1. 1 Autonomous Foraging in a Simulated Environment

2. 2 Introduction Autonomous foraging: the scenario  Robots from the Matrix, harvesting humans and avoiding mannequins  Multiple robots, laying pheromones to maximize harvesting efficiency  Dark post-industrial environment

3. 3 Hybrid Architecture Mostly reactive  No internal map  React immediately to sensor data  Poses challenges for efficiency  Difficult to fix minima Partially deliberative  Track relative offset from goal  Some ordering exists  Allows for some degree of predictability

4. 4 Behavior Network

5. 5

6. 6 Module Summary

7. 7 Sensor Goals Link specific sensors to specific goals  Obstacle distance/detection  Potential field measurement  Object discrimination Enable specific rules for architecture  Sensors must facilitate reactive behavior

8. 8 Sensors Laser range finder  Avoid obstacles in advance (less moves)‏  Limited range due to fog, smog, and “gloom” Thermal sensor  Detect heat emitted by humans  Inverse Euclidean distance from object center used as gradient 2 color sensors  One for humans, one for mannequins  Both are semi-active for goal (where all other humans are stored)‏

9. 9 Sensor Models Laser range finder (front)‏  Returns distance (integer)‏  Assume accuracy for distances of 1 to 6 squares  Used for obstacle detection Thermal sensor (front)‏  Returns 3 x 3 matrix (floating point)‏  Assume 10% error per grid  Used for object detection 2 color sensors (bottom)‏  Returns wavelength intensity (floating point)‏  Assume 2% error  Used for object detection/discrimination

10. 1010 Reactive Components sensor_read; thermalsum = sum( sum( robot.thermal ) ); % detect_reward if robot.green >= 0.8 & robot.carrying == TYPE_BLANK robot_grab; end % detect_avoid if robot.blue >= 0.8 & robot.carrying == TYPE_BLANK disp(' - avoidance detected' ); end % detect_goal if ( robot.blue >=.5 -.2 ) & ( robot.blue =.5 -.2 ) & ( robot.green <= 0.5 +.2 )‏ % drop_object if robot.carrying ~= TYPE_BLANK robot_drop; end

11. 1 Detect Object if thermalsum > 0 & robot.carrying == TYPE_BLANK sumleft = sum( robot.thermal( 1:3, 1 ) ); sumcenter = sum( robot.thermal( 1:3, 2 ) ); sumright = sum( robot.thermal( 1:3, 3 ) ); % detect_obstacle if robot.laser == 1 if randint( 0, 1 ) == 0 robot_moveleft; else robot_moveright; end end randomly moves left or right once to avoid obstacle

12. 1212 Detect Object if sumcenter >= sumleft & sumcenter >= sumright robot_move( robot.dir ); elseif sumleft >= sumcenter & sumleft >= sumright if robot.thermal( 3, 1 ) > robot.thermal ( 1, 1 )‏ robot_turnleft; if randint( 0, 1 ) == 1 robot_turnleft; end robot_move( robot.dir ); else robot_move( robot.dir ); robot_turnleft; end handles movement towards heat source

13. 1313 Detect Object else if robot.thermal( 3, 3 ) > robot.thermal ( 1, 3 )‏ robot_turnright; if randint( 0, 1 ) == 1 robot_turnright; end robot_move( robot.dir ); else robot_move( robot.dir ); robot_turnright; end end % sumcenter,left,right end handles movement towards heat source

14. 1414 Move to Goal –if robot.laser >= 1 & robot.laser < 3 – – % perturb direction – if randint( 0, 1 ) == 0 – robot_turnleft; – else – robot_turnright; – end – – % move away from obstacle – robot_move( robot.dir ); –else – % move toward goal – if robot.x > robot.goal.x – robot_move( W ); – elseif robot.x < robot.goal.x – robot_move( E ); – end – – if robot.y > robot.goal.y – robot_move( S ); – elseif robot.y < robot.goal.y – robot_move( N ); – end

15. 1515 Wander Pattern

16. 1616 if thermalsum == 0 if robot.laser == 1 if wander_parity == 0 – robot_turnleft; – else – robot_turnright; – end – – sensor_read; – – % test if in corner – if robot.laser == 1 – if wander_parity == 0 – robot_turnleft; – else – robot_turnright; – end – else – for i = 1 : 5 – robot_move( robot.dir ); – end – – if wander_parity == 0 – robot_turnleft; – else – robot_turnright; – end – end % if robot.laser == 1 – – wander_parity = ~wander_parity; – end % if robot_laser == 1 – –robot_move( robot.dir ); –end % if thermalsum == 0 robot_turnleft and robot_turnright turn the robot left/right 45º

17. 1717 Original Plan Planned for multiple robots  Use implicit communication (stigmergy) through use of pheromones Follow own pheromone trails back to sources of rewards, to goal, and around obstacles Avoid other pheromone trails to prevent redundant searching  Ideally more robots could be added without changing any code

18. 1818 Actual Results Ran out of time!  Have single robot with no pheromones Inefficient obstacle avoidance Inefficient coverage of area  Some singularities may exist Rare looping around rewards (depends on environment and robot direction)‏  3041 moves, 1232 turns (on average)‏ Taken from 10 simulation runs Moves ranged from 4633-2049 Turns ranged from 972-1470

19. 1919 Actual Results 25 separate MATLAB files  1225 lines of code total  193 lines for forage script  276 lines for display  5455 elements using 48694 bytes  7 scripts, 47 functions, 10 subfunctions

20. 2020 Actual Results

21. 2121 Future Work Add pheromone trails and multiple robots Enhance obstacle avoidance and detection Restructure reactive behavior code  Perhaps place code so that executed every time move or every time sensors are read Force every action to update simulation figure

22. 2 What We Learned Reactive approach demonstrates Braitenberg teachings  Designing simple rules to generate intended emergence is tough  Appearance of free will? “the hobgoblin of philosophy”  Inductive behavior analysis is tougher than deductive Simple interactions may be the explanation

23. 2323 Simulation