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In the name of Allah. Introduction to Robotics. Leila Sharif l_sharif@sharif.edu Lecture #4: The Big Picture. Last time we saw:. Controller Reactive Delibrative Hybrid Behaviour A brief history of robotics Feedback control Cybernetics Artificial Intelligence (AI)
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Introduction to Robotics • Leila Sharif • l_sharif@sharif.edu • Lecture #4: The Big Picture
Last time we saw: • Controller • Reactive • Delibrative • Hybrid • Behaviour • A brief history of robotics • Feedback control • Cybernetics • Artificial Intelligence (AI) • Early robotics • Robotics today
Lecture Outline • Why is robotics hard? • Degrees of Freedom (DOF) • holonomicity, redundancy • Legged locomotion • stability (static and dynamic) • polygon of support • Wheeled locomotion • Trajectory/motion planning
Why is Robotics hard? • Sensors are limited and crude • Effectors are limited and crude • State (internal and external, but mostly external) is partially-observable • Environment is dynamic (changing over time) • Environment is full of potentially-useful (and useless) information
Key Issues • Grounding in reality:not just planning in an abstract world • Situatedness (ecological dynamics): tight connection with the environment • Embodiment: having a body • Emergent behavior: interaction with the environment • Scalability: increasing task and environment complexity
Definition of Effector • An effector is any device that has an effect on the environment. • A robot’s effectors are used to purposefully effect the environment. • E.g., legs, wheels, arms, fingers... • The role of the controller is to get the effectors to produce the desired effect on the environment, based on the robot’s task.
Definition of Actuator • An actuator is the actual mechanism that enables the effector to execute an action. • E.g, electric motors, hydraulic or pneumatic cylinders, pumps… • Actuators and effectors are not the same thing. • Incorrectly thought of the same; “whatever makes the robot act”
Degrees of Freedom • Most simple actuators control a single degree of freedom (DOF) • Think of DOFs as ways in which a motion can be made (e.g., up-down, left-right, in-out) • E.g., a motor shaft controls one rotational DOF; a sliding part on a plotter controls one translational DOF.
Counting DOF • A free body in space has 6 DOF • 3 are translational (x, y, z) • 3 are rotational (roll, pitch, and yaw) • Every robot has a specific number of DOF • If there is an actuator for every DOF, then all of the DOF are controllable • Usually not all DOF are controllable • This makes robot control harder
Example: DOF of a Car • A car has 3 DOF: position (x,y) and orientation (theta) • Only 2 DOF are controllable • driving: through the gas pedal and the forward-reverse gear • steering: through the steering wheel • Since there are more DOF than are controllable, there are motions that cannot be done, like moving sideways (that’s why parallel parking is hard)
Actuators and DOFs • We need to make a distinction between what an actuator does (e.g., pushing the gas pedal) and what the robot does as a result (moving forward) • A car can get to any 2D position but it may have to follow a very complicated trajectory • Parallel parking requires a discontinuous trajectory, velocity, i.e., the car has to stop and go