Stanford AA289/ENGR319 - Robotics and Autonomous Systems Seminar - Stanford Seminar - Modeling and Control for Robotic Assistants

Monroe Kennedy is an Assistant Professor of Mechanical Engineering at Stanford University. This talk was given on October 4, 2019. As advances are made in robotic hardware, the capacity of the complexity of tasks they are capable of performing also increases. One goal of modern robotics is to introduce robotic platforms that require very little augmentation of their environments to be effective and robust. Therefore the challenge for the Roboticist is to develop algorithms and control strategies that leverage the knowledge of the task while retaining the ability to be adaptive, adjusting to perturbations in the environment and task assumptions. These strategies will be discussed in the context of a wet-lab robotic assistant. Motivated by collaborations with a local pharmaceutical company, we will explore two relevant tasks. First, we will discuss a robot-assisted rapid experiment preparation system for research and development scientists. Second, we will discuss ongoing work for intelligent human-robot cooperative transport with limited communication. These tasks are the beginning of a suite of abilities for an assisting robotic platform that can be transferred to similar applications useful to a diverse set of end-users. View the full playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rMeercb-kvGLUrOq4HR6BZD Learn about our Robotics and Autonomous Systems Graduate Program: https://online.stanford.edu/programs/robotics-and-autonomous-systems-graduate-program 0:00 Introduction 0:30 Outline 1:56 The Three A's of Robotics 4:35 Current PhD Students 4:41 Human-Robot Cooperative Transport 5:53 Improving Dexterous Manipulation 6:56 Intelligent Prosthetic Arm 8:10 Modeling Considerations 11:11 Wet-Lab Robotic Assistant 11:44 Executing Complex Tasks 13:32 Why is the pouring problem challenging? 14:00 Additional Wet-Lab Pouring Task Challenges 14:15 Pouring Problem Solutions 16:24 Problem Formulation 18:05 Precision Pouring for Experiment Preparation Precision Pouring With Known Container Geometries 23:34 Fluid Detection Methods 41:37 Obtaining Pourer Geometry 43:18 Precision Pouring Summary 43:46 Wet Lab Robotic Assistant 43:54 Transport Problem 48:28 Human Robot Collaboration Estimating Human intent for Cooperative Transport of Large/Heavy Objects 54:41 Cooperative Transport Summary 55:44 Acknowledgements 55:49 Questions?