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SIPHER Students: Javier Lara, Darren Lamison-White Graduate Student Advisors: Ethan Jackson, Ryan Thibodeaux Controlling Robots: Controlling Robots: Long distance, straight-line navigation of an Long distance, straight-line navigation of an unreliable robot with optical waypoints unreliable robot with optical waypoints Differential Gear System Mechanically detects the difference in motor speeds. If the motors are rotating at the same speeds, the differential (gray piece) will not move. However, if there is a difference in motor speeds then the differential will move, providing some amount of mechanical correction. A rotation sensor detects this difference and uses it as an error signal for the PID controller. Mechanical Components Wheel and Caster System The robot is designed with two large wheels, each of which is powered by a motor. The mass of the robot is concentrated over these wheels so that the geometric center and center of mass are aligned as much as possible. Much of this weight is due to batteries that power the robot. A caster on the rear of the platform adds stability, without requiring additional control. Optical Waypoints The optical waypoints allow the robot to periodically correct its orientation. The robot is equipped with two optical sensors that can distinguish colors, so the waypoint is colored with three high contrast colors. The start of the waypoint is marked by a horizontal white bar. Once the starting point has been recognized, the robot tries to place the left sensor on black and the right sensor on green. The contours of the waypoint allow it to make corrections until this final configuration is reached. Embedded Control Main Control Logic The control logic alternates between PID control (see below) and optical waypoint navigation. The optical waypoint navigation makes large corrections until it detects a left sensor on black and a right sensor on green. After this alignment event, the corrections decrease in strength. PID resumes after an alignment event is reproduced two times. If the robot leaves the waypoint before observing these events, it reverses to reacquire the waypoint. PID Controller The PID controller uses rate of drift from the centerline as an error signal. The robot sensors cannot monitor the actual wheel turns, only the axel rotation. As a result, this error signal is an estimate of the true drift. COEFFICIENTS: K P = 126 K I = 7.2 K D = 20 Introduction Straight-line locomotion is an essential primitive in most robotic platforms, yet it is difficult to achieve due to numerous error sources that act on the robot during locomotion. This is especially true for inexpensive robotic platforms that can be distributed in large numbers over long distances. The goal of this project was to implement reliable straight-line navigation over long distances with an inexpensive unreliable robot. Unreliable and Resource Constrained Inexpensive robot platforms are unreliable and resource constrained for numerous reasons. We used the Lego Mindstorm robots as an example of such a platform. At a cost of only several hundred dollars per kit, the platform is cheap, but it has a number of disadvantages: Only 32K of memory, with RTOS footprint, only 14K of user space to implement control algorithms. Light sensors can only detect drastically different colors Rotation sensors cannot detect actual rotation of wheel, only of axel. Maximum on three sensors and actuators per robot. No communication mechanisms for communication to a base station or other robot. Solution This problem was solved by creating a synergy between robot mechanics and embedded control. The robot was design to mechanically reduce as much error as possible. A PID controller operating on top of the robot could reduce error to a 1-foot off-axis displacement per 20 feet of on-axis locomotion. The accumulation of error was periodically eliminated with cheap optical waypoints that the robot could use to realign itself. Results The robot can successfully navigate long distances over multiple waypoints. Approximately 1 foot

SIPHER Students: Javier Lara, Darren Lamison-White Graduate Student Advisors: Ethan Jackson, Ryan Thibodeaux Controlling Robots: Long distance, straight-line

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Page 1: SIPHER Students: Javier Lara, Darren Lamison-White Graduate Student Advisors: Ethan Jackson, Ryan Thibodeaux Controlling Robots: Long distance, straight-line

SIPHER Students:Javier Lara, Darren Lamison-White

Graduate Student Advisors: Ethan Jackson, Ryan Thibodeaux

Controlling Robots: Controlling Robots:

Long distance, straight-line navigation of an unreliable robot with Long distance, straight-line navigation of an unreliable robot with optical waypointsoptical waypoints

Differential Gear System Mechanically detects the difference in motor speeds. If the motors are rotating at the same speeds, the differential (gray piece) will not move. However, if there is a difference in motor speeds then the differential will move, providing some amount of mechanical correction. A rotation sensor detects this difference and uses it as an error signal for the PID controller.

Mechanical Components

Wheel and Caster System

The robot is designed with two large wheels, each of which is powered by a motor. The mass of the robot is concentrated over these wheels so that the geometric center and center of mass are aligned as much as possible. Much of this weight is due to batteries that power the robot. A caster on the rear of the platform adds stability, without requiring additional control.

Optical WaypointsThe optical waypoints allow the robot to periodically correct its orientation. The robot is equipped with two optical sensors that can distinguish colors, so the waypoint is colored with three high contrast colors. The start of the waypoint is marked by a horizontal white bar. Once the starting point has been recognized, the robot tries to place the left sensor on black and the right sensor on green. The contours of the waypoint allow it to make corrections until this final configuration is reached.

Embedded Control

Main Control LogicThe control logic alternates between PID control (see below) and optical waypoint navigation. The optical waypoint navigation makes large corrections until it detects a left sensor on black and a right sensor on green. After this alignment event, the corrections decrease in strength. PID resumes after an alignment event is reproduced two times. If the robot leaves the waypoint before observing these events, it reverses to reacquire the waypoint.

PID Controller

The PID controller uses rate of drift from the centerline as an error signal. The robot sensors cannot monitor the actual wheel turns, only the axel rotation. As a result, this error signal is an estimate of the true drift.

COEFFICIENTS:

KP = 126

KI = 7.2

KD = 20

IntroductionStraight-line locomotion is an essential primitive in most robotic platforms, yet it is difficult to achieve due to numerous error sources that act on the robot during locomotion. This is especially true for inexpensive robotic platforms that can be distributed in large numbers over long distances. The goal of this project was to implement reliable straight-line navigation over long distances with an inexpensive unreliable robot.

Unreliable and Resource ConstrainedInexpensive robot platforms are unreliable and resource constrained for numerous reasons. We used the Lego Mindstorm robots as an example of such a platform. At a cost of only several hundred dollars per kit, the platform is cheap, but it has a number of disadvantages:

• Only 32K of memory, with RTOS footprint, only 14K of user space to implement control algorithms.• Light sensors can only detect drastically different colors• Rotation sensors cannot detect actual rotation of wheel, only of axel. • Maximum on three sensors and actuators per robot.• No communication mechanisms for communication to a base station or other robot.

SolutionThis problem was solved by creating a synergy between robot mechanics and embedded control. The robot was design to mechanically reduce as much error as possible. A PID controller operating on top of the robot could reduce error to a 1-foot off-axis displacement per 20 feet of on-axis locomotion. The accumulation of error was periodically eliminated with cheap optical waypoints that the robot could use to realign itself.

ResultsThe robot can successfully navigate long distances over multiple waypoints.

Approximately 1 foot