PPT-A Confidence-Based Approach to Multi-Robot Demonstration Le

Author : briana-ranney | Published Date : 2016-03-18

Sonia Chernova Manuela Veloso Carnegie Mellon University Computer Science Department Policy Development Learning from Demonstration Accessselect sensor data Develop

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A Confidence-Based Approach to Multi-Robot Demonstration Le: Transcript

Sonia Chernova Manuela Veloso Carnegie Mellon University Computer Science Department Policy Development Learning from Demonstration Accessselect sensor data Develop actions Provide demonstrations. Robot Obstacle domainofresponsibility (a)Robottoblame Robot Obstacle (b)Bothtoblame Robot domainofresponsibility (c)Sensor-dependentdo-mainofresponsibility Robot Obstacle b Collision (d)Collision,butb Vickie Hawkins . Background. CRRT @ . Cardon. Children’s PICU. Low Volume/High Risk Skill. Previous experience. Patients transferred to other facilities. No continuity of patient care. Decreased RN confidence. Anahita. . Mohseni-Kabir. , Sonia . Chernova. and Charles Rich. Worcester Polytechnic Institute. Project . Objectives and Contributions. Main Goal: Learning complex procedural tasks from human demonstration and . T. . Bajd. and M. . Mihelj. Proprioceptive sensors. position . velocity . joint torques. Exteroceptive. sensors. force sensors . tactile sensors . proximity sensors. distance sensors. Robot sensors. 2011/12/08. Robot Detection. Robot Detection. Better Localization and Tracking. No Collisions with others. Goal. Robust . Robot . Detection. Long . Range. Short. . Range. Long Range. C. urrent . M. ethod. What is ROBOT ?. DEFINITION. “A reprogrammable, multifunctional manipulator designed to move material, parts, tools, or specialized devices through various programmed motions for the performance of a variety of tasks.”. Mobile Agent Cloning for . Servicing . Networked . Robots . 2. . STIGMERGICALLY CONTROLLING A POPULATION OF. HETEROGENEOUS MOBILE AGENTS USING CLONING RESOURCE. 4. . ROBOTICS . LABORATORY . www.iitg.ernet.in/cse/robotics/. -based Learning from Demonstration. Anthony Dubis. “. Keyframe. -based Learning from Demonstration – Method and Evaluation” . – . Akgun. , . Cakmak. , Jiang, and . Thomaz. What We’ll Cover. Lesson . 5. Teaching Assistant: . Roi. . Yehoshua. roiyeho@gmail.com. . Summer 2015. Agenda. Spanning . multiple robots in Gazebo. Controlling multiple robots in . Gazebo. Running navigation stack in Gazebo with multiple . Alison Iredale. Wayne Bailey. Dr Kevin Orr. Jane Wormald. Overview. Professional knowledge and practice. Policy discourses. The inculcation of confidence. Accommodation . of risk . Eukairia. Professional knowledge and practice. Chapter 6 Confidence Intervals Sections 6-1 and 6-2 Confidence Intervals for Large and Small Samples VOCABULARY: Point Estimate – A single value estimate for a population parameter. Autonomous Narration of Humanoid Robot Kitchen Task Experience by Qingxiaoyang Zhu, Vittorio Perera, Mirko Wächter, Tamim Asfour, & Manuela Veloso Why do we need narration? “...progress in humanoid robotics research has led to robots that are able to perform complex tasks with a certain level of autonomy...However, robot capabilities are still limited in regard to how they externalize their internal state and world state...” Autonomous . Exploration. Carl Nelson*, . Khoa. Chu*, . Prithviraj. (Raj) . Dasgupta. **. University of . Nebraska. *: Mechanical Engineering, University of Nebraska, Lincoln. **: Computer Science, University of Nebraska, Omaha. Conceptual Design Review MRSD Team D Stakeholders: Customer – Cyert Center for Early Education Mentor – Dr. David Held Professors: Dr. Dimitrios (Dimi) Apostolopoulos Dr. John M. Dolan The Te

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