Raghav Mishra

Roboticist, Mechatronic Engineer

I’m a PhD student at the University of Sydney, based at the Australian Centre for Robotics and the ARIAM hub. I did my Bachelors/Masters with a major in Mechatronic Engineering at the University of Queensland.

My main interests lie in control and motion planning for robots. I am currently working on generative AI-inspired models for manipulation in harsh environments with complex dynamics and unreliable perception.

Previously, I’ve worked at Emesent, a robotics company working on autonomous inspection and 3D mapping using drones and legged robots. I’ve also interned at CSIRO Robotics and Microsoft AutoML.

Publications

Training-Free Imitation Learning with Closed-Form Diffusion Policies

Raghav Mishra, Ian R. Manchester

arXiv

Diffusion policies in milliseconds, directly from the demonstration dataset and fast inference on a mobile CPU. Plus inference-time neural diffusion policy editing to steer actions or add new demonstrations to the policy

EB-MBD: Emerging-Barrier Model-Based Diffusion for Safe Trajectory Optimization in Highly Constrained

Raghav Mishra, Ian R. Manchester

IEEE International Conference on Robotics & Automation (ICRA), 2026

Inequality constrainted Model-Based Diffusion using interior-point inspired time-varying barrier functions to improve performance in highly constrained environments without using computationally expensive operations like projections.

∂LITE: Differentiable Lighting-Informed Trajectory Evaluation for On-Orbit Inspection

Jack Naylor, Raghav Mishra, Nicholas H Barbara, and Donald G Dansereau

International Aeronautical Conference (IAC), 2025

An end-to-end differentiable simulation pipeline with orbital propagation and physically based rendering for on-orbit inspection operations to optimise inspection trajectories for image quality.

Appearance-Aware Trajectory Optimisation for On-Orbit Inspection

Raghav Mishra, Jack Naylor, Nicholas H Barbara, and Donald G Dansereau

International Symposium on Artificial Intelligence, Robotics and Automation in Space (i-SAIRAS), 2024

An appearance-aware impulsive trajectory optimisation using differentiable Lambert problem solver, using Blender-in-the-loop as an appearance model and using gradient-based optimisation.

Active Vibration Fluidization for Granular Jamming Grippers

Cameron Coombe; James Brett; Raghav Mishra; Gary W. Delaney; David Howard

IEEE International Conference on Soft Robotics (RoboSoft), 2023

We augment a conventional universal gripper with a computer-controllled audio exciter to show it can improve holding strength. We build an automated test rig to allow large-scale data collection to explore the effects of active vibration.

Raghav Mishra

Roboticist, Mechatronic Engineer

Publications

Articles