ROBOTIC RAPID PROTOTYPING

High Level Components

Manuel Bonilla, Manolo Garabini, Carlos Rosales, Alessandro Settimi e Antonio Bicchi

Tim

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• MECHANICS • Rapid Prototyping: Tecniche & Materiali

• Dallo Sketch allo Slicing

• Design for 3D rapid prototyping

• Esempi

• ELECTRONICS • Attuatori & Sensori di Base

• Schede di Controllo

• Protocolli di Comunicazione

• Esempio

• HW-IN-THE-LOOP • Comunicazione pc-hw

• Problematiche Soft REal-Time, HArd Real-Time

• MATLAB/Simulink

• Esempio: Variable Stiffness Actuators

• HIGH LEVEL COMPONENTS • “Attuatori” & “Sensori” High level

• Simulatori

• Sistemi integrazione ROS/YARP

• Video Session & Darpa Robotics Challenge

How do we connect everything?

Component drivers

ACTUATORS

• VSA*

• Robotic hands* (PISA/IIT soft hand, Velvet gripper)

• Haptic displays*

• KUKA Light Weight Robot

SENSORS

• Primesense & Kinect (RGB-D sensors)

• Phase Space (motion tracking system)

• ATI (F/T sensors)

• IMU & GPS (from tablets, mobiles, etc)

*developed at Centro "E. Piaggio"

Libraries and Tips

C++ LIBRARIES

• 3D Point clouds processing

• Computer Vision

• Grasp Analysis and Tactile Sensing

• OROCOS Kinematics and Dynamics Library

• Open Motion Planning Library

• Rigid Body Dynamic Library

• Linear Algebra

• Optimization library

• And thousands more...

Trade-off between developing time and customization!

An example - ATI and KUKA integration

Simulators – why?

READY-TO-USE

• ADAMS

• GAZEBO

• SIMULINK

DYNAMIC SOLVERS

• Rigid Body Dynamic Library

• Open Dynamic Engine

• Bullet Physic Library

Darpa Robotics Challenge

Darpa Robotics Challenge

DARPA’s Vision for Disaster Response Robots

• Disasters are unpredictable.

• Robot key properties to be effective:

• Compatibility with environments engineered for humans, even if they are

degraded.

• Ability to use a diverse assortment of tools engineered for humans.

• Ability to be supervised by humans who have had little to no robotics

training.

• Successful robots will demonstrate supervised autonomy in perception and decision-making, and be adaptable enough to operate effectively in unexpected environments where communications might be degraded.

Darpa Robotics Challenge

• Task 1 - Vehicle

• Task 2 - Obstacle

Darpa Robotics Challenge

• Task 3 – Ladder • Task 4 - Debris

Darpa Robotics Challenge

• Task 5 - Door

Darpa Robotics Challenge

• Task 6 - Wall

Darpa Robotics Challenge

• Task 7 - Valve

Darpa Robotics Challenge

• Task 8 - Hose

Darpa Robotics Challenge

How do we connect everything?

Previous tasks require:

• Sensory Perception

• Object Grasping and Manipulation

• Locomotion

• Motion Planning

• High Level Control

Middleware (Software glue)

Peer-to-peer Network of Processes using Streaming Protocols

ADVANTAGES

• Several re-usable code

• Fault tolerance

• High-level debugging tools

DISAVANTAGES

• Extra-effort when developing

• Slow (compared to hard-real time)

Integration with ROS/YARP

• Hardware abstraction

• Distributed System

• Core/Server cares about

sharing resources

– Robot Operating System

Integration with ROS/YARP

• C++

• Python

– Yet Another Robot Platform

Integration with ROS/YARP

Yarp Server • C++

Yarp Device

Yarp Port

Integration with ROS/YARP

Simple examples - Motion tracking of 3D-printed part

Integration with ROS

Complex example - ROBLOG Project Integration

What do we have to integrate?

Camera

KUKA LWR

Velvet Gripper

Grasp Planner

Motion Planner

Virtual Environment

Object Recognition

Real Time Feedback

Real Time Obstacle Avoidance

Complex example - Grasping in an Unstructured Environment