Path planning and navigation inside off-world lava tubes and caves. - Himangshu Kalita; Steven D. Morad; Aaditya Ravindran; Jekan Thangavelautham (PLANS, 2018)

Planning and navigation of climbing robots in low-gravity environments. - Steven D. Morad; Himangshu Kalita; Jekan Thangavelautham (PLANS, 2018)

Path Planning and Navigation Inside Off-World Lava Tubes and Caves. - Himangshu Kalita; Steven D. Morad; Jekan Thangavelautham (CoRR, 2018)

On-Orbit Smart Camera System to Observe Illuminated and Unilluminated Space Objects. - Steven D. Morad; Ravi Teja Nallapu; Himangshu Kalita; Byon Kwon; Vishnu Reddy; Roberto Furfaro; Erik Asphaug; Jekan Thangavelautham (CoRR, 2018)

Coordination and Control of Multiple Climbing Robots in Transport of Heavy Loads through Extreme Terrain. - Himangshu Kalita; Steven D. Morad; Jekan Thangavelautham (CoRR, 2018)

A Spring Propelled Extreme Environment Robot for Off-World Cave Exploration. - Steven D. Morad; Thomas Dailey; Leonard Vance; Jekan Thangavelautham (CoRR, 2019)

Building Small-Satellites to Live Through the Kessler Effect. - Steven D. Morad; Himangshu Kalita; Ravi Teja Nallapu; Jekan Thangavelautham (CoRR, 2019)

Improving Visual Feature Extraction in Glacial Environments. - Steven D. Morad; Jeremy Nash; Shoya Higa; Russell Smith; Aaron Parness; Kobus Barnard (IEEE Robotics Autom. Lett., 2020)

Graph Convolutional Memory for Deep Reinforcement Learning. - Steven D. Morad; Stephan Liwicki; Amanda Prorok (CoRR, 2021)

Embodied Visual Navigation With Automatic Curriculum Learning in Real Environments. - Steven D. Morad; Roberto Mecca; Rudra P. K. Poudel; Stephan Liwicki; Roberto Cipolla (IEEE Robotics Autom. Lett., 2021)

A Framework for Real-World Multi-Robot Systems Running Decentralized GNN-Based Policies. - Jan Blumenkamp; Steven D. Morad; Jennifer Gielis; Qingbiao Li; Amanda Prorok (ICRA, 2022)

Modeling Partially Observable Systems using Graph-Based Memory and Topological Priors. - Steven D. Morad; Stephan Liwicki; Ryan Kortvelesy; Roberto Mecca; Amanda Prorok (L4DC, 2022)

Permutation-Invariant Set Autoencoders with Fixed-Size Embeddings for Multi-Agent Learning. - Ryan Kortvelesy; Steven D. Morad; Amanda Prorok (AAMAS, 2023)

POPGym: Benchmarking Partially Observable Reinforcement Learning. - Steven D. Morad; Ryan Kortvelesy; Matteo Bettini; Stephan Liwicki; Amanda Prorok (ICLR, 2023)

Generalised f-Mean Aggregation for Graph Neural Networks. - Ryan Kortvelesy; Steven D. Morad; Amanda Prorok (NeurIPS, 2023)

Reinforcement Learning with Fast and Forgetful Memory. - Steven D. Morad; Ryan Kortvelesy; Stephan Liwicki; Amanda Prorok (NeurIPS, 2023)

CoViS-Net: A Cooperative Visual Spatial Foundation Model for Multi-Robot Applications. - Jan Blumenkamp; Steven D. Morad; Jennifer Gielis; Amanda Prorok (CoRL, 2024)

Recurrent Reinforcement Learning with Memoroids. - Steven D. Morad; Chris Lu 001; Ryan Kortvelesy; Stephan Liwicki; Jakob N. Foerster; Amanda Prorok (NeurIPS, 2024)

Revisiting Recurrent Reinforcement Learning with Memory Monoids. - Steven D. Morad; Chris Lu 001; Ryan Kortvelesy; Stephan Liwicki; Jakob N. Foerster; Amanda Prorok (CoRR, 2024)

Generalising Multi-Agent Cooperation through Task-Agnostic Communication. - Dulhan Jayalath; Steven D. Morad; Amanda Prorok (CoRR, 2024)

Language-Conditioned Offline RL for Multi-Robot Navigation. - Steven D. Morad; Ajay Shankar; Jan Blumenkamp; Amanda Prorok (CoRR, 2024)