Sudharshan Suresh | Suddhu

suddhu [at] cmu [dot] edu

I'm a PhD student in the Robotics Institute at Carnegie Mellon University, where I work with Michael Kaess in the Robot Perception Lab. I'm interested in statistical methods for robot perception, state-estimation, and mapping. Currently, I work on inference methods for robot manipulators to comprehend the world.

I completed my Masters in Robotics at CMU working with Michael Kaess on visual localization and active exploration for AUVs (thesis). Prior to that, I worked with Red Whittaker on state-estimation for lunar rovers, and spent time at IISc Bangalore working on visual understanding. In my undergrad, I majored in Controls and Instrumentation at NIT Trichy.

CV / Scholar / RI webpage / Github

Research

	Efficient shape mapping through dense touch and vision S. Suresh, Z. Si, J. Mangelson, W. Yuan, and M. Kaess [submitted] IEEE Intl. Conf. on Robotics and Automation, ICRA, May 2022 arXiv / website / video Can we efficiently reconstruct household objects with touch and vision? We harness the GelSight sensor and a depth-camera for 3-D shape perception, as inference on a spatial graph informed by a Gaussian process.
	Tactile SLAM: Real-time inference of shape and pose from planar pushing S. Suresh, M. Bauza, K.-T. Yu, J. Mangelson, A. Rodriguez, and M. Kaess IEEE Intl. Conf. on Robotics and Automation, ICRA, May 2021 [Finalist for the 2021 IEEE ICRA Best Paper Award in Service Robotics] arXiv / website / presentation ICRA '20 ViTac workshop: Closing the Perception-Action Loop with Vision and Tactile Sensing pdf / presentation Can we estimate object shape and pose in real-time through purely tactile sensing? We demonstrate this for planar pushing, combining Gaussian process implicit surfaces with factor-graph based inference.
	Active SLAM using 3D submap saliency for underwater volumetric exploration S. Suresh, P. Sodhi, J. Mangelson, D. Wettergreen, and M. Kaess IEEE Intl. Conf. on Robotics and Automation, ICRA, May 2020 pdf / video How do you balance volumetric exploration and pose uncertainty in exploration? We combine a sampling-based planner, deformable pose graph, and a 3D saliency metric to explore a 3D underwater volume.
	Through-water stereo SLAM with refraction correction for AUV localization S. Suresh, E. Westman, and M. Kaess IEEE Robotics and Automation Letters (RA-L), presented at ICRA 2019, Jan 2019 pdf / video How can you incorporate refraction into water-to-air visual SLAM? We present a novel method inspired by multimedia photogrammetry for underwater localization.
	Localized imaging and mapping for underwater fuel storage basins J. Hsiung, A. Tallaksen, L. Papincak, S. Suresh, H. Jones, W. L. Whittaker, and M. Kaess Proceedings of the Symposium on Waste Management, Phoenix, Arizona, Mar 2018 pdf / slides / video What's the ideal sensor suite for underwater dense mapping? We build and demonstrate an inspection solution comprising of a stereo camera, IMU, standard + structured lighting, and depth sensor.
	Optical kinematic state estimation of planetary rovers using downward-facing monocular fisheye camera S. Suresh , E. Fang, and W. L. Whittaker Robotics Institute Summer Scholars Working Paper Journal, Nov 2016 Camera-Only Kinematics for Small Lunar Rovers E. Fang, S. Suresh, and W. L. Whittaker Annual Meeting of the Lunar Exploration Analysis Group, Nov 2016 pdf / video / poster Is it possible to track a lunar rover's kinematic state through self-perception? With a downward-facing fisheye lens, we estimate the Autokrawler's kinematics on rugged terrain.
	Object category understanding via eye fixations on freehand sketches R. K. Sarvadevabhatla, S. Suresh and R. V. Babu IEEE Transactions on Image Processing (TIP), May 2017 paper / website / dataset Can we better understand free-hand sketches through human gaze fixations? We collect the SketchFix-160 dataset and investigate visual saliency to reveal multi-level consistency in sketches.

Other projects

	DeepGeo: photo localization with deep neural network S. Suresh, N. Chodosh, and M. Abello arXiv / github A deep network that beats humans at GeoGuessr, trained on our 50States10K* dataset.*
	Task and motion planning for robotic food preparation S. Suresh, T. Rhodes, M. Abello, and H. Yadav pdf / video 1 / video 2 Hierarchical task and motion planning for a 6-DOF robot arm, to prepare yogurt parfaits!
	Thin structure reconstruction via 3D lines and points S. Suresh and M. Abello poster Reconstructing thin objects in a scene through an SfM pipeline can be hard!
	Factor graph optimization for dynamic parameter estimation S. Suresh, E. Dexheimer, and M. Abello pdf We implement a method for estimation of MAV poses and dynamic parameters during flight.

Last updated: circa Sep 2021

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