Car assembly Overview: Perception Planning Control Robot - PowerPoint PPT Presentation

Sep 12, 2023 •273 likes •461 views

Car assembly Overview: Perception Planning Control Robot Operating System Practice Session 1: Driving using Keyboard controls Traxxas 1/10 scale RC race car Traxxas 1/10 scale RC race car Brushless DC motor Electronic Speed Control (ESC)

Car assembly Overview: Perception Planning Control Robot Operating System Practice Session 1: Driving using Keyboard controls
Traxxas 1/10 scale RC race car
Traxxas 1/10 scale RC race car
Brushless DC motor
Electronic Speed Control (ESC)
Servo motor for steering
Radio receiver
Battery pack
Sensor Integration LiDAR Camera IR Depth Cameras IMU
Sensor Integration LiDAR Camera IR Depth Cameras IMU Motor Controller Battery Wi-fi Telemetry Onboard Computer
Ready to race ! Not quite..
System Architecture Steering Filters Localization Map generation Path planning Computer vision Drive Wireless Telemetry
Perception
Perception Wall – T section or turn Uneven Wall – T section or turn Wall Surface Laser Scans Laser Scans Uneven Wall Surface Race car view LaserScans viewed in Rviz
Planning
Planning Cost Maps path planning
Control
System Architecture Steering Filters Localization Map generation Path planning Computer vision Drive Wireless Telemetry

Recommend

Robot behaviour and control A robot can be defined as an intelligent link between perception

Robot behaviour and control A robot can be defined as an intelligent link between perception and action Robot Action Perception Environment www.biorobotics.ttu.ee For a mobile robot Knowledge, Mission Data Base Commands Cognition

553 views • 29 slides

Perception, Planning and Control F1/10 th Racing Perception, planning and control Localization

Perception, Planning and Control F1/10 th Racing Perception, planning and control Localization IMU and PID Control LIDAR 2 Perception Sensors: specifications, placement and data Inertial Measurement Unit An I nertial M

1.05k views • 49 slides

Robot sensors A robot can be defined as an intelligent link between perception and action

Robot sensors A robot can be defined as an intelligent link between perception and action Robot Action Perception Environment www.biorobotics.ttu.ee For a mobile robot Knowledge, Mission Data Base Commands Cognition Localization

551 views • 29 slides

(Deep) Learning for Robot Perception and Navigation Wolfram Burgard Deep Learning for Robot

(Deep) Learning for Robot Perception and Navigation Wolfram Burgard Deep Learning for Robot Perception (and Navigation) Lifeng Bo, Claas Bollen, Thomas Brox, Andreas Eitel, Dieter Fox, Gabriel L. Oliveira, Luciano Spinello, Jost Tobias

509 views • 50 slides

Overview of Robot Perception Prof. Yuke Zhu Fall 2020 CS391R: Robot Learning (Fall 2020) 1

Overview of Robot Perception Prof. Yuke Zhu Fall 2020 CS391R: Robot Learning (Fall 2020) 1 Logistics Office Hours Instructor: 4-5pm Wednesdays (Zoom) or by appointment TA: 10:15-11:15am Mondays (Zoom) or by appointment Presentation Sign-Up:

635 views • 48 slides

Perception. Planning. Control Making sense of the surroundings Planning the fastest racing line

F 1 / 1 0 Dr. Madhur Behl University of Pennsylvania Perception. Planning. Control Making sense of the surroundings Planning the fastest racing line Controlling the car to follow the planned path Sense. Plan. Act. Repeat. Sense Plan

386 views • 13 slides

SnakeSIM : a Snake Robot Simulation Framework for Perception-Driven Obstacle-Aided Locomotion

Introduction SnakeSIM Control approach Conclusion References SnakeSIM : a Snake Robot Simulation Framework for Perception-Driven Obstacle-Aided Locomotion Filippo Sanfilippo 1 , yvind Stavdahl 1 and P ack 1 al Liljeb 1Dept. of

466 views • 18 slides

Ensemble Control as a Tool for Robot Motion Planning: Uncertainty, Optimality, and Complexity

Introduction Linear example Nonlinear example Conclusion Ensemble Control as a Tool for Robot Motion Planning: Uncertainty, Optimality, and Complexity Timothy Bretl (w/ Aaron Becker) University of Illinois at Urbana-Champaign IEEE ICRA

601 views • 37 slides

System Architecture Steering Filters Localization Map generation Path planning Computer

System Architecture Steering Filters Localization Map generation Path planning Computer vision Drive Perception Planning Control ROS: Robot Operating System ROS distributions This course 2012 2013 2014 2015 ROS Capabilities

380 views • 20 slides

Integrating decision-theoretic planning and programming for robot control in highly dynamic

Integrating decision-theoretic planning and programming for robot control in highly dynamic domains Christian Fritz Thesis, Final Presentation Integrating decision-theoretic planning and programming for robot control in highly dynamic domains

752 views • 31 slides

Overview n Perception for robotics Page 1 Overview n Perception for robotics Overview

Perception for Robotics: Instance Detection Pieter Abbeel UC Berkeley EECS Overview n Perception for robotics Page 1 Overview n Perception for robotics Overview n Perception for robotics n Accurately localizing (specific)

532 views • 22 slides

Out line Robot ics Percept ion Robot ics Planning Reading: R&N Sect .

Out line Robot ics Percept ion Robot ics Planning Reading: R&N Sect . 25.1-25.4 J uly 26, 2005 CS 486/ 686 Univer sit y of Wat erloo 2 CS486/686 Lecture Slides (c) 2005 P. Poupart Robot s Robot s Mobile r obot s

247 views • 4 slides

Control of an 8-legged, 24 DOF, Control of an 8-legged, 24 DOF, Mechatronic Robot Mechatronic

Control of an 8-legged, 24 DOF, Control of an 8-legged, 24 DOF, Mechatronic Robot Mechatronic Robot Brian Lim Youliang Kuvesvaran s/o Paramasivan National Junior College Assoc. Prof. Dr. Malcolm Francis John Nickols Nanyang Technological

129 views • 10 slides

ROBOT CONTROL USING LIVING ROBOT CONTROL USING LIVING NEURONAL CELLS: PROGRESS AND CHALLENGES Vi

ROBOT CONTROL USING LIVING ROBOT CONTROL USING LIVING NEURONAL CELLS: PROGRESS AND CHALLENGES Vi Victor M. Becerra M B School of Systems Engineering Whitehead Lecture Series G ld Goldsmiths, 09 March 2011 i h M h Introduction Introduction

662 views • 39 slides

Safe model-based learning for robot control Breaking your robot is only fun in simulation Felix

Safe model-based learning for robot control Breaking your robot is only fun in simulation Felix ix Berkenkamp, Andreas Krause, Angela P. Schoellig @LCCC Workshop on Learning and Adaptation for Sensorimotor Control Lund University October

448 views • 43 slides

Learning and adaptation Perception of robots by humans Interfaces Exhibiting and

Learning and adaptation Perception of robots by humans Interfaces Exhibiting and recognizing emotions Control Multimodal interactions Applications Constraints on robot abilities Physical design / appearance

543 views • 25 slides

01/12/2010 Naive View of Perception Naive View of Perception I directly experience the

01/12/2010 Brief Biography Background in philosophy 2004-2008, University of Essex. PhD Machine consciousness. Worked on EPSRC project to Perception, Causation and the build a conscious robot. Scientific Study of Human and

665 views • 21 slides

Analysis and Control of Multi-Robot Systems Multi-Robot Localization Dr. Paolo Stegagno

Elective in Robotics 2011/2012 Analysis and Control of Multi-Robot Systems Multi-Robot Localization Dr. Paolo Stegagno Dipartimento di Ingegneria Informatica, Automatica e Gestionale 1 / 73 Introduction multi-robot localization :

759 views • 73 slides

Robot Architectures You dont need to implement an intelligent agent as: Perception Reasoning

Robot Architectures You dont need to implement an intelligent agent as: Perception Reasoning Action as three independent modules, each feeding into the the next. Its too slow. High-level strategic reasoning takes more time than

388 views • 13 slides

Localization 1 Odometric Localization planning and feedback control require the knowledge of

Autonomous and Mobile Robotics Prof. Giuseppe Oriolo Localization 1 Odometric Localization planning and feedback control require the knowledge of the robot configuration q (e.g., see Motion Control of WMRs: Trajectory Tracking, slide 3)

361 views • 9 slides

Some old and new algorithms for robot motion planning Quang-Cuong Pham Department of

Some old and new algorithms for robot motion planning Quang-Cuong Pham Department of Mechano-Informatics University of Tokyo October 16th, 2012 Robotics Laboratory Seoul National University Outline Time-optimal control under dynamics

394 views • 37 slides

CS CS391R: Robot Learnin ing Perception, Decision Making, and General-Purpose Autonomy Prof.

CS CS391R: Robot Learnin ing Perception, Decision Making, and General-Purpose Autonomy Prof. Yuke Zhu Fall 2020 CS391R: Robot Learning (Fall 2020) 1 Robotics and COVID-19 Photos from the Internet CS391R: Robot Learning (Fall 2020) 2

1.29k views • 42 slides

A Self-Localization and Path Planning Technique for Mobile Robot Navigation Jia-Heng Zhou and

A Self-Localization and Path Planning Technique for Mobile Robot Navigation Jia-Heng Zhou and Huei-Yung Lin National Chung Cheng University 9th World Congress on Intelligent Control and Automation (WCICA), 2011 Presented by: Dereck Wonnacott

629 views • 18 slides

5. Situated Agents (Robots) Part 2: Planning and Motion. ) Multi Robot Systems Multi-Robot

5. Situated Agents (Robots) Part 2: Planning and Motion. ) Multi Robot Systems Multi-Robot Systems. tems (SMA-UPC Javier Vzquez-Salceda SMA-UPC Multiagent Syst https://kemlg.upc.edu Task Planning Usually most of the tasks are

439 views • 33 slides