Introduction To Cognitive Robots

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1 Introduction To Cognitive Robots Prof. Brian Williams Rm Wednesday, February 2 nd, 2004

2 Outline Examples of Robots as Explorers Course Objectives Student Introductions and Goals Introduction to Model-based Programming

3 Course Objective 1 To understand the main types of cognitive robots and their driving requirements: Immobile Robots and Engineering Operations Robust space probes, ubiquitous computing Robots That Navigate Hallway robots, Field robots, Underwater explorers, stunt air vehicles Cooperating Robots Cooperative Space/Air/Land/Underwater vehicles, distributed traffic networks, smart dust. Accomplished by: Case studies, invited lectures & final projects.

4 Immobile Robots in Space

5 courtesy NASA Ames

Autonomous Systems use Models to Anticipate or Detect Subtle Failures NASA Mars Habitat Crew Chamber Airlock Plant Growth Chamber CO 2 lighting system pulse injection valves flow regulator 1 flow

6 Autonomous Systems use Models to Anticipate or Detect Subtle Failures NASA Mars Habitat Crew Chamber Airlock Plant Growth Chamber CO 2 lighting system pulse injection valves flow regulator 1 flow regulator 2 CO 2 tank CO 2 concentration (ppm) crew requests entry to plant growth chamber crew enters chamber lighting fault time (minutes) crew leaves chamber chamber control

7 The Role of Robots in Human Exploration

8 Robonaut: Robotic Assistance For Orbital Assembly and Repair

9 Exploration by Quadrapeds and Bi-Peds Marc Raibert, MIT Leg Lab & Boston Dynamics

10 Outline Examples of Robots as Explorers Course Objectives Student Introductions and Goals Introduction to Model-based Programming

11 Course Objective 2 To understand advanced methods for creating highly capable cognitive robots. Localize in World Interpret Scenes Monitor & Diagnosis Manage Dialogue Plan Activities Execute & Adapt Map and Explore Navigation & Manipulation Manipulation Accomplished by: Lectures on advanced core methods ~ Implement & empirically compare two core methods.

12 Lectures: Planning and Acting Robustly Monitoring, and Diagnosis Diagnosing Multiple Faults Constraint-based Monitoring Hybrid Monitoring and Estimation Planning Missions Planning using Informed Search Planning with Time and Resources Robust Plan Execution Through Dynamic Scheduling Reactive Planning and Execution Plan Activities Monitor & Diagnosis Execute & Adapt

13 Lectures: Interacting With The World Simultaneous Localization and Mapping Basic SLAM Vision-based SLAM Cognitive Vision Visual Interpretation using Probabilistic Grammars Context-based Vision Localize in World Navigation & Manipulation Probabilistic Path Planning Exploring Unknown Environments Human - Robot Interaction Discourse Management & Nursebot Social Robotics Navigation & Manipulation Interpret Scenes Manage Dialogue Map and Explore Manipulation

14 Lectures: Fast, Large-scale Reasoning Optimality and Soft Constraints Optimal CSPs and Conflict-Learning Valued CSPs and Dynamic Programming Solving CSPS through Tree Decomposition Incremental Methods Incremental Satisfiability Incremental Scheduling Incremental Path Planning Incremental Reasoning Any-Time Enumeration Structural Decomposition Symbolic State Space Encodings

15 Topics On Cognitive Robot Capabilities Robots that Plan and Act in the World Robots that Deftly Navigate Planning and Executing Complex Missions Robots that Are State-Aware Robots that Find Their Way In The World Robots that Deduce Their Internal State Robots that Preplan For An Uncertain Future Theoretic Planning in a Hidden World State and Fault Aware Systems

16 Course Objective 3 To dive into the recent literature, and collectively synthesize, clearly explain and evaluate the state of the art in cognitive robotics. Accomplished by: Group lectures on advance topic One 40 minute lecture per student tutorial article on ~2 methods, to support lectures. Groups of size ~2.

17 Course Objective 4 To apply one or more core reasoning methods to create a simple agent that is driven by goals or rewards Localize in World Interpret Scenes Monitor & Diagnosis Manage Dialogue Plan Activities Execute & Adapt Map and Explore Navigation & Manipulation Manipulation Accomplished by: Final project during half of course Implement and demonstrate one or more reasoning methods in a simple cognitive robot scenario (simulated or hardware). Final project report. Short project demonstration.

18 Outline Examples of Robots as Explorers Course Objectives Student Introductions and Goals Introduction to Model-based Programming

Spacecraft Autonomy. Seung H. Chung. Massachusetts Institute of Technology Satellite Engineering Fall 2003

Spacecraft Autonomy. Seung H. Chung. Massachusetts Institute of Technology Satellite Engineering Fall 2003 Spacecraft Autonomy Seung H. Chung Massachusetts Institute of Technology 16.851 Satellite Engineering Fall 2003 Why Autonomy? Failures Anomalies Communication Coordination Courtesy of the Johns Hopkins