Outline. Introduce yourself!! Class information and logistics. What is planning? Motivational Examples
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1 Outine Introduce yoursef!! Cass information and ogistics What is panning? Motivationa Exampes What is CIS 6930 Introduction to Panning Agorithms about?
2 About the instructor: Name: Leonardo Bobadia, Ph.D B.E Computer Systems and Engineering. (Nationa University of Coombia) M.Sc Statistics (Nationa University of Coombia) Ph.D Computer Science (University of Iinois at Urbana-Champaign) Research interests: Robotics, Artificia Inteigence, Cyber-Physica Systems
3 About the instructor: Leonardo Bobadia, Assistant Professor Meeting times: Tuesday/Thursday 9:30am10:45am ECS 235 Office:ECS 212b Phone: Tuesday/Thursday 11:00am-12:00pm or by appointment
4 Introduce yoursef! -Name -Year of PhD/Master -Area -Advisor -Why are you interested in the cass? -Your background, casses you have taken in Agorithms, Statistics, Differentia Equations
5 What is panning? Robotics -A fundamenta need in Robotics is to have agorithms that convert high-eve description of task from human into ow-eve. Piano Movers probem From
6 What is panning? Contro Theory -Contro theory concerns designing inputs to physica systems described by differentia equations. Exampes: Mechanica systems, cars or aircraft Eectrica systems: Noise fiters Other areas: Chemistry, economics, socioogy Finding a execution feedback poicy to respond during
7 What is panning? Artificia Inteigence -More discrete or ogic favor A finite set of actions that can be appied to a discrete set of states
8 Commonaities -Different communities Artificia Inteigence, Contro Theory, Robotics has used the term panning. In this cass we wi consider panning as a branch of agorithms Mosty focus on agorithmic and computationa issues Some terminoogy: Robotics: Robot or decision maker Artificia Inteigence: Agent, inteigent agent Contro: Controer (pan are refered as poicies) Game Theory: Payers
9 Some interesting questions: -What is a pan? - How is a pan represented? -How is it computed? What is supposed to achieve? How is its quaity evauated? How is going to use it?
10 Motivationa Exampes: Discrete Puzzes, Operations, and Scheduing First part of the cass wi cover discrete panning This has been usefu in puzzes ike Rubik's cube and siding tie puzzes They can be appied to games such as chess or bridge
11 Motion Panning Puzze This puzze requires panning in a continous space
12 Seaing cracks in automotive assemby A CAD mode of the robot workce is input for the motion panning software
13 Virtua humans and humanoid robots
14 Navigating Mobie Robots Mapping, Locaization, and Navigation.
15 Parking Car and Traiers Differentia constrains
16 Fying Through The Air Differentia constrains
17 Designing Better Drugs
18 Basic Ingredients of Panning State: State space capture a possibe situation that coud arise What is the state for a robot in a 2D environment? In a tie puzze? In the case of the heicopter Discrete (finite or countaby infinite) Continous (uncountaby infinite)
19 Basic Ingredients of Panning Time: A panning probems invove a sequence of decision appied over time Expicity: Driving a car as quicky as possibe Impicity: Soving a Rubik's cube Piano mover probem Actions: A pan generate actions that manipuate the state. Caed actions and operators in AI, and inputs and contros Initia and goa states: A panning Probem start in an initia state and try to arrive to a specific goa, the actions are seected in a way that tries to make this happen.
20 Basic Ingredients of Panning Criterion: 1. Feasibiity: Find a pan that causes arriva at a goa state, regardess of its efficiency 2. Optimaity: Find a feasibe pan that optimizes performans, in addition to ariving at a goa state. Pan: A sequence of actions to be taken -Or depending on the state (feedback or reactive) Some time the state can not be measured (information state)
21 Cass Structure Part 1. Discrete Panning Part 2. Motion Paning (Continuous Panning) Part 3. Panning Under Differentia Constrains Part 4. Decision Theoretic Panning (Panning Under Uncertainty)
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