Joseph Bowkett — accepted AI-conference papers

2025

ProDapt: Proprioceptive Adaptation Using Long-Term Memory Diffusion

Federico Pizarro Bejarano, Bryson Jones, Daniel Pastor Moreno, Joseph Bowkett, Paul G. Backes, Angela P. Schoellig

ICRA 2025

Diffusion models have revolutionized imitation learning, allowing robots to replicate complex behaviours. However, diffusion often relies on cameras and other exteroceptive sensors to observe the environment and lacks long-term memory. In space, military, and underwater applications, robots must be

Cited by 0 Source ↗code ↗Scholar ↗

2023

EELS: Towards Autonomous Mobility in Extreme Terrain with a Versatile Snake Robot with Resilience to Exteroception Failures

Rohan Thakker, Michael Paton, Marlin P. Strub, Michael Swan, Guglielmo Daddi, Rob Royce +41

IROS 2023poster

The discovery of ocean worlds such as Enceladus, Titan, and Europa motivates the development of versatile autonomous mobility systems to enable the next era of space exploration where there is large uncertainty in terrain specifications due to a lack of prior surface reconnaissance missions. To expl…

Cited by 12 Source ↗Scholar ↗

2023

GranularGym: High Performance Simulation for Robotic Tasks with Granular Materials

David R Millard, Daniel Pastor, Joseph Bowkett, Paul Backes, Gaurav S Sukhatme

RSS 2023poster

Granular materials are of critical interest to many robotic tasks in planetary science, construction, and manufacturing. However, the dynamics of granular materials are complex and often computationally very expensive to simulate. We propose a set of methodologies and a system for the fast simulatio…

Cited by 6 Source ↗PDF ↗Scholar ↗