1 Introduction to AI Robotics (MIT Press)Chapter 11 Course Objectives Know what it takes to make a robust autonomous robot work: –Sense/Think/Act Understand the important, approaches, research issues and challenges in autonomous robotics. Know how to program an autonomous robot.

1 Introduction to AI Robotics (MIT Press)Chapter 12 What Can Robots Be Used For? Manufacturing 3 Ds –Dirty –Dull –Dangerous Space –Satellites, probes, planetary landers, rovers Military Agriculture Construction Entertainment Consumer?

1 Introduction to AI Robotics (MIT Press)Chapter 13 History of Intelligent Robotics 1940s –First remote manipulators for hazardous substances 1950s –Industrial manipulators: “reprogrammable and multi-functional mechanism designed to move materials, parts, tools…” –Closed loop control

1 Introduction to AI Robotics (MIT Press)Chapter 14 History Continued 1955 – term “AI” coined 1960s manufacturing robots –Automatic guided vehicles (AGVs) –Precision, repeatability –Emphasis on mechanical aspects 1970s –Planetary landers –Machine vision research expands 1980s –Black factory –First intelligent autonomous robots: Shakey, Stanford Cart, etc

1 Introduction to AI Robotics (MIT Press)Chapter 15 History Continued 1990s –Symbolic AI/Robotics stalls –Reactive/Behavior-based robotics emerges 2000s –?

1 Introduction to AI Robotics (MIT Press)Chapter 16 Intelligent Robot Mechanical creature which can function autonomously –Mechanical= built, constructed –Creature= think of it as an entity with its own motivation, decision making processes –Function autonomously= can sense, act, maybe even reason; doesn’t just do the same thing over and over like automation

1 Introduction to AI Robotics (MIT Press)Chapter 17 “Intelligent” Robotics Basic robot primitives : Sense/Think/Act Three paradigms (architectures): - Hierarchical (Deliberative): Sense ->Plan ->Act ; - Reactive: Sense -> Act; - Hybrid (Deliberative/Reactive): Plan -> Sense -> Act

1 Introduction to AI Robotics (MIT Press)Chapter 18 Ways of Controlling a Robot “RC-ing” –you control the robot –you can view the robot and it’s relationship to the environment –ex. radio controlled cars, bomb robots –operator isn’t removed from scene, not very safe teleoperation –you control the robot –you can only view the environment through the robot’s eyes –don’t have to figure out AI semi- or full autonomy –you might control the robot sometimes –you can only view the environment through the robot’s eyes –ex. Sojouner with different modes –human doesn’t have to do everything

1 Introduction to AI Robotics (MIT Press)Chapter 19 Teleoperation Human controls robot remotely –Hazardous materials –Search and rescue –Some planetary rovers Considerations –Feedback (video, tactile, smell?) –User interfaces (cognitive fatigue, nausea) –Time/distance

1 Introduction to AI Robotics (MIT Press)Chapter 110 Components of a Telesystem (after Uttal 89) Local –display –Local control device Communication Remote –sensor –mobility –effector –power Display Control Sensor Mobility Effector Power Communi- cation Local Remote

1 Introduction to AI Robotics (MIT Press)Chapter 111 Example Local Remote

1 Introduction to AI Robotics (MIT Press)Chapter 112 Typical Run

1 Introduction to AI Robotics (MIT Press)Chapter 113 Problems that You Saw no feedback, couldn’t really tell that the robot was stuck but finally got free –robot doesn’t have “proprioception” or internal sensing to tell you what the flippers were doing. No crunching noises, no pose widget to show the flippers no localization, mapping-> no idea how far traveled partial solution: better instrumentation (but can’t do dead reckoning well) –operator doesn’t have an external viewpoint to show itself relative to the environment solution: two robots, one to spot the other communications dropout, even though ~3 meters away lighting conditions went from dark to very bright –hard for computer vision or human to adjust

1 Introduction to AI Robotics (MIT Press)Chapter 114 DarkStar+7 seconds=DarkSpot 7 second communications lag (satellite relay) “interruption” lag on part of operator

1 Introduction to AI Robotics (MIT Press)Chapter 115 Predator: ~7:1 human to robot ration 4 people to control it (52-56 weeks of training) –one for flying –two for instruments –one for landing/takeoff plus maintenance, sensor processing and routing lack of self-awareness– in Kosovo, come along side in helicopter and shoot down Leo’s unofficial Predator page

1 Introduction to AI Robotics (MIT Press)Chapter 116 Teleop Problems cognitive fatigue communications dropout communications bandwidth communications lag too many people to run one robot

1 Introduction to AI Robotics (MIT Press)Chapter 117 Telesystems Best Suited For: the tasks are unstructured and not repetitive the task workspace cannot be engineered to permit the use of industrial manipulators key portions of the task require dexterous manipulation, especially hand-eye coordination, but not continuously key portions of the task require object recognition or situational awareness the needs of the display technology do not exceed the limitations of the communication link (bandwidth, time delays) the availability of trained personnel is not an issue

1 Introduction to AI Robotics (MIT Press)Chapter 118 Teleop Solutions Telepresence –improves human control, reduces simulator sickness and cognitive fatigue by providing sensory feedback to the point that teleoperator feels they are “present” in robot’s environment Semi-autonomous –Supervisory Control human is involved, but routine or “safe” portions of the task are handled autonomously by the robot Shared Control –human initiates action, interacts with remote by adding perceptual inputs or feedback, and interrupts execution as needed Traded Control –human initiates action, does not interact –Mixed Initiative (Guarded Control) robot doesn’t let the operator injure the robot (without override) “whoever figures it out first”

1 Introduction to AI Robotics (MIT Press)Chapter 119 Collaborative Teleoperation Urban is stuck, Inuktun can’t help from current perspective 1.Driven off 3 rd floor 2.Hoisted to 2 nd floor by tether 3.Has better view, changing configuration & rocking extend view mpg: June 2, 2000 SRDR Miami Beach: view from Inuktun as it falls mpg: June 2, 2000 SRDR Miami Beach: view from Inuktun from hoisted position still: June 2, 2000 SRDR Miami Beach

1 Introduction to AI Robotics (MIT Press)Chapter AAAI Mobile Robot 2 robots helping each other reduced collision errors, sped up time navigating confined space, righting

1 Introduction to AI Robotics (MIT Press)Chapter 121 Example: Mixed-Initiative & Collab. Teleop 9/2000 DARPA Tactical Mobile Robots demonstration Robot used an intelligent assistant agent to look for signs of snipers hiding in urban rubble –motion –skin color –difference in color –thermal (IR camera) Human navigated mother robot using viewpoint of 2 nd robot (not in picture) Once deposited the human moved the daughter robot, and either saw a sniper or was alerted by the agent

1 Introduction to AI Robotics (MIT Press)Chapter 122 AI provides the “other stuff” knowledge representation understanding natural langugage learning planning and problem solving inference search vision

1 Introduction to AI Robotics (MIT Press)Chapter 123 Summary Teleoperation arose as an intermediate solution to autonomy, but it has a number of problems:cognitive fatigue, high comms bandwidth, short delays, and many:one human to robot ratios. Telepresence tries to reduce cognitive fatigue through enhanced immersive environments Semi-autonomy tries to reduce fatigue, bandwidth by delegating portions of the task to robot