Transcript CS225B Robots - Artificial Intelligence Center @ SRI

Autonomous Robots
Key questions in mobile robotics
 What is around me?
 Where am I ?
 Where am I going ?
 How do I get there ?
Alternatively, these questions correspond to
 Sensor Interpretation: what objects are there in the vicinity?
 Localization: find your own position in a map (given or built
autonomously)
 Map building: how to integrate sensor information and your own
movement?
 Path planning: decide the actions to perform for reaching a target position
[Many following robot slides courtesy
Steffen Gutmann, SONY Labs]
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Robotics Yesterday
Current Trends in Robotics
Robots are moving away from factory floors to
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Entertainment robots
Personal services
Medical, surgery
Industrial automation
(mining, harvesting, ...)
Hazardous environments
(space, underwater)
Military
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UGV, UAV, AUV
Transitioning from remote control to autonomous control
Robotics Today
AI View on Mobile Robotics
Sensor data
Control
system
World model
Actions
Helpmate
HELPMATE is a mobile robot used in hospitals for
transportation tasks. It has various on board sensors for
autonomous navigation in the corridors. The main sensor
for localization is a camera looking to the ceiling. It can
detect the lamps on the ceiling as reference (landmark).
http://statusreports-atp.nist.gov/reports/91-010034.htm
Cleaning Robot - Sinas
Autonomous cleaning robot with Sinas navigation
system (developed by Siemens) and manifactured by
Karcher. The robot is equipped with several sonar
sensors, a laser range finder and a gyroscope.
Sinas Video
CS225B Kurt Konolige
ROV Tiburon Underwater Robot
Picture of robot ROV Tiburon for underwater
archaeology (teleoperated)- used by MBARI for
deep-sea research, this UAV provides
autonomous hovering capabilities for the
human operator.
Sojourner, First Robot on Mars
The mobile robot
Sojourner was used
during the Pathfinder
mission to explore the
mars in summer 1997.
It was nearly fully
teleoperated from
earth. However, some
on board sensors
allowed for obstacle
detection.
http://ranier.oact.hq.nasa.gov/telerobotics_page/telerobotics.shtm
The B21 Robot
B21 of Real World
Interface is a
sophisticated mobile robot
with up to three Intel
Pentium processors on
board. It has all different
kinds of on board sensors
for high performance
navigation tasks.
Minerva (CMU + Univ. Bonn, 1998)
Courtesy Sebastian Thrun, CMU
Pioneer 1
PIONEER 1 is a modular mobile robot offering various options like a gripper or an on board camera.
It is equipped with a sophisticated navigation library developed at Stanford Research Institute (SRI)
and manifactured by ActivMedia Robotics http://www.mobilerobots.com/
RoboCup – Middle Size League
Emotional Robots: Kismet
Courtesy Cynthia Breazeal, MIT
Sony's AIBO Robot
First model (1998)
Latest model ERS 7 (2004)
RoboCup 4-legged League
The Honda Walking Robot Asimo
http://www.honda.co.jp/robot/
Sony's QRIO Robot
QRIO Navigation
CS225B Kurt Konolige
Darpa Grand Challenge
Stanley is based on a VW Touareg R5
with 7 Pentium M computers
incorporating measurements from
GPS, INS, and wheel speed for
pose estimation.
Standford's Stanley “racing car”
Sample tracking visualization
The environment is perceived through
4 laser range finders, a radar system,
a stereo camera pair, and a monocular
vision system. Sensor data is processed
at rates between 10 and 100 Hertz.
Map and pose information are
incorporated at 10 Hz, enabling Stanley
to avoid collisions with obstacles in
real-time while advancing along the
2005 DARPA Grand Challenge route.
Darpa Grand Challenge Video
Courtesy Sebastian Thrun, Stanford University
Darpa Learning Applied to Ground Robotics
• Autonomous outdoor vehicle in
unstructured environments
• Main sensor is stereo vision
• Learn models of terrain
traversability
Stanford Mausoleum Run
Robot-view Interpretation
Global Map
BigDog: Quadruped Beast of Burden
• Autonomous
outdoor vehicle
in unstructured
environments
• Internal
sensors only
Video from Boston Dynamics
Trends in Robotics Research
Classical AI Robotics (mid-70’s)
• Sense-Plan-Act
• Complex world model and reasoning
Reactive Paradigm (mid-80’s)
• No models: “the world is the model”
• Simple sense-act functions
• Emergent behavior
Hybrid Architectures (90’s)
• Models at higher levels, reactive at lower levels
• Mid-level executive to sequence actions
Probabilistic Methods (mid-90’s)
• Uncertain sensing and acting
• Integration of models, sensing, acting
Indoor, wheeled,
static blocks world
Static legged motion,
robot swarms,
reactive
Complex environments,
mapping and localization,
human-robot interactions
Challenging outdoor
environments
Air, water vehicles
Dynamic legged motion