1. Robotics Introduction Robot Hardware Robotic Perception Planning to Move Dynamics and Control Robotic Software Applications

2. Introduction Robots are equipped with effectors. Effectors Actuators Assert a force on Communicates a the environment command to an effector

3. Types of Robots 1.Manipulators Anchored to the workplace. Common industrial robots. 2. Mobile Robots Move using wheels, legs, etc. Examples: delivering food in hospitals, autonomous navigation, surveillance, etc.

5. Types of Robots 3.Hybrid (mobile with manipulators) Examples: humanoid robot (physical design mimics human torso) Made by Honda Corp. in Japan.

7. Robotics Introduction Robot Hardware Robotic Perception Planning to Move Dynamics and Control Robotic Software Applications

8. Robot Hardware Sensors: a.Passive sensors. True observers such as cameras. b. Active sensors Send energy into the environment, like sonars.

11. Sensors Examples of sensors: Tactile sensors (whiskers, bump panels) Global Positioning System Imaging sensors Odometry (distance travelled)

12. Effectors Characterized by the degrees of freedom DF. DF counts one for each independent direction of movement. 6 degrees of freedom are required to place an object at a particular orientation.

14. Other Types of Effectors Unlike wheels, legs can handle tough terrains, but they are slow on flat surfaces. Devices vary from one leg to dozens of legs. Robots can be dynamically stable dynamically unstable

16. Sources of Power The electric motor is the most popular source But you may also see: Pneumatic actuation using compressed gas. Hydraulic actuation using pressurized fluids.

17. Robotics Introduction Robot Hardware Robotic Perception Planning to Move Dynamics and Control Robotic Software Applications

18. Robotic Perception Can be illustrated using a Bayesian Belief Network. It can be defined as a temporal inference from sequences of actions and measurements.

20. Other Robotic Tasks 1.Localization 2.Mapping 3.Perception of a.Temperature b.Odors c.Acoustic signals Quantities can be estimated probabilistically.

21. Robotics Introduction Robot Hardware Robotic Perception Planning to Move Dynamics and Control Robotic Software Applications

22. Planning to Move Types of motion: a.Point-to-Point. Deliver robot to target location. b.Compliant motion. Move while in contact to an obstacle (robot pushing a box).

23. Configuration Space Working Space: Spatial coordinates. Problem: not all coordinates are attainable Configuration Space: Represent robot joints. With two joints we need two angles (e.g., for shoulder and elbow).

25. Configuration Space The space can be decomposed into two subspaces: a.Free space. Space of attainable configurations. b. Occupied Space. Space of unattainable configurations.

29. Methods to Move Cell Decomposition. Decompose the free space into a number of contiguous regions, called cells. The problem is a discrete graph search problem.

31. Methods to Move Cell Decomposition. Disadvantages: a.Limited to low-dimensional configurations. b.Cells may be “mixed”. (solution: make cells more granular). c.Path may get too close to obstacles. (solution: use a potential field).

32. Potential Field A function defined over state space. Value grows with distance to closest obstacle. Tradeoff: Minimize path length to goal while staying away from obstacles.

35. Skeletonization Reduce free space to a one-dimensional representation. Lower representation is called a skeleton. Example is a Voronoi graph. (points equidistant to two or more obstacles). Steps: -) Follow Voronoi graph until close to target -) Leave graph and move to target.

37. Probabilistic Roadmap Create random graph by creating a large number of configurations. Discard those that do not fall into free space. Then join any two nodes by an arc if it is easy to reach one node from the other. Method is incomplete but scales better to high dimensional configurations.

39. Robotics Introduction Robot Hardware Robotic Perception Planning to Move Dynamics and Control Robotic Software Applications

40. Dynamics and Control Keeping a robot on track is not easy. Use a controller to keep the robot on track. Controllers that provide a force in negative proportion to the observed error are known as P controllers.

42. Dynamics and Control Let y(t) be the reference path. The control generated by the controller has the form: a(t) = K ( y(t) – x(t) ) K: gain parameter

44. Dynamics and Control To achieve stability we use a PD controller P – proportional D – derivative a(t) = K1 ( y(t) – x(t) ) + K2 d ( y(t) - x(t) ) / dt K1: gain parameter K2: differential component

46. Reactive Control In some cases reflex-agents are more appropriate. When a leg’s forward motion is blocked, Simply retract it, lift it higher, And try again.

48. Robotics Introduction Robot Hardware Robotic Perception Planning to Move Dynamics and Control Robotic Software Applications

49. Robotic Software Three layer architecture reactive layer ( low-level control) executive layer (which reactive behavior to invoke?) deliberate layer (planning)

50. Robotics Introduction Robot Hardware Robotic Perception Planning to Move Dynamics and Control Robotic Software Applications

51. Industry and Agriculture Assembly lines Harvest, Mine Excavate earth Transportation Autonomous helicopters Automatic wheelchairs Transport food in hospitals

52. Applications Hazardous environments Cleaning up nuclear waste Collapse of World Trade Center Transport bombs Exploration Surface of Mars Under the sea Military activities Health Care (surgery) Personal Services

53. Applications Health Care Surgery Personal Services Entertainment Dog-like robots Human Augmentation

57. A Video https://www.youtube.com/watch?v=6feEE716UEk