Transcript Slide 1

Designing a Small-Scale Autonomous Path-Finding Robot
Blake Hayman
Dr. Takis Zourntos, Nebu Mathai
Texas A&M University, Electrical & Computer Engineering NSF/DOD REU
Research Methods
Abstract & Purpose
Our eventual purpose with this project is to create a
fully analog small-scale autonomous robot that can
home in on a specific target autonomously.
However, this path-finding robot is still in the
prototyping and algorithm testing phase. We are
thus a bit more lenient on using digital parts, and
the design is not expected to be perfect. However,
even with some digital components, our robot’s
design should be very similar to the expected final
product.
Block Diagram of System
Before researching anything, you first look at your project’s predecessors. We examined several robot projects
that were meant to mimic life, and we looked at as many as could be found. Many older projects were not welldocumented, but much work was generated in this field in the late ‘90s.
Prototype Schematic
Source Sampling:
Gallagher, John C. “The Once and Future Analog Alternative: Evolvable Hardware and Analog Computation.” Proceedings of
2003 NASA/DOD Conference on Evolvable Hardware. IEEE 2003.
Holland, Owen. “The First Biologically Inspired Robots.” Robotics, vol. 21, pg. 351 – 363.
Kumagai, Jean . “Halfway to Mars,” IEEE Spectrum. March 2006.
Walter, W. Grey – “A Machine That Learns.” Scientific American, vol. 185, is. 5, pg. 60-63. August 1951.
Walter, W. Grey – “An Imitation of Life.” Scientific American, vol. 182 pg. 42-45. 1950.
Once an analysis of previous attempts is complete, we decide ways to build upon them and introduce new ideas.
With the new ideas, we research methods of implementation and begin searching out pieces for the robot’s
physical design.
Design
Algorithms & Subsystem Control
The sensor system contains two microphones and an ultrasonic rangefinder that receive data from the
environment. The microphones’ analog signals must go through additional conditioning (an amplifier and a filter
each) before they can be sent to the RIO FPGA (brain).
The RIO first converts the sensor system’s analog signals to digital for processing; then, it performs calculations
based on the signal data to create data useful for the control algorithm. The dynamic systems-based algorithm will
control the actuation and behavior of the robot and send output to the motor control functions based on its
specified behaviors.
The motor control functions then send desired velocities in the form of analog voltages to the motors, which
actuate based on this signal. This actual velocity is read by shaft encoders, which send digital signals back to the
motor control functions for correction processing. The drive shafts interact with gear systems, the chassis, and
wheels before outputting a change to the environment (actuation).
Results & Conclusions
The robot should be a Powered Brain with
Sensors and Motors that interacts with its
Environment, fleshed out in more detail.
A 17-page PDF document that summarizes our work over the summer, our recommendations as to design and part
choice, and justification of our choices.
Nine weeks is generally not enough time to finish a paradigm-shifting project like ours. Research on creating an
autonomous analog path-finding robot will continue into the Fall with new undergrad 405 and 485 students, who
will implement and improve on our prototype design.
Acknowledgements
Dr. Takis Zourntos
Anthony Pham
Nebu Mathai
Marcus Dunn
Emily Weisbrook