Simeon Adebola

I am a 5th year PhD student in Electrical Engineering and Computer Science(EECS) at UC Berkeley where I am advised by Ken Goldberg as a member of the AUTOLab and Berkeley Artificial Intelligence Research (BAIR) Lab. I am supported by the Bakar BioEnginuity Impact Grant.

My research interests are in robotics and computer vision. My current research is in Agricultural Robotics, Cloud Robotics and Manipulation of 1D Deformable Linear Objects (DLO).

In the past, I graduated from MTSU Murfreesboro, where I worked with Lei Miao on robotics for fall detection and received the Outstanding Masters Research Award, College of Basic and Applied Sciences. I have also been fortunate to spend time at UCLA and Vanderbilt University.

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• My prior research has been featured in CISC 4/667 (011): Computing for Social Good at the University of Delaware and CSE 580: Computing for Social Good at the University of Washington.

We augment 16 OXE datasets into 4.4 million trajectories across 9 robot types for each dataset.

This journal paper extends our CSCL 2022 paper.

We created segmented 3D reconstructions of eight potted plants and used those to guide a robot's interaction with the plants to reveal occluded leaf structures.

Temporal reconstructions of plants across multiple timesteps by combining 3D reconstructions with a robust sample alignment pipeline using a two-stage registration approach.

Novel gasket assembly task with three testbeds and a benchmark comparison between three procedural algorithms and one deep imitation learning approach across 100 trials.

A multi-institution project bringing together multiple datasets across multiple robot platforms and multiple skills/tasks with a large model, RT-X trained on the entire dataset. This project was carried out in collaboration with Google Deepmind and 33 different labs across 21 institutions.

This journal paper extends our CASE 2022 paper.

A platform for connecting robot and robot components across physical locations and networks securely and globally.

An algorithm for seed placement in polyculture settings that works for both convex and non-convex planting areas, for various plants types and numbers.

Comparing humans experts to AlphaGarden on similarly planted gardens two 60-day cycles. Evaluation is based on coverage, diversity, and water usage.

An easy way for roboticists using ROS 2 to take advantage of cloud platforms including AWS, Azure and GCS to run any portions of their pipeline.

Novel hardware and algorithms for automated pruning of polyculture plants with results for four 60-day garden cycles.

This paper is extended in our journal paper.

An exploration, using interaction analysis, of how children use teacher-, peer-, and technology-provided feedback together towards collective and embodied learning in a mixed-reality environment.

This paper is extended in our journal paper.

Lessons from AlphaGarden including its seed planting algorithm can be leveraged for polyculture farming in Africa

Maker initiatives should embrace and integrate with the informal sector and grassroots innovators.

A low-cost 5 DOF robot for STEM education made using indigenously sourced parts and reused motors.

Africa's STI policy should include an indigenous futures(Strategic Foresight) component.

Reviewer: T-FR, TMLR, ICRA, IROS, CASE, T-ASE, WACV, RA-L, RAM

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