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Max Bajracharya

5 accepted papers

2025

Mobi-$\pi$: Mobilizing Your Robot Learning Policy

CoRL 2025poster

Learned visuomotor policies are capable of performing increasingly complex manipulation tasks. However, most of these policies are trained on data collected from limited robot positions and camera viewpoints. This leads to poor generalization to novel robot positions, which limits the use of these p…

Cited by 0SourceScholar
2023

Demonstrating Mobile Manipulation in the Wild: A Metrics-Driven Approach

RSS 2023poster

We present our general-purpose mobile manipulation system consisting of a custom robot platform and key algorithms spanning perception and planning. To extensively test the system in the wild and benchmark its performance, we choose a grocery shopping scenario in an actual, unmodified grocery store.…

2022

A Learned Stereo Depth System for Robotic Manipulation in Homes

RA-L 2022

We present a passive stereo depth system that produces dense and accurate point clouds optimized for human environments, including dark, textureless, thin, reflective and specular surfaces and objects, at 2560 × 2048 resolution, with 384 disparities, in 30 ms. The system consists of an algorithm com

Cited by 29SourceScholar
2020

A Mobile Manipulation System for One-Shot Teaching of Complex Tasks in Homes

ICRA 2020poster

We describe a mobile manipulation hardware and software system capable of autonomously performing complex human-level tasks in real homes, after being taught the task with a single demonstration from a person in virtual reality. This is enabled by a highly capable mobile manipulation robot, whole-bo…

Cited by 36SourceScholar
2015

Supervised Remote Robot with Guided Autonomy and Teleoperation (SURROGATE): A framework for whole-body manipulation

ICRA 2015poster

The use of the cognitive capabilties of humans to help guide the autonomy of robotics platforms in what is typically called “supervised-autonomy” is becoming more commonplace in robotics research. The work discussed in this paper presents an approach to a human-in-the-loop mode of robot operation th…

Cited by 29SourceScholar