Bardienus Pieter Duisterhof


I am a Ph.D. student at Carnegie Mellon University (CMU), in the Robotics Institute advised by Sebastian Scherer. Before coming to CMU, I completed a Bachelor's and Master's degree in Aerospace Engineering at Delft University of Technology, in the Netherlands. Advised by Guido de Croon, I studied efficient bio-inspired algorithms for autonomous flight of tiny flying drones. In 2019 I was a visiting student at Vijay Janapa Reddi's Edge Computing lab, at Harvard University, where we studied Deep Reinforcement Learning for tiny robots. During this time my work on bio-inspired intelligence with Guido de Croon also helped me receive the titel of best graduate in engineering of TU Delft in the academic year 2020-2021. My research focus continues to be on scalable AI for fully autonomous operation of robots that interact with their environment. At the intersection of computer vision, machine learning, and systems, I hope to contribute to a future where complex robotic automation is scalable, safe and useful.

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TartanCalib: Iterative Wide-Angle Lens Calibration using Adaptive SubPixel Refinement of AprilTags
Bardienus P Duisterhof, Yaoyu Hu, Si Heng Teng, Michael Kaess, Sebastian Scherer
Under Review - ICRA 2023
project website / arXiv / video / code

In this work we present our methodology for accurate wide-angle calibration. Our pipeline generates an intermediate model, and leverages it to iteratively improve feature detection and eventually the camera parameters.

Sniffy Bug: A Fully Autonomous Swarm of Gas-Seeking Nano Quadcopters in Cluttered Environments
Bardienus P Duisterhof, Shushuai Li, Javier Burgués, Vijay Janapa Reddi, Guido C.H.E. de Croon
IROS, 2021
arXiv / video / code

We have developed a swarm of autonomous, tiny drones that is able to localize gas sources in unknown, cluttered environments. Bio-inspired AI allows the drones to tackle this complex task without any external infrastructure.

Tiny Robot Learning (tinyRL) for Source Seeking on a Nano Quadcopter
Bardienus P Duisterhof, Srivatsan Krishnan, Jonathan J. Cruz, Colby R. Banbury, William Fu, Aleksandra Faust , Guido C.H.E. de Croon, Vijay Janapa Reddi
ICRA, 2021
paper / video / code

We present fully autonomous source seeking onboard a highly constrained nano quadcopter, by contributing application-specific system and observation feature design to enable inference of a deep-RL policy onboard a nano quadcopter.

A Tailless Flapping Wing MAV Performing Monocular Visual Servoing Tasks
Diana A. Olejnik, Bardienus P Duisterhof, Matej Karásek , Kirk Y. W. Scheper, Tom van Dijk, Guido C.H.E. de Croon
Unmanned Systems, Vol. 08, No. 04, pp. 287-294 , 2020
paper / video

This paper describes the computer vision and control algorithms used to achieve autonomous flight with the ∼30g tailless flapping wing robot, used to participate in the International Micro Air Vehicle Conference and Competition (IMAV 2018) indoor microair vehicle competition.

AE2235-I: Aerospace Systems & Control Theory
Media Coverage
IEEE Spectrum Video Friday
Bitcraze Blog
PiXL Drone Show
Best Graduate in Engineering, TU Delft, academic year 2020-2021
Best Graduate in Aerospace Engineering, TU Delft, academic year 2020-2021
Innovation Award, IMAV 2018 Autonomous Drone Race

Modified version of template from here