Nathan Barnwell Final Report

Shot Bot

Intelligent Machines Design Laboratory

EEL 4665/5666

Instructors: Dr. A. Antonio Arroyo Dr. Eric M. Schwartz

TAs : Ryan Stevens

Tim Martin

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Table of Contents 1. Abstract ……………………………………………………………………………...……3 2. Executive Summery……………………………………………………………………….3 3. Introduction………………………………………………………………………………..3 4. Integrated System………………………………………………………………………….4 5. Mobile Platform…………………………………………………………………………...4 6. Actuation…………………………………………………………………………………..5 7. Sensors…………………………………………………………………………………….5 8. Behaviors………………………………………………………………………………….8 9. Experimental Layout and Results…………………………………………………………8 10. Conclusion……………………………………………………………………………….10 11. Documentation………………………………………………………………………...…11 12. Appendices……………………………………………………………………………….12

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Abstract

Shot Bot navigates through an arena, avoids obstacles that it encounters. Once the enemy colored beacon is located, and then launches a non-lethal shot at the target.

Executive Summary

Shot Bot searches for the enemy colored beacon with its projectile loaded and ready to fire. It navigates around obstacles using infrared proximity sensors, an ultrasonic sensor, and a bump sensor with some redundancy in order to ensure obstacle detection and avoidance. This obstacle avoidance and target searching state continues until the enemy beacon is spotted.

The state is changed to the alignment state once the target is spotted with Shot Bot’s IP camera. During this state, Shot Bot centers itself if the target is on the edges of the image and creeps forward if the target is in the centered. If the target is ever lost during the alignment state, Shot Bot returns to the obstacle avoidance and search state. Once the target is centered and at the bottom of the image, which indicates that the target is within firing range, Shot Bot shoots its projectile at the target.

Shot Bot isolates the beacon showing the enemy’s color using OpenCv and CVblobs. In the image processing code, the color of interest of interest is isolated using a color threshold and the areas of the color of interest are grouped into blobs. The smaller sized blobs are eliminated from consideration since there is a good chance that they could be a reflection or a false target. The center positions of the remaining blobs are then averaged and the average center location is stored, interpreted, and then sent out to Shot Bot using Xbee as a value that it can make sense of.

Introduction

The goal of Shot Bot is to locate and shoot at a specified target while avoiding any obstacles along the way. During a cycle, Shot Bot travels though an arena in search of an illuminated target. It navigates around obstacles until it locates its target, aligns itself, and then fires a non-lethal projectile at the target. Shot Bot integrates a combination of circuitry, logic, mobile platform, motor, servo, and sensor designs in order to carry out the behavioral goals.

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Integrated System

Shot Bot is an integrated system that allocates sensors, a microprocessor, controllers, motors, servos, an LCD display, and LEDs as seen in Figure 1. The sensors used for avoiding obstacles communicate with the microprocessor as inputs. These sensors include infrared detectors and an ultrasonic detector that function as proximity sensors and a bump sensor that detects collision. They are arranged in a manner that helps to minimize bind spots and maximize object position awareness. The IP camera captures images from the front of the laptop and sends this data to the laptop, which processes the video, and then the laptop sends information back to the microprocessor using Xbee. The microprocessor outputs to the motor and servo controllers, LCD display, and LEDs based on these inputs. Finally, the controllers output the desired voltage to the motors and servos which create actuation for this system.

Mobile Platform

Shot Bot has a two tier, circular mobile platform constructed from plywood so it will be both strong, easy to construct, and cost effective for this design. The base is a circular shape with cutouts for the wheels inside and centered on the base. This combination decreases obstacle collision while turning, protects the wheels from collision, and increases maneuverability. Additionally, the bottom tier has the motors mounted to it using brackets, the main circuit board, and the battery for powering the robot. Locating all of these components on the bottom tier lowers the center of gravity and increases stability. The top tier has the shooting mechanism and camera mounted on it so there is a minimized obstructed path for tracking and shoots the target.

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Actuation

The actuation in Shot Bot consists of two drive motors and a servo for controlling the shooting mechanism. The drive motors are from pololu.com (item #1105) and the servo is from sparkfun.com (sku: ROB-09347).

The drive motors are each 12V with a maximum stall torque of 200oz-in and maximum speed of 150 RPM. The motor also has 5A stall so if Shot Bot runs into a wall, the current drawn will not destroy the robot’s circuitry. The characteristics of this motor provide reasonable amount of speed while not being too fast to inhibit the constancy of the Shot Bot’s functions. The torque provides a sufficient amount of torque for moving Shop Bot around the arena. An internal gear ratio of 67:1 was selected so the gearing of the motor is as compact and tailored for this design. Calculations concerning the motors and their ability to satisfy the requirements for Shot Bot can be seen in Appendix A.1 and A.2

The drive motors have the wheels mounted directly to the motor shafts for a direct drive configuration. The motors are mounted next to each other in the center of Shot Bot so if both motors are rotating in opposite directions, the robot will either drive forward or reverse, depending on the electrical current direction. When the motors are rotating in the same direction, the robot will spin clockwise or counter clockwise and will do so on an axis in the center of the robot if identical signal magnitudes are given to the motor controllers. This configuration is beneficial for obstacle avoidance because Shot Bot can change directions in a space confined by its footprint.

A hacked servo will be used as a trigger for the firing mechanism. It operates at 5V and rotates 360° with a maximum speed of 65RPM. It also provides 49 oz-in of stall torque which is sufficient to spin the trigger cam that has to overcome the force of the spring on the firing lever.

Sensors

Shot Bot is equipped with infrared sensors, bump switches, an ultrasonic sensor and an IP camera in order to receive useful information from the surrounding environment.

Infrared proximity sensors are used for obstacle avoidance on Shot Bot. There is one on the left side and another on the right side of Shot Bot. The purpose of these sensors is to correct the path of Shot Bot if it is going collide with an obstacle on the side and allow it to maneuver accordingly. The IR proximity sensor used is the Sharp GP2Y0A21YK from sparkfun.com. This sensor has an effective range from 10cm to 80cm. The sensor emits an infrared pulse that reflects off of and is returned to the sensor which ultimately converts a distance into a signal that the microprocessor can understand. Figure 2 shows the voltage output of the IR proximity sensor based on the distance between the object and the sensor.

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A bump sensor will be attached to a bumper so if an obstacle bypasses the IR sensors and ultrasonic sensor, Shot Bot will be aware of its presence. The bump sensor used is a double-throw, single pole switch from pololu.com (item #1403).

The LV-MaxSonar-EZ0 is a 42 kHz ultrasonic sensor that is used on the front of the robot for detecting obstacles. The sensor emits an ultrasonic pulse and the time that it takes for the pulse to return to the sensor is output as an analog voltage. This voltage is sent to the microprocessor and can be interpreted as a distance. It has a beam angle of 70° which is wide enough to cover the front of the robot. The main purpose of this sensor is to avoid any collisions from the front that the infrared sensors may miss. With a range of about 8ft for objects greater than 0.25 in, this sensor will be able to detect objects before they need to be avoided. The ultrasonic sensor used is from sparkfun.com (sku: SEN-08502). Figure 3 shows the voltage output of the ultrasonic sensor based on the distance the object is away from the sensor in inches.

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These infrared proximity sensors, ultrasonic sensors, and the bump sensor work together so Shot Bot can detect and avoid obstacles. If there is an object that is in only in the threshold for the right or left infrared proximity sensors, Shot Bot rotates away from the object until it is back outside of the threshold distance. If an object is detected in the threshold range of the ultrasonic sensor in the front, Shot Bot rotates until the object is out of the way. If the bump senor is pressed, Shot Bot moves away from the object.

The Foscam FI8918W IP camera on Shot Bot is used for tracking the illuminated target. The IP camera communicates with a laptop running OpenCV 2.3 through a wireless router. The program grabs the video data from the IP camera and it isolates the target color from the surrounding environment. Then the software takes all of the blobs of that particular color, excludes blobs smaller that a threshold size, and places rectangles around the blobs that meet the size requirements. These centers of all the blob rectangles are computed and the average position of all the rectangle centers is determined based on their position in the frame. The data is then interpreted by the laptop, and a number corresponding to the particular case is then sent to Shot Bot.

The initial design for Shot Bot actually had a CMU camera instead of an IP Camera. However, after ordering the CMU camera seattlerobotics.com and waiting for 2 weeks, they never collected the money nor shipped the product and could not be contacted. At this point, I decided that I still wanted to have a camera on Shot Bot. Ultimately, the idea of viewing what Shot Bot sees on a laptop screen from a distance outweighed the increased complexly that would accompany this new design and the IP camera replaced that CMU camera.

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Behaviors

The three main states that Shot Bot operates in are search, obstacle avoidance, and the alignment and shooting states and can be seen in Figure 4.

During the obstacle avoidance/search state, Shot Bot systematically maneuvers until it locates obstacles or the target. When an obstacle is found by one of the IR sensors, ultrasonic sensor, or bump sensor, Shot Bot avoids it by altering its search maneuvering pattern which is the obstacle avoidance state. The alignment state occurs when the target is located by the camera. During this state, Shot Bot will move towards the target very slowly and corrects its course if it ever gets of course, until it is in range of the target. When it gets in range and position of the target, Shot Bot shoots it. If the target is ever lost during any state, it goes back to the obstacle avoidance/search state.

Experimental Layout and Results

Obstacle Avoidance

After testing the infrared proximity sensors on each side of the robot, it was determined that these sensors have a narrow range that created many blind spots on Shot Bot with only two infrared sensors. As a result, the primary obstacle avoidance configuration has a central ultrasonic proximity sensor in the middle since it has a wide and far range of detection. The two infrared sensors are going to be kept on the outsides of the mobile platform so Shot Bot can avoid obstacles on one particular side and correct the direction of Shot Bot if it gradually drifts into an obstacle. Additionally, it was discovered that the effective range for the infrared sensors

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is from 5 inches to 30 inches and that critical points in the obstacle avoidance code should account for at least 3 inches of uncertainty since output values tend to vary even at rest.

IP Camera

Setting up the IP camera with OpenCV ended up taking a lot of time and energy. OpenCV itself was challenging to setup, but ultimately investing the resources in it turned out to be a good decision. It is a powerful program that allows the laptop to grab data from the camera and interpret the data. An important discovery during this process was that two different IP cameras may have the same code to function with OpenCV, but the IP address format for grabbing the camera data can. After everything was set up, OpenCV became a very powerful tool.

Occasionally, it can be difficult getting the computer to communicate to the IP camera through the router since the IP address often changes. Once they are communicating, the camera works fantastic. The laptop can control the pan and tilt of the IP camera using the html page interface and I hope to be able to access those commands though OpenCV since it could make searching for the target a much easier task.

Tracking Objects

During testing, it became apparent that lighting conditions seemed to significantly affect the quality, ability, and consistency that the IP camera was able to detect a specific color. To overcome this many steps were taken as precautions to maximize the performance of Shot Bot.

On the target itself, there is a very bright blue light encased in a ping pong ball that is enclosed in a box with a window on only one side. The blue color was determined to be a preferred color to track since most outside obstacles are not the particular shade of blue that I chose. The ping-pong ball enclosure was used to disperse the light that was emitted from the LED so Shot Bot had a larger object to track and the bright light inside was chosen in order to reduce the effect of external light reflecting off of the object. The enclosed box with the window serves two purposes which are to block external light from the beacon and reflect any extra blue light from the beacon.

In the Shot Bot integrated system, programming precautions were taken in OpenCV. In OpenCV, CVblobs was used to get rid of any color noise and isolate the target. Averages of the blob positions were also used to track the target in increase the consistency that Shot Bot can track the target. Figure 4 shows how the image processing program isolates the target and creates a rectangle around the threshold image.

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Processing the Color

A major problem with the color tracking was in the color processing and the compatibility between OpenCV and my particular IP camera. This problem was never able to be fixed and many other classmates with the same IP camera experienced the same problem. A solution that I came up with compensated for the severe lag that occasionally occurred from the image processing. This solution only allowed Shot Bot to move in a particular state for a specified time interval every time it received new data from the Xbee. This means that when there was very little lag, Shot Bot appeared to be moving continuously and when the lag was severe, Shot Bot has jerky movement and even stops in place. This was Shot Bot does not keep moving until it is sure of the environment around it.

Conclusion

Shot Bot was constructed by cutting out and drilling all of the features of the mobile platform by hand which made modifications very easy to make, but at the cost of precision and the visual appeal. Then all of the components, like the motors, wheels, and sensors, were mounted into the desired place. This stage of the creation of Shot Bot did not give me too much trouble since I have some previous assembly experience.

The trickiest mechanical component of Shot Bot was the shooting mechanism that I personally designed and fabricated. My idea of a using a tear drop shaped cam as the trigger worked as I wanted and it minimized the number of moving components for the shooting system. It was very challenging to balance the servo torque and the force from the tension spring since the system seemed to be hyper sensitive to the relative position of all the components. The position of the components also greatly affected the trajectory characteristics of the projectile. After lots of trial and error with different combinations, I was able to get a relatively consistent shot that did not place a large strain on the servo.

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OpenCV gave me a lot of trouble and consumed a huge amount of time that I spent working on Shot Bot. Setting up was probably the worst part about it, but once I got it working, OpenCV became a very powerful image processing tool. It allowed color isolation and helped to exclude false color blobs using CVblobs.

After I had all of the individual components of Shot Bot working, I had to integrate the entire system which presented unanticipated challenges like the occasional lag in the image processing that I compensated for in coding. I also learned that complex obstacle avoidance created more problems than cases were it helped, so the simple solution turned out to be the best. I also had trouble with the Xbee data input was interfering with my servo and it was also solved using coding. Overall, I got the Shot Bot integrated system to work better than I expected considering the challenges that I was faced with.

The major difficulties I had with Shot Bot was in the programming portion since that is the area of the project that I have the least experience in and my limited knowledge of microprocessors also challenged me. Networking with other classmates was helpful because where my knowledge of a particular component was limited, other classmates where more knowledgeable and vice versa. Networking was helpful to both designers and ultimately led to more high quality projects. Additionally, networking allowed me to learn more about robotics than I would have been able to by searching though resources on my own.

If I were to do the project over again, I would try to have the image processing code with OpenCV done much sooner so I would have more time to make the code better and do more things with it like shape or face detection. I would also machine cut the shooting mechanism out of a stronger material like aluminum on a mill so it would be more durable and have more repeatable results. Additionally, I would add a servo controlled loader to the shooter so it could fire many more shots in a controlled manner.

Documentation

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Appendices

A.1 Maximum Robot Weight

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A.2 Maximum Robot Speed (no slipping)

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A.3 IR Output Value to Voltage Conversion

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A.4 Robot Code and OpenCV Code

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#$""

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#K""

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#L""

) ,542(<OCF=>:;<O.?>;>DP)l))!(#'"-))!"-'(-)(#+@%(F+25?H))"#5)&+25?HRK(5$/+2CoYAM)V,52(+9DU)) )) "-)C@&-?H.5+"%)GG)@&-?H.@&--(2M#'DU)) ) &"#5QR5)5(97)G)V@&-?H.5+"%P)) ) @&-?H.5+"%)G)@&-?H.@&--(2`(K"#P)) ) 2(5&2#)5(97P)) l)) (%,()2(5&2#)V@&-?H.5+"%mmP)l))14"'),542(?HC$/+2)$DU)) "-C@&-?H./(+')GG)@&-?H.@&--(2M#'DU)) ) V@&-?H./(+')G)$P)) ) @&-?H./(+')G)@&-?H.@&--(2`(K"#P) )) l) ) )) (%,()V@&-?H./(+'mm)G)$P)l))&"#5QR5)'+5+Y#`&-?HC14"'DU)) "-C@&-?H./(+')GG)@&-?H.5+"%D)2(5&2#)HP) 33#4)'+5+)54)@()2(+')) (%,()2(5&2#)OP) ) ) ) ) ) ) 33'+5+)54)@()2(+')l)Y=:CF=>:;?HR:b<R1($5DU)) ,542(?HCF=>:;?H.?>;>DP)l))!(#'"-))!"-'(-)(#+@%(F+25?O))"#5)&+25?ORK(5$/+2CoYAM)V,52(+9DU)) )) "-)C@&-?O.5+"%)GG)@&-?O.@&--(2M#'DU)) ) &"#5QR5)5(97)G)V@&-?O.5+"%P)) ) @&-?O.5+"%)G)@&-?O.@&--(2`(K"#P)) ) 2(5&2#)5(97P)) l)) (%,()2(5&2#)V@&-?O.5+"%mmP)l))14"'),542(?OC$/+2)$DU)) "-C@&-?O./(+')GG)@&-?O.@&--(2M#'DU)) ) V@&-?O./(+')G)$P)) ) @&-?O./(+')G)@&-?O.@&--(2`(K"#P) )) l) ) )) (%,()V@&-?O./(+'mm)G)$P)l))&"#5QR5)'+5+Y#`&-?OC14"'DU)) "-C@&-?O./(+')GG)@&-?O.5+"%D)2(5&2#)HP) 33#4)'+5+)54)@()2(+')) (%,()2(5&2#)OP) ) ) ) ) ) ) 33'+5+)54)@()2(+')

#R""

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#T""

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#X""

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$O""

) ) ) &+25t0<;:A`)G)F=>:;R<;:A`Ra_HHP)) ) ) &+25t0<;:A<)G)F=>:;R<nB?MR>=Zj<q:BjBF=RK$)s)F=>:;REnB?MR?Y=>`AM?RK$)s)F=>:;R<q=YzMRQ`Y;RK$P)) ) ) &+25t0`>F?<;:A>)G)F=>:;R`>F?<;:A>Ra_HHP)) ) ) &+25t0`>F?<;:A`)G)F=>:;R`>F?<;:A`Ra_HHP)) ) @2(+TP)) ) $+,()COhhHHDd)) ) ) &+25t0<;:A`)G)F=>:;R<;:A`ROhhHHP)) ) ) &+25t0<;:A<)G)F=>:;R<nB?MR>=Zj<q:BjBF=RK$)s)F=>:;REnB?MR?Y=>`AM?RK$)s)F=>:;R<q=YzMRQ`Y;RK$P)) ) ) &+25t0`>F?<;:A>)G)F=>:;R`>F?<;:A>ROhhHHP)) ) ) &+25t0`>F?<;:A`)G)F=>:;R`>F?<;:A`ROhhHHP)) ) @2(+TP)) ) $+,()COaJHHDd)) ) ) &+25t0<;:A`)G)F=>:;R<;:A`ROaJHHP)) ) ) &+25t0<;:A<)G)F=>:;R<nB?MR>=Zj<q:BjBF=RK$)s)F=>:;REnB?MR?Y=>`AM?RK$)s)F=>:;R<q=YzMRQ`Y;RK$P)) ) ) &+25t0`>F?<;:A>)G)F=>:;R`>F?<;:A>ROaJHHP)) ) ) &+25t0`>F?<;:A`)G)F=>:;R`>F?<;:A`ROaJHHP)) ) @2(+TP)) ) $+,()CJQQHHDd)) ) ) &+25t0<;:A`)G)F=>:;R<;:A`RJQQHHP)) ) ) &+25t0<;:A<)G)F=>:;R<nB?MR>=Zj<q:BjBF=RK$)s)F=>:;REnB?MR?Y=>`AM?RK$)s)F=>:;R<q=YzMRQ`Y;RK$P)) ) ) &+25t0`>F?<;:A>)G)F=>:;R`>F?<;:A>RJQQHHP)) ) ) &+25t0`>F?<;:A`)G)F=>:;R`>F?<;:A`RJQQHHP)) ) @2(+TP)) ) $+,()CgQhHHDd)) ) ) &+25t0<;:A`)G)F=>:;R<;:A`RgQhHHP)) ) ) &+25t0<;:A<)G)F=>:;R<nB?MR>=Zj<q:BjBF=RK$)s)F=>:;REnB?MR?Y=>`AM?RK$)s)F=>:;R<q=YzMRQ`Y;RK$P)) ) ) &+25t0`>F?<;:A>)G)F=>:;R`>F?<;:A>RgQhHHP)) ) ) &+25t0`>F?<;:A`)G)F=>:;R`>F?<;:A`RgQhHHP)) ) @2(+TP)) ) $+,()C]_HHHDd)) ) ) &+25t0<;:A`)G)F=>:;R<;:A`R]_HHHP)) ) ) &+25t0<;:A<)G)F=>:;R<nB?MR>=Zj<q:BjBF=RK$)s)F=>:;REnB?MR?Y=>`AM?RK$)s)F=>:;R<q=YzMRQ`Y;RK$P)) ) ) &+25t0`>F?<;:A>)G)F=>:;R`>F?<;:A>R]_HHHP)) ) ) &+25t0`>F?<;:A`)G)F=>:;R`>F?<;:A`R]_HHHP)) ) @2(+TP)) ) $+,()C]^_HHDd)) ) ) &+25t0<;:A`)G)F=>:;R<;:A`R]^_HHP)) ) ) &+25t0<;:A<)G)F=>:;R<nB?MR>=Zj<q:BjBF=RK$)s)F=>:;REnB?MR?Y=>`AM?RK$)s)F=>:;R<q=YzMRQ`Y;RK$P)) ) ) &+25t0`>F?<;:A>)G)F=>:;R`>F?<;:A>R]^_HHP)) ) ) &+25t0`>F?<;:A`)G)F=>:;R`>F?<;:A`R]^_HHP)) ) @2(+TP)) ) $+,()COO]JHHDd)) ) ) &+25t0<;:A`)G)F=>:;R<;:A`ROO]JHHP)) ) ) &+25t0<;:A<)G)F=>:;R<nB?MR>=Zj<q:BjBF=RK$)s)F=>:;REnB?MR?Y=>`AM?RK$)s)F=>:;R<q=YzMRQ`Y;RK$P)) ) ) &+25t0`>F?<;:A>)G)F=>:;R`>F?<;:A>ROO]JHHP)) ) ) &+25t0`>F?<;:A`)G)F=>:;R`>F?<;:A`ROO]JHHP)) ) @2(+TP)) ) $+,()CJgHhHHDd)) ) ) &+25t0<;:A`)G)F=>:;R<;:A`RJgHhHHP)

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