Review and Ideas for future Projects

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Presentation transcript:

Review and Ideas for future Projects

Projects with robots for teens. What we already discussed. Line following robots Y shaped lines for robots that drive to selected locations. Robots following walls on corridors. Algorithms for mazes: Right Wall Following Algorithm (RWFA) Left Wall Following Algorithm (LWFA) Deterministic Switch from from RWFA and LWFA based on mapping the known part of maze to memory. Variants of searching mazes to find an exit. Deterministic and probabilistic combinational behavior based on input – output matrix and multiplication of matrix by vector. Combinational and State Machine based Braitenberg Vehicles

Analysis of a Braitenberg robot with memory LOGIC S1 J M1 Q M1 M2 K Q M2 S2 0= happy 1 =angry S1 S2 Q J K Q+ 1 S1 S2 Q Q+ M1 M2 1 S1 S2 Q Q+ M1 M2 1 S1 S2 Q Q+ 1

Analysis Analyze how this behaves in room with no light. Analyze how this behaves in room with light on floor, oriented towards robot. Analyze how this behaves in a maze. Draw snaphsots of movie of robot position , orientation and internal state in time 0= happy 1 =angry S1 S2 LOGIC M1 M2

Maze exit

Wall is on the left Robots marks his motion for Left Wall algorithm in blue exit

Robots maps its position in memory and now is back in the same point Robots marks his motion for Left Wall algorithm in blue exit

Robot moves to other wall X Robot starts left wall following algorithm (wall at left) Robot moves to other wall Robots marks his motion for Left Wall algorithm in crosses X X exit

Robot executes left wall following algorithm (wall at left) exit

Robot executes left wall following algorithm (wall at left) exit

Robot executes left wall following algorithm (wall at left) exit

Robot found the solution to exit by changing the wall in the corridor but still using the left wall following algorithm (wall at left) X X X X X X X X X X X X X X X X X X X X X X X X X exit

Projects with robots for teens Robot finding cans and bringing them to safe place. Robot attacking or escaping other robots. Robots boxing. Robots shooting one another. Robots fencing. Repeated Prisoner Dilemma for robots. Repeated Chicken for robots. Subsumption Architecture Maze Searching Genetic Algorithm Tree search

Advanced Line Following

SENSOR ARRAY 7 sensors Observe the order of variables from outside to the center MINIMUM DISTANCE BETWEEN SENSORS IS 1cm

THE PRIORITY ENCODER Number of sensor as output 7 sensors as inputs Problem: Design such priority encoder as a circuit using Kmaps

THE NO SURFACE LOGIC A 1 NS signal = no line detected B C A A 1 B B C A 1 NS signal = no line detected B C A A 1 B B C C NS signal = no line detected

INPUTS TO THE MICROCONTROLLER NS signal = no line detected NS GS A2 A1 A0 STATE IN ACTION 1 X No surface is detected Stop the motors No line is detected Execute the no line code (specially designed algorithm) A detects the line Sharp turn left B detects the line Sharp turn right C detects the line Turn left D detects the line Turn right E detects the line Move left F detects the line Move right G detects the line Go straight Forbidden state Software reset the processor

How this algorithm based on sensors works?

LINE FIND MODE

Generalizations Wall following Vision based Wall following Labyrinth problems Can collecting tasks

FLOW CHART

RESULT AND CONCLUSION The robot follows a line as demonstrated. It effectively overcomes problems such as “barren land syndrome” and line breaks. The hardware and software works as designed.

APPLICATIONS OF LINE FOLLOWING IDEAS Industrial automated equipment carriers Automated cars. Tour guides in museums and other similar applications. Second wave robotic reconnaissance operations.

LIMITATIONS Choice of line is made in the hardware abstraction and cannot be changed by software. Calibration is difficult, and it is not easy to set a perfect value. The steering mechanism is not easily implemented in huge vehicles and impossible for non-electric vehicles (petrol powered). Few curves are not made efficiently, and must be avoided.

…LIMITATIONS Lack of a four wheel drive, makes it not suitable for a rough terrain. Use of IR even though solves a lot of problems pertaining to interference, makes it hard to debug a faulty sensor. Lack of speed control makes the robot unstable at times.

FUTURE SCOPE Software control of the line type (dark or light) to make automatic detection possible. “Obstacle detecting sensors” to avoid physical obstacles and continue on the line. Distance sensing and position logging & transmission.