Learn More
This paper presents a vision-based localization and mapping algorithm for an autonomous mower. We divide the task for robotic mowing into two separate phases, a teaching phase and a mowing phase. During the teaching phase, the mower estimates the 3D positions of landmarks and defines a boundary in the lawn with an estimate of its own trajectory. During the(More)
This paper describes the motivation, design and implementation of a Perception Validation System (PVS), a system for measuring the outdoor perception performance of an autonomous vehicle. The PVS relies on using large amounts of real world data and ground truth information to quantify performance aspects such as the rate of false positive or false negative(More)
In this paper, we present an omnidirectional-vision-based localization and mapping system which can detect whether a robotic mower is contained in a permitted area. We exploit a robot-centric mapping framework that exploits a differential equation of motion of the landmarks, which are referenced with respect to the robot body frame. The estimator in our(More)
  • 1