systems, 2013, pp. 602-609.
  • J. Yang, A. P. Dani, S.-J. Chung, S. Hutchinson, “Observer Design via Hybrid Contraction Analysis for UAS Navigation in Riverine Environments”, AIAA Guidance, Navigation, and Control (GNC), 2013.

Image-based Tracking and Fusion

This research is about designing image-based robust tracking algorithms along with sensor fusion of camera and inertial measurement unit (IMU).

Sample publications:

  • G. Yao, M. Williams, A. P. Dani, “Gyro-aided Visual Tracking Using Iterative Earth Mover’s Distance”, IEEE International Conference on Information Fusion, 2016. Best Student Paper Award – 2nd runner up.
  • H. Ravichandar, A. P. Dani, “Gyro-aided Image-Based Tracking using Mutual Information Optimization and User Inputs”, IEEE International Conference on Systems, Man and Cybernetics, 2014.
  • A. P. Dani, M. McCourt, J. W. Curtis, S. Mehta, “Information Fusion in Human-Robot Collaboration using Neural Network Representation”, IEEE Systems, Man, Cybernetics Conference, 2014, pp.2114-2120.

 


Gait Estimation in Walking Restoration

This work is about using estimation tools for rehabilitation applications. This work is a joint collaboration with Prof. Nitin Sharma of University of Pittsburgh.

Relevant publications:

  • A. P. Dani, N. Sharma, “A Discrete-time Nonlinear Estimator for an Orthosis-aided Gait”, ASME Dynamics Systems and Control Conference, 2014, paper no. DSCC2014-6161, pp. V001T04A003.
  • N. Sharma, A. P. Dani, “Nonlinear estimation of gait kinematics during functional electric stimulation and orthosis-based walking”, American Controls Conference, 2014, pp. 4778-4783.