Intrinsic

Software Engineer

Open Robotics

At Open Robotics, I was the "ROS Boss" of the Humble (LTS) release of ROS 2. This involved extensive collaboration with various stakeholders and the development of new infrastructure to streamline the release process.

To address a need in the testing process, I designed and implemented a Test Case Manager tool in Typescript. This tool automates the creation of test cases for different platform permutations and has been employed in several key releases, including ROS 2 Humble, ROS 2 Iron, and Gazebo Garden.

In addition to these responsibilities, I worked on various other projects that required a wide range of technical skills. These included debugging multithreaded executor issues, designing C++ client library features for Nvidia, contributing to NASA's VIPER mission, and integrating different UAV frameworks under a common API.

Robohub

As the Podcast Director at Robohub, I managed an international team and conducted over 100 interviews with key figures in the robotics field. The variety of our interviewees, from academics to industry leaders, allowed us to present a comprehensive view of the sector.

I led the team in expanding our podcast's monthly listenership from 2k to 120k and secured $20k in academic sponsorships. This growth and financial support helped to sustain our operations and extend our reach.

During my tenure, we produced and released 160 podcast episodes. This consistent output, combined with our increased listenership and financial support, illustrates my focus on steady growth and commitment to sharing knowledge in the robotics community.

Podcast Director

Halodi Robotics

Software Engineer Intern

senseFly

I work at Intrinsic AI, where I am a software engineer. I am also the host of the Audrow Nash Podcast. Previously, I hosted the Sense Think Act podcast and led Robohub's podcast. Outside of robotics, I rock climb.

Audrow Nash

Electric Sheep

Making billions of outdoor robots to care for our planet.

Chief Technology Officer

Leading software initiatives to create landscaping robots.

Vice President of Autonomy 

Leading our ML team to deploy smart autonomous mowers across the US.

Principal Engineer

Toyota Research Institute

Project Lead of the Generalized Behaviors Team
-Developing a synthetic data pipeline for training  3D perception networks
-Managing a fleet of robots that are currently deployed in homes across California
-Implemented a variety of manipulation behaviors (I.e. place/grasps/open)  for home tidying

Sr. Research Scientist

UC Berkeley

Research Experience 
Machine Learning: Imitation Learning , Multi-Armed Bandits, Policy Gradients
Computer Vision: Object Detection, CNNs, GANs
Robotics:  Motion Planning, Grasp Planning
Software: EC2, Amazon Mechanical Turk, Tensorflow, PyTorch, ROS, Ray, OpenCV
Managerial: Mentored up to Ten Bachelors and Master Students, Experience in Recruiting and Interviewing

Here is a sample of recent projects:

Algorithmic Development for Robust Imitation Learning:
Developed DART a new algorithm for Imitation Learning that is competitive with state of the art methods such as DAgger. However unlike DAgger, DART is computationally inexpensive, user-friendly and is safe. A blog post on this can be found at http://bair.berkeley.edu/blog/2017/10/26/dart/
 
 Simulation for Self-Driving Cars: 
 The goal is to create fast python based simulations, which can enable rapid prototyping of algorithms for self-driving car agents. Our system first uses Object Detection to extracted driving behavior from live traffic camera streams. Then applies DART to train multi-agent deep policies over a distributed EC2 network. 

  Robotic Manipulation for the Home :
Leveraging recent advances in Imitation Learning and Object Detection, such as Faster R-CNNs and YOLO, we have trained a Toyota HSR robot to perform various home tasks, such as picking up playing cards or retrieving objects from a cupboard. Recently, we have applied DART to train the HSR robot to perform the sequential task of making a bed.  A video can be found at https://youtu.be/HbNNkrk9aOI
  
 Order Fulfillment in Warehousing:
 Implemented an end-to-end prototype system for packing boxes using the Dex-Net Grasping Software and an Industrial ABB YuMi Robot. Given a heap of objects the robot would search for a given set and pack them into a box. A video of the system can be found at https://www.youtube.com/watch?v=i6K3GI2_EgU

See here for more information and complete list of publications: 
https://people.eecs.berkeley.edu/~laskeymd/

AI and Robotics Researcher

Intel Corporation

Created a SLAM based algorithm using machine learning with an IMU and a pedometer. Applied algorithm to allow users to walk around a virtual world with a tablet.

taplio

The Battle

Audrow Nash

Michael Laskey

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