Rapid Integration and Calibration of New Sensors Using the Berkeley Aachen Robotics Toolkit (BART)

TL;DR

This paper discusses the rapid integration and calibration of new sensors in autonomous vehicles using the Berkeley Aachen Robotics Toolkit (BART), emphasizing systems engineering challenges and solutions.

Contribution

It introduces a methodology for quick sensor integration and calibration within BART, addressing practical limitations in autonomous vehicle development.

Findings

Effective sensor calibration procedures developed

Reduced integration time for new sensors

Enhanced robustness in autonomous systems

Abstract

After the three DARPA Grand Challenge contests many groups around the world have continued to actively research and work toward an autonomous vehicle capable of accomplishing a mission in a given context (e.g. desert, city) while following a set of prescribed rules, but none has been completely successful in uncontrolled environments, a task that many people trivially fulfill every day. We believe that, together with improving the sensors used in cars and the artificial intelligence algorithms used to process the information, the community should focus on the systems engineering aspects of the problem, i.e. the limitations of the car (in terms of space, power, or heat dissipation) and the limitations of the software development cycle. This paper explores these issues and our experiences overcoming them.