Arun Srivatsan Rangaprasad


I am a researcher at Apple, where I develop algorithms for augmented and virtual reality systems. I have over 10 years of experience in research, with a focus on computer vision, machine learning, and robotics. I have a proven track record of taking projects from concept to completion by solving challenging problems with innovative solutions.

Specialities : Computer vision  /  Deep learning  /  Point cloud registration  /  3D reconstruction  /  Data encryption and encoding  /  Color science  /  SLAM  /  Classical machine learning  /  Sensor design and calibration  

Bio

Prior to joining Apple, I did my postdoc at the Robotics Institute in Carnegie Mellon University, where I explored deep learning techniques for 3D reconstruction, pose estimation and tracking. This research built on my PhD thesis work on probabilistic approaches for pose estimation. My research finds application in augmented reality, situational awareness in robotic surgery as well as manufacturing. In 2017, I was awarded a fellowship by the Centre for Machine Learning and Health.

In my Masters research, I was involved in the design, development and analysis of a novel parallel manipulator robot platform. I received the gold medal in 2012 from the Indian Institute of Technology Madras.

I also have an active interest in product development. I had a brief stint developing a product called Tangle , that keeps earphones from entangling. We ran an Indiegogo campaign and sold the product to 18 countries.


Email: rarunsrivatsan[at]gmail.com

CV  /  Thesis  /  Google Scholar / 
GitHub  /  LinkedIn

Projects

Algorithms for Augmented and Virtual Reality

Working on various computer vision and machine learning algorithms for augmented and virtual reality. These algorithms find application in iPhones, iPads and the Apple Vision Pro. Seamlessly blending the physical world with digital content can be a powerful tool for a variety of tasks, including productivity, mindfulness, creativity, gaming, and entertainment.
News | Video

App Clip Codes

An App Clip is a lightweight version of your app that lets people perform everyday tasks quickly, without downloading and installing your app. The easiest way to launch an App Clip is by scanning an App Clip Code. Its distinct design is immediately recognizable, and people trust it to offer a fast, secure way to launch your App Clip.
We designed the App Clip Code to be more secure than conventional QR codes and offer superior scanning performance. App Clip Codes can also be used as spatial anchors for augmented reality applications.

App Clip Codes were announced in WWDC 2020 and the scanning has been supported by all iOS devices since 2020. App Clip Codes have been widely adopted by several companies around the world including Exxon, Macys, Panera Bread, etc.                           
Link

Deep learning for Point Cloud Registration

MaskNet: A Fully-Convolutional Network to Estimate Inlier Points
Vinit Sarode, Animesh Dhagat, R. Arun Srivatsan, Nicolas Zevallos, Simon Lucey and Howie Choset
In proceedings of IEEE International Conference on 3D Vision(3DV), 2020.                           
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Correspondence Matrices are Underrated
Tejas Zodage, Rahul Chakwate, Vinit Sarode, R. Arun Srivatsan, and Howie Choset
In proceedings of IEEE International Conference on 3D Vision(3DV), 2020.                           
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PCRNet: Point Cloud Registration Network using PointNet Encoding
Vinit Sarode, Xueqian Li, Hunter Goforth, Yasuhiro Aoki, R. Arun Srivatsan, Simon Lucey and Howie Choset
arXiv preprint arXiv:1908.07906, 2019.                           
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PointNetLK: Robust & Efficient Point Cloud Registration using PointNet
Hunter Goforth, Yasuhiro Aoki, R. Arun Srivatsan and Simon Lucey
In proceedings of IEEE conference on Computer Vision and Pattern Recognition (CVPR), 2019.                           
PDF | Video | Code

Learning for Visual Place Recognition

MRS-VPR: a multi-resolution sampling based global visual place recognition method
Peng Yin, R. Arun Srivatsan, Yin Chen, Xueqian Li, Hongda Zhang, Lingyun Xu, Lu Li, Zhenzhong Jia, Jiamin Ji and Yuqing He
In proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 2019.                           
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A Multi-Domain Feature Learning Method for Visual Place Recognition
Peng Yin, Lingyun Xu, Xueqian Li, Yin Chen, Yingli Li, R. Arun Srivatsan, Lu Li, Jiamin Ji and Yuqin He
In proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 2019.                           
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Probabilistic Approaches to Pose Estimation

For more information click here.

Globally optimal registration of noisy point clouds
R. Arun Srivatsan, Tejas Zodage and Howie Choset
arXiv preprint arXiv:1908.08162, 2019.                           
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Probabilistic Pose Estimation Using a Bingham Distribution-Based Linear Filter
R. Arun Srivatsan, Mengyun Xu, Nicolas Zevallos and Howie Choset
in the International Journal of Robotics Research (IJRR), vol. 37, 13-14: pp. 1610-1631, June 2018.                           
PDF | Code

Bingham Distribution-Based Linear Filter for Online Pose Estimation
R. Arun Srivatsan, Mengyun Xu, Nicolas Zevallos and Howie Choset
in proceedings of Robotics: Science and Systems (RSS), MIT, Boston, 2017.                           
PDF | Video

Estimating SE(3) elements using a dual-quaternion based linear Kalman filter
R. Arun Srivatsan , Gillian T. Rosen, Feroze M. Naina and Howie Choset
in the Proceedings of Robotics Science and Systems (RSS), Michigan, USA, June 2016.
PDF | Video| Code

Registration with a small number of sparse measurements
R. Arun Srivatsan, Nicolas Zevallos, Prasad Vagdargi and Howie Choset
International Journal of Robotics Research (IJRR), 2019.
PDF                           

Sparse Point Registration
R. Arun Srivatsan, Prasad Vagdargi and Howie Choset
in proceedings of International Symposium on Robotics Research (ISRR), 2017.
PDF | Video

Multiple Start Branch and Prune Filtering Algorithm for Nonconvex Optimization
R. Arun Srivatsan and Howie Choset
in proceedings of the Workshop on the Algorithmic Foundations of Robotics (WAFR), San Francisco, USA, December 2016.                           
PDF | Video


Approaches for Complementary Situational Awareness in Minimially Invasive Surgeries

For more information click here.

Complementary Model Update: A Method for Simultaneous Registration and Stiffness Mapping in Flexible Environments
R. Arun Srivatsan, Elif Ayvali, Long Wang, Rajarshi Roy, Nabil Simaan and Howie Choset
In the proceedings of the International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, May 2016.
PDF | Video

Simultaneous Registration and Stiffness mapping of a Flexible Environment using Stiffness and Geometric Prior
R. Arun Srivatsan, Long Wang, Elif Ayvali, Nabil Simaan, and Howie Choset
in the proceedings of the Hamlyn symposium on Medical Robotics, UK, June 2016.
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Multimodal Approach to Registration Using Stereo Imaging and Contact Sensing
Prasad Vagdargi, R. Arun Srivatsan, Nicolas Zevallos, Feroze M. Naina and Howie Choset
in Robotics: Science and Systems (RSS), Workshop on 'Revisiting Contact - Turning a problem into a solution', 2017.                          
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Registering Surgical Tool to a Soft Body using Mechanical Palpation
R. Arun Srivatsan, Rajarshi Roy, Long Wang, Nabil Simaan, and Howie Choset
Tech. report CMU-RI-TR-13, Robotics Institute, Carnegie Mellon University, June, 2015.              
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Hand-held stiffness measurement device for tissue analysis
Tejas Zodage, Arkadeep N Chaudhury, R. Arun Srivatsan, Nicolas Zevallos and Howie Choset
in the proceedings of the Hamlyn symposium on Medical Robotics, UK, June 2019.                          

Tissue Stiffness Mapping Strategies

Trajectory-Optimized Sensing for Active Search of Tissue Abnormalities in Robotic Surgery
Hadi Salman, Elif Ayvali, R. Arun Srivatsan, Yifei Ma, Nicolas Zevallos, Rashid Yasin, Long Wang, Nabil Simaan and Howie Choset
In the proceedings of the International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 2018.
PDF |Code | Video

Using Bayesian Optimization to Guide Probing of a Flexible Environment for Simultaneous Registration and Stiffness Mapping
Elif Ayvali, R. Arun Srivatsan, Long Wang, Rajarshi Roy, Nabil Simaan, and Howie Choset
the proceedings of the International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, May 2016.                           
PDF | Video

Augmented Reality for Surgical Applications

A Real-time Augmented Reality Surgical System for Overlaying Stiffness Information
Nicolas Zevallos, R. Arun Srivatsan, Hadi Salman, Lu Li, Jianing Qian, Saumya Saxena, Mengyun Xu, Kartik Patath and Howie Choset
in proceedings of Robotics: Science and Systems (RSS), Pittsburgh, PA, 2018.
PDF | Code | Video

A surgical system for automatic registration, stiffness mapping and dynamic image overlay
Nicolas Zevallos, R. Arun Srivatsan, Hadi Salman, Lu Li, Jianing Qian, Saumya Saxena, Mengyun Xu, Kartik Patath and Howie Choset
in proceedings of 2018 International Symposium on Medical Robotics (ISMR), Atlanta, GA, 2018. (Best paper finalist)                          
PDF | Video

Dynamic Texture Mapping of 3D models for Stiffness Map Visualization
Kartik Patath, R. Arun Srivatsan, Nicolas Zevallos and Howie Choset
workshop on medical imaging, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017.                          
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Miniature Force Sensor Development

Development of an Inexpensive Tri-axial Force Sensor for Minimally Invasive Surgery
Lu Li, Bocheng Yu, Chen Yang, Prasad Vagdargi, R. Arun Srivatsan and Howie Choset
in proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017.
PDF | Video

BodySLAM for medical snake robot

For more information click here.

Using Lie algebra for shape estimation of medical snake robots
R. Arun Srivatsan, Matthew Travers and Howie Choset
in the proceedings of the 27th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Chicago, USA, September 2014.                           
PDF | Video1 | Video2

Deep Q Reinforcement Learning for Autonomous Navigation of Surgical Snake Robot in Confined Spaces
Stam Athiniotis, R. Arun Srivatsan and Howie Choset
in the proceedings of the Hamlyn symposium on Medical Robotics, UK, June 2019.


Kinematics, design and analysis of parallel manipulators

For more information click here.

Computation of the safe working zones of parallel manipulators
Murali Karnam, Aravind Baskar, R. Arun Srivatsan, and Sandipan Bandyopadhyay
accepted for publication in Robotica, 2019.

Determination of the safe working zone of a parallel manipulator
R. Arun Srivatsan, and Sandipan Bandyopadhyay
Proceedings of the 6th International Workshop of Computational Kinematics (CK), May 2013, Series: Mechanisms and Machine Science, Volume 15.
PDF

On the position kinematic analysis of MaPaMan: a reconfigurable three-degrees-of-freedom spatial parallel manipulator
R. Arun Srivatsan, and Sandipan Bandyopadhyay
Mechanism and Machine Theory, Volume 62, Pages150-165, 2013, DOI 10.1016/j.mechmachtheory.2012.11.008
PDF | Video

Analysis of the degrees-of-freedom of spatial parallel manipulators in regular and singular configurations
R. Arun Srivatsan, Sandipan Bandyopadhyay and , Ashitava Ghosal
Mechanism and Machine Theory, Volume 69, November 2013, Pages 127-141.
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Analysis of constraint equations and their singularities
R. Arun Srivatsan and Sandipan Bandyopadhyay
in the proceedings of 14th International Symposium on Advances in Robot Kinematics (ARK), Slovenia, June 2014.
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Coupler-curve synthesis of a planar four-bar mechanism using a genetic algorithm based optimization method
Jaideep Badduri, R. Arun Srivatsan, G. Saravana Kumar and Sandipan Bandyopadhyay
in the proceedings of the 9th International Conference on Simulated Evolution And Learning (SEAL), December 2012, Volume 7673, pp 460-469, DOI 10.1007/978-3-642-34859-4_46.
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Coupler-curve synthesis via multi-objective optimisation using NSGA-II
Jaideep Badduri, R. Arun Srivatsan, G. Saravana Kumar and Sandipan Bandyopadhyay
In proceedings of iNaCoMM, December 2013.
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Computational geometry

Analytical Determination of the Proximity of Two Right-circular Cylinders in Space
Saurav Agarwal, R. Arun Srivatsan, and Sandipan Bandyopadhyay
ASME. J. Mechanisms Robotics. 2016; 8(4):041010-041010-10. doi:10.1115/1.4032211.
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An analytical formulation for finding the proximity of two arbitrary cylinders in space
R. Arun Srivatsan, and Sandipan Bandyopadhyay
in the Proceedings of the 1st International Conference on Advances in Robotics (AIR), July 2013.
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Minimum area enclosure and alpha hull of a set of freeform planar closed curves
A. V. Vishwanath, R. Arun Srivatsan, and M. Ramanathan
Computer-Aided Design, Volume 45, Issue 3, 2013, Pages 751–763, DOI 10.1016/j.cad.2012.12.001
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