1. Behavior- Based Approaches Behavior- Based Approaches

2. Finishing up robotic architecture Reactive control Motor Schemas Subsumption

3. Overview Robot architecture from the bottom up Getting around Perceiving the world

4. Overview Reasoning representing space motion planning

5. Overview Handling uncertainty sensor fusion building maps localization

6. Overview Vision -- just another sensor ?

7. Overview Sonar Sound Navigation and Ranging –Sonar provides useful information about objects very close to the robot and is often used for fast emergency collision avoidance. Camera data –machine vision –structured light sensors –cross beam sensors –parallel-beam sensors

8. ARCHITECTURES ARCHITECTURES How the job of generating actions from percepts is organized Concerned to Autonomous mobile robot in dynamic environments The design of robot architectures is essentially the same agent design problem that was discussed

9. Classical architecture Shakey 1969, demonstrated the importance of experimental research in bringing to light unsuspected difficulties –difficulties of general problem solving integrating geometric and symbolic representation of the world –low level actions –macro-operators –error detection –recovery capabilities

10. Situated automata Since the mid 1980s, a significant minority of AI and robotics researchers have begun to question the “classical” view of intelligent agent design based on representation and manipulation of explicit knowledge In robotics, the principal drawback of the classical view is that explicit reasoning about the effects of low-level actions is too expensive to generate real time behavior

11. Situated automata Finite state machine whose inputs are provided by sensors connected to the environment and whose outputs are connected to effectors Situated automata provide a very efficient implementation of reflex agents with state

12. Rosenschein’s basic design Theorem: Any finite-state machine can be implemented as a state register together with a feed-forward circuit that updates the state based on the sensor inputs and the current state, and another circuit that calculates the output given the state register Execution time for each decision cycle is small

14. CONFIGURATION SPACES: A FRAMEWORK FOR ANALYSIS CONFIGURATION SPACES: A FRAMEWORK FOR ANALYSIS Both the configuration of the robot’s body and the locations of the objects in physical space are defined by real-valued coordinates. –It is therefore impossible to apply standard search algorithms in any straightforward way because the number of states and actions are infinite. The configuration space is mathematical tool for design and analyzing motion planning algorithms.

15. Robot Architectures how much / how do we represent the world internally ? None. Just what we need. Just the current world. As much as possible. 1234 Purely Reactive Control Absolute Control SPA architecture Subsumption paradigm Motor Schema

16. how much / how do we represent the world internally ? Just the current world. 2 Purely Reactive Control Decision-making based only on the current sensor readings. For the survivor robot assignment (A, part 1): int computeRotationalVelocity(…) Robot Architectures

17. One view of reactive control Control is a function of the sensed data. Case 1: If sonars 12, 13, or 14 Look at the front nine sonar values-- which are closest ? Turn left at 20 deg./sec Case 2: If sonars 15, 0, or 1 Turn left at 40 deg./sec Case 3: If sonars 2, 3, or 4 Turn right at 20 deg./sec 0 1 2 3 4 15 14 13 12

18. Another view of reactive control Direct mapping from the environment to a control signal goal-seeking behaviorobstacle-avoiding behavior

19. Robot Architecture how much / how do we represent the world internally ? Just what we need. 3 Subsumption paradigm Motor Schema Motor schemas compose simple reactions by adding the outputs that each would send to the robot. Individual schemas may contain state Ron Arkin @ Georgia Tech

20. Behavior Summer vector sum of the avoid and goal motor schemas path taken by a robot controlled by the resulting field

21. Additional primitives Direct mapping from the environment to a control signal go! schemacorridor-centering schema

22. A more complex task Direct mapping from the environment to a control signal larger composite task

23. Another primitive Direct mapping from the environment to a control signal larger composite task random motion schema

24. Local minima Noise allows a system to “jump out” of local minima. the problem a solution

25. Bigger deadends... How to get out of larger wells ?

26. uses memory of where the robot has been past-avoiding motor schema Bigger deadends...

27. Another example Keeping away from past locations...

28. Inspiration

29. Study of how animals react to different stimuli Toads (Arbib 87) Vowels Rodents (Hull 1934)Inspiration

30. Beyond subsumption... 1995 Polly Navlab & ALVINN

31. Polly Ian Horswill @ MIT