The purpose of this paper is to discuss the challenge of engineering robust intelligent robots. Robust
intelligent robots may be considered as ones that not only work in one environment but rather in all types of
situations and conditions. Our past work has described sensors for intelligent robots that permit adaptation
to changes in the environment. We have also described the combination of these sensors with a "creative
controller" that permits adaptive critic, neural network learning, and a dynamic database that permits task
selection and criteria adjustment. However, the emphasis of this paper is on engineering solutions which
are designed for robust operations and worst case situations such as day night cameras or rain and snow
solutions. This ideal model may be compared to various approaches that have been implemented on
"production vehicles and equipment" using Ethernet, CAN Bus and JAUS architectures and to modern,
embedded, mobile computing architectures. Many prototype intelligent robots have been developed and
demonstrated in terms of scientific feasibility but few have reached the stage of a robust engineering
solution. Continual innovation and improvement are still required. The significance of this comparison is
that it provides some insights that may be useful in designing future robots for various manufacturing,
medical, and defense applications where robust and reliable performance is essential.
Determining if a segment of property is suitable for use as an aircraft is a vitally important task that is currently performed by humans. However, this task can also put our people in harms way from land mines, sniper and artillery attacks. The objective of this research is to build a soil survey manipulator that can be carried by a lightweight, portable, autonomous vehicle, sensors and controls to navigate in assault zone. The manipulators permit both surface and sub surface measurements. An original soil sampling tube was constructed with linear actuator as manipulator and standard penetrometer as sampling sensor. The controls provide local control of the robot as well as the soil sampling mechanism. GPS has been selected to perform robot global navigation. The robot was constructed and tested on the test field. The results verified
the concepts of using soil sampling robot to survey runway is feasible.
The purpose of this paper is to describe the use of Global Positioning Systems (GPS) as geographic information and navigational system for a ground based mobile robot. Several low cost wireless systems are now available for a variety of innovative automobile applications including location, messaging and tracking and security. Experiments were conducted with a test bed mobile robot, Bearcat II, for point-to-point motion using a Motorola GPS in June 2001. The Motorola M12 Oncore GPS system is connected to the Bearcat II main control computer through a RS232 interface. A mapping program is used to define a desired route. Then GPS information may be displayed for verification. However, the GPS information is also used to update the control points of the mobile robot using a reinforcement learning method. Local position updates are also used when found in the environment. The significance of the method is in extending the use of GPS to local vehicle control that requires more resolution that is available from the raw data using the adaptive control method.
Conference Committee Involvement (1)
Intelligent Robots and Computer Vision XXVII: Algorithms and Techniques
18 January 2010 | San Jose, California, United States