Aditya Mandalika

According to our database, Aditya Mandalika authored at least 11 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

GuILD: Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning.

Rosario Scalise, Aditya Mandalika, Brian Hou, Sanjiban Choudhury, Siddhartha S. Srinivasa

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022

Human-Scale Mobile Manipulation Using RoMan.

Chad Kessens, Matthew Kaplan, Trevor Rocks, Philip R. Osteen, John G. Rogers, Ethan Stump, Arnon Hurwitz, Jonathan Fink, Long Quang, Mark Gonzalez, Jaymit Patel, Michael Diblasi, Shiyani Patel, Matthew Weiker, Dilip Patel, Joseph Bowkett, Renaud Detry, Sisir Karumanchi, Larry H. Matthies, Joel Burdick, Yash Oza, Aditya Agarwal, Andrew Dornbush, Dhruv Saxena, Maxim Likhachev, Karl Schmeckpeper, Kostas Daniilidis, Ajinkya Kamat, Aditya Mandalika, Sanjiban Choudhury, Siddhartha S. Srinivasa

Field Robotics, March, 2022

2021

Efficient Robot Motion Planning in Cluttered Environments.

Aditya Mandalika

PhD thesis, 2021

Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning.

Aditya Mandalika, Rosario Scalise, Brian Hou, Sanjiban Choudhury, Siddhartha S. Srinivasa

CoRR, 2021

2020

Posterior Sampling for Anytime Motion Planning on Graphs with Expensive-to-Evaluate Edges.

Brian Hou, Sanjiban Choudhury, Gilwoo Lee, Aditya Mandalika, Siddhartha S. Srinivasa

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019

LEGO: Leveraging Experience in Roadmap Generation for Sampling-Based Planning.

Rahul Kumar, Aditya Mandalika, Sanjiban Choudhury, Siddhartha S. Srinivasa

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Bayesian Policy Optimization for Model Uncertainty.

Gilwoo Lee, Brian Hou, Aditya Mandalika, Jeongseok Lee, Sanjiban Choudhury, Siddhartha S. Srinivasa

Proceedings of the 7th International Conference on Learning Representations, 2019

Generalized Lazy Search for Robot Motion Planning: Interleaving Search and Edge Evaluation via Event-Based Toggles.

Aditya Mandalika, Sanjiban Choudhury, Oren Salzman, Siddhartha S. Srinivasa

Proceedings of the Twenty-Ninth International Conference on Automated Planning and Scheduling, 2019

2018

Sample-Efficient Learning of Nonprehensile Manipulation Policies via Physics-Based Informed State Distributions.

Lerrel Pinto, Aditya Mandalika, Brian Hou, Siddhartha S. Srinivasa

CoRR, 2018

Bayesian Policy Optimization for Model Uncertainty.

Gilwoo Lee, Brian Hou, Aditya Mandalika, Jeongseok Lee, Siddhartha S. Srinivasa

CoRR, 2018

Lazy Receding Horizon A* for Efficient Path Planning in Graphs with Expensive-to-Evaluate Edges.

Aditya Mandalika, Oren Salzman, Siddhartha S. Srinivasa

Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling, 2018