When: Thursday 19th of June, 1:00pm AEST
Where: This seminar will be partially presented at the ACFR seminar area, J04 lvl 2 (Rose St Building) and partially online via Zoom. RSVP
Speaker: Raghav Mishra
Title: Using Diffusion Models for Motion Planning in Constrained Environments

Abstract:
Diffusion Models are deep learning models that have been very successful in generative modelling of complex data such as images, videos and text. They have also shown state of the art performance in difficult robotics tasks such as imitation learning, but they discount prior knowledge of system dynamics and task objectives. Model-Based Diffusion is a technique that offers an alternative approach enabling diffusion based on models while retaining the ability to incorporate learning. However, Model-Dased Diffusion struggles in severely constrained environments due to its Monte Carlo sampling-based mature. This presentation introduces diffusion models in the context of optimisation theory, how model-based diffusion can be used to do motion planning, why it struggles in constrained environments, and how it can be improved. We present applications and simulated examples for underwater robotic manipulation.
Bio:
Raghav is a second year PhD researcher in Control and Motion Planning at the Australian Centre for Robotics. He received a Bachelors and Masters in Mechatronic Engineering at the University of Queensland in 2021. He is a part of the ARIAM Hub and is currently working with industry partner Reach Robotics on combining learning and planning for underwater mobile manipulation.