Ashutosh Mishra

Publications

10 peer-reviewed papers, newest first. Author order is as published, with my name in bold; an asterisk marks equal authorship. Each title opens a page with the abstract summary, links and a ready-made citation.

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Accepted, to appear

IEEE iSpaRo2026

Robot-Assisted Deployment and Maintenance of Inflatable Modules for Lunar Habitation: A Field Demonstration

Kentaro Uno*, Shamistan Karimov*, Ashutosh Mishra, Elian Neppel, Hazal Gozbasi, Shreya Santra, Shinichi Kimura, Kazuya Yoshida

IEEE International Conference on Space Robotics (iSpaRo)

MoonBot working alongside the HIDAS inflatable habitat module: inspection during inflation, alignment, final safety locking, and 3D mapping for maintenance, demonstrated on real hardware in the lab and at a lunar analogue site.

* Equal authorship.

IEEE/RSJ IROS2026

Distributed Multi Robot Lunar Cargo Transportation via Phase Decomposed Reinforcement Learning

Ashutosh Mishra, Elian Neppel, Shreya Santra, Antoine Jonquières, Muhammad Athallah Naufal, Kentaro Uno, Kazuya Yoshida

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Lunar cargo transport split into lifting, transportation and placement, each learned as its own policy so several robots can share the load, evaluated in simulation and in field experiments at a JAXA test facility.

Published

2025

IEEE T-FR2025

MoonBot: Modular and On-Demand Reconfigurable Robot Toward Moon Base Construction

Kentaro Uno*, Elian Neppel*, Gustavo H. Diaz*, Ashutosh Mishra*, Shamistan Karimov*, A. Sejal Jain, Ayesha Habib, Pascal Pama, Hazal Gozbasi, Shreya Santra, Kazuya Yoshida

IEEE Transactions on Field Robotics (T-FR)

The MoonBot platform: limbs, wheels and tools that recombine on demand into whichever machine a lunar construction task needs, developed under JST Moonshot Goal 3 and shown in a preliminary field demonstration of lunar infrastructure tasks.

* Equal authorship.

IEEE iSpaRo2025

Multi-Modal Decentralized Reinforcement Learning for Modular Reconfigurable Lunar Robots

Ashutosh Mishra, Shreya Santra, Elian Neppel, Edoardo M. Rossi Lombardi, Shamistan Karimov, Kentaro Uno, Kazuya Yoshida

IEEE International Conference on Space Robotics (iSpaRo)

A decentralized reinforcement learning approach for robots whose morphology changes: each module learns to act on local, multi-modal observation rather than from a central controller, so the same policy set survives reconfiguration.

Best Paper Award in Planetary Robotics, IEEE iSpaRo 2025, Sendai, Japan

IEEE/RSJ IROS2025

Robust and Modular Multi-Limb Synchronization in Motion Stack for Space Robots with Trajectory Clamping via Hypersphere

Elian Neppel, Ashutosh Mishra, Shamistan Karimov, Kentaro Uno, Shreya Santra, Kazuya Yoshida

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Keeping multiple limbs of a space robot synchronized when any of them may be added, removed or delayed, using hypersphere trajectory clamping to bound the motion each limb is allowed to command.

IEEE iSpaRo2025

Designing for Distributed Heterogeneous Modularity: On Software Architecture and Deployment of the MoonBots

Elian Neppel, Shamistan Karimov, Ashutosh Mishra, Gustavo H. Diaz, Hazal Gozbasi, Shreya Santra, Kentaro Uno, Kazuya Yoshida

IEEE International Conference on Space Robotics (iSpaRo)

The software architecture question behind modular hardware: how to deploy and coordinate software across heterogeneous modules that do not know in advance what they will be attached to.

2024

IAC2024

International Lunar University: The Dawn of Interplanetary Education

Adam Hanlon, Alba Badia Rifà, Alejandro J. Garcia Morales, Annemarie Schuite, Ashutosh Mishra, Austin Phillips, and 26 others

International Astronautical Congress (IAC) 2024, IAF Space Exploration Symposium

The International Lunar University proposal from the International Space University Space Studies Program 2024, hosted at NASA Johnson Space Center and Rice University, where I led the project management team and served as lead editor, supervised by Jacob Cohen, Chief Scientist at NASA Ames.

2022

IJRFMCAE2022

Multilayer Perceptron-Random Forest Based Hybrid Machine Learning-Neural Network Model for GaN High Electron Mobility Transistor's Parameter Estimations

Ashutosh Mishra, Samriddhi Raut, Khushwant Sehra, Raghvendra Pratap Singh, Shweta Wadhera, Poonam Kasturi, Geetika Jain Saxena, Manoj Saxena

International Journal of RF and Microwave Computer-Aided Engineering

A hybrid multilayer-perceptron and random-forest model for estimating GaN HEMT device parameters. From my earlier semiconductor device modelling work at the University of Delhi.

2021

2020

Under review and in submission

Listed for completeness. None of these has completed peer review, so please do not cite them as published.