GT @ ICRA 2023


The largest and most prestigious event of the year in the Robotics and Automation calendar, 2023 IEEE International Conference on Robotics and Automation (ICRA) will bring together the world's top academics, researchers, and industry representatives. GT will have a large, cross-discipline group of amazing faculty and student researchers presenting at ICRA 2023.


Accepted Papers

Tuesday, May 30


Modeling and Inertial Parameter Estimation of Cart-Like Nonholonomic Systems Using a Mobile Manipulator | Learning for Control II
Sergio Aguilera, Muhammad Ali Murtaza, Jonathan Rogers, Seth Hutchinson

Hybrid SUSD-Based Task Allocation for Heterogeneous Multi-Robot Teams | Multi-Robot Systems I
Shengkang Chen, Tony X. Lin, Said Al-Abri, Ronald Arkin and Fumin Zhang

Force/Torque Sensing for Soft Grippers Using an External Camera | Soft Robots II
Jeremy Collins, Patrick Grady, Charles C. Kemp

GPF-BG: A Hierarchical Vision-Based Planning Framework for Safe Quadrupedal Navigation | Vision Based Navigation I
Shiyu Feng, Ziyi Zhou, Justin Smith, Maxwell Asselmeier, Ye Zhao, Patricio Vela

Intermittent Diffusion Based Path Planning for Heterogeneous Groups of Mobile Sensors in Cluttered Environments | Motion and Path Planning I
Christina Frederick, Haomin Zhou, Frank Crosby

A Multi-Step Dynamics Modeling Framework for Autonomous Driving in Multiple Environments | Integrated Planning and Learning & Award Finalist II
Jason Gibson, Bogdan Vlahov, David D Fan, Patrick Spieler, Daniel Pastor, Ali-akbar Agha-mohammadi, Evangelos Theodorou

Communication-Critical Planning Via Multi-Agent Trajectory Exchange | Multi-Robot Systems II
Nathaniel Glaser, Zsolt Kira

LES: Locally Exploitative Sampling for Robot Path Planning | Motion and Path Planning I
Sagar Joshi, Seth Hutchinson, Panagiotis Tsiotras

ViNL: Visual Navigation and Locomotion Over Obstacles | Vision Based Navigation I
Simar Kareer, Naoki Yokoyama, Dhruv Batra, Sehoon Ha, Joanne Truong

Learning Deep Neural Network Controller for Path Following of Unicycle Robots | Deep Learning and Neural Networks in Robotics
Priyabrata Saha, Luis Guerrero-Bonilla, Magnus Egerstedt, Saibal Mukhopadhyay

Generalizable Pose Estimation Using Implicit Scene Representations | Pose Estimation
Vaibhav Saxena, Kamal Rahimi Malekshan, Linh Tran, Yotto Koga

AeriaLPiPS: A Local Planner for Aerial Vehicles with Geometric Collision Checking | Vision Based Navigation II
Justin Smith, Patricio Vela

Real-Time Solutions to Multimodal Partially Observable Dynamic Games | Optimization and Optimal Control
Oswin So, Paul Drews, Thomas Balch, Velin Dimitrov, Guy Rosman, Evangelos Theodorou

MVTrans: Multi-View Perception of Transparent Objects | Perception for Grasping and Manipulation II
Yi Ru Wang, Yuchi Zhao, Haoping Xu, Sagi Eppel, Alan Aspuru-Guzik, Florian Shkurti, Animesh Garg

BITS: Bi-Level Imitation for Traffic Simulation | Imitation Learning
Danfei Xu, Yuxiao Chen, Boris Ivanovic, Marco Pavone

Constraint Manifolds for Robotic Inference and Planning | Optimization and Optimal Control
Yetong Zhang, Fan Jiang, Gerry Chen, Varun Agrawal, Adam Rutkowski, Frank Dellaert

Guided Conditional Diffusion for Controllable Traffic Simulation | Intelligent Transportation Systems II
Ziyuan Zhong, Davis Rempe, Danfei Xu, Yuxiao Chen, Sushant Veer, Tong Che, Baishakhi Ray, Marco Pavone

Wednesday, May 31


Keypoint-GraspNet: Keypoint-Based 6-DoF Grasp Generation from the Monocular RGB-D Input | Grasping and Manipulation II
Yiye Chen, Yunzhi Lin, Ruinian Xu, Patricio Vela

Information-Theoretic Abstraction of Semantic Octree Models for Integrated Perception and Planning | Probability and Statistical Methods
Daniel Larsson, Arash Asgharivaskasi, Jaein Lim, Nikolay Atanasov, Panagiotis Tsiotras

Fast-Grasp'D: Dexterous Multi-Finger Grasp Generation through Differentiable Simulation | Grasping and Manipulation I
Dylan Turpin, Tao Zhong, Shutong Zhang, Guanglei Zhu, Eric Heiden, Miles Macklin, Stavros Tsogkas, Sven Dickinson, Animesh Garg

Modeling of a Robotic Transcatheter Delivery System | Medical Robotics I
Namrata Unnikrishnan Nayar, Ronghuai Qi, Jaydev P. Desai

Self-Supervised Learning of Action Affordances As Interaction Modes | Learning Methods
Liquan Wang, Nikita Dvornik, Rafael Dubeau, Mayank Mittal, Animesh Garg

Risk-Aware Model Predictive Path Integral Control Using Conditional Value-At-Risk | Planning under Uncertainty II
Ji Yin, Zhiyuan Zhang, Panagiotis Tsiotras

Thursday, June 1


Deep IMU Bias Inference for Robust Visual-Inertial Odometry with Factor Graphs | SLAM and Navigation
Russell Buchanan, Varun Agrawal, Marco Camurri, Frank Dellaert, Maurice Fallon

A Hybrid Cable-Driven Robot for Non-Destructive Leafy Plant Monitoring and Mass Estimation Using Structure from Motion | Agricultural Robotics and Automation II
Gerry Chen, Venkata Harsh Suhith Muriki, Andrew Sharkey, Cedric Pradalier, Yongsheng Chen, Frank Dellaert

Nerf2nerf: Pairwise Registration of Neural Radiance Fields | Radiance Fields
Leili Goli, Daniel Rebain, Sara Sabour, Animesh Garg, Andrea Tagliasacchi

Controlling Collision-Induced Aggregations in a Swarm of Micro Bristle-Robots | Swarms and Multi Agent Systems
Zhijian Hao, Siddharth Mayya, Gennaro Notomista, Seth Hutchinson, Magnus Egerstedt, Azadeh Ansari

Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation | Radiance Fields
Yunzhi Lin, Thomas Müller, Jonathan Tremblay, Bowen Wen, Stephen Tyree, Alex Evans, Patricio Vela, Stan Birchfield

Anticipation and Delayed Estimation of Sagittal Plane Human Hip Moments using Deep Learning and a Robotic Hip Exoskeleton | Rehabilitation and Augmentation
Dean Molinaro, Ethan Park, Aaron Young

Pose-Graph SLAM Using Multi-Order Ultrasonic Echoes and Beamforming for Long-Range Inspection Robots | Localization and Mapping V
Othmane-Latif Ouabi, Neil Zeghidour, Nico F. Declercq, Matthieu Geist, Cedric Pradalier

Tendon-Driven Soft Robotic Gripper with Integrated Ripeness Sensing for Blackberry Harvesting | Agricultural Robotics and Automation II
Alex Qiu, Claire Young, Anthony Gunderman, Milad Azizkhani, Yue Chen, Ai-Ping Hu

Synthetic-To-Real Domain Adaptation for Action Recognition: A Dataset and Baseline Performances | Data Sets II
Arun Reddy, Ketul Shah, William Paul, Rohita Mocharla, Judy Hoffman, Kapil Katyal, Dinesh Manocha, Celso de Melo, Rama Chellappa

ProgPrompt: Generating Situated Robot Task Plans Using Large Language Models | AI-Enabled Robots
Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, Animesh Garg

Data-Driven Optimal Control under Safety Constraints Using Sparse Koopman Approximation | Safety and Trustworthy Robotics I
Hongzhe Yu, Joseph Moyalan, Umesh Vaidya, Yongxin Chen



Animal Quad for Workshop


Agile Movements: Animal Behavior, Biomechanics, and Robot Devices

The workshop focuses on agile movements, ranging from natural animal behaviors to robot motions as a result of both mechanism design and control. Agile movements have been reported in many animals and robots, but there still lacks a comprehensive discussion on the essence of agility, especially among researchers from various areas such as roboticists, biomechanics experts, biologists, and physicists. This workshop provides a platform for researchers, especially early career researchers, with different backgrounds to interact, and expects to attract participants who are non-regulars to robotics conferences. The goal of this workshop is to identify the challenges and opportunities of understanding and improving robotic agility from a diverse range of areas, including biology, biomechanics, mechanism design, and control. Such multidisciplinary cooperation will facilitate the robot deployment to the real world with complex unstructured environments and the creation of new directions for the fields, thus reinforcing the originality and diversity of ICRA 2023.

The topics of interest include but are not limited to the following:

Agile motion in Animals/Robots | Appendages | Bio-inspired Robots | Biomechanics | Biomimetic & Soft Materials | Mechanical Design & Manufacturing | Natural/Passive Dynamics | Neuroscience | Physical Modelling | Planning, Learning, & Control for Agile Movements | Sensor & Actuators

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