Md Sazzad Islam — accepted AI-conference papers

2025

RoboCrowd: Scaling Robot Data Collection Through Crowdsourcing

Suvir Mirchandani, David D. Yuan, Kaylee Burns, Md Sazzad Islam, Tony Z. Zhao, Chelsea Finn +1

ICRA 2025

In recent years, imitation learning from large-scale human demonstrations has emerged as a promising paradigm for training robot policies. However, the burden of collecting large quantities of human demonstrations is significant in terms of collection time and the need for access to expert operators

Cited by 9 Source ↗code ↗Scholar ↗

2024

So You Think You Can Scale Up Autonomous Robot Data Collection?

Suvir Mirchandani, Suneel Belkhale, Joey Hejna, Evelyn Choi, Md Sazzad Islam, Dorsa Sadigh

CoRL 2024poster

A long-standing goal in robot learning is to develop methods for robots to acquire new skills autonomously. While reinforcement learning (RL) comes with the promise of enabling autonomous data collection, it remains challenging to scale in the real-world partly due to the significant effort required…

Cited by 4 Source ↗Scholar ↗