We describe an entomological dual-band 808 and 980 nm lidar system which has been implemented in a tropical cloud forest (Ecuador). The system was successfully tested at a sample rate of 5 kHz in a cloud forest during challenging foggy conditions (extinction coefficients up to 20 km–1). At times, the backscattered signal could be retrieved from a distance of 2.929 km. We present insect and bat observations up to 200 m during a single night with an emphasis on fog aspects, potentials, and benefits of such dual-band systems. We demonstrate that the modulation contrast between insects and fog is high in the frequency domain compared to intensity in the time domain, thus allowing for better identification and quantification in misty forests. Oscillatory lidar extinction effects are shown in this work for the first time, caused by the combination of dense fog and large moths partially obstructing the beam. We demonstrate here an interesting case of a moth where left- and right-wing movements induced oscillations in both intensity and pixel spread. In addition, we were able to identify the dorsal and ventral sides of the wings by estimating the corresponding melanization with the dual-band lidar. We demonstrate that the wing beat trajectories in the dual-band parameter space are complementary rather than covarying or redundant, thus a dual-band entomological lidar approach to biodiversity studies is feasible in situ and endows species specificity differentiation. Future improvements are discussed. The introduction of these methodologies opens the door to a wealth of possible experiments to monitor, understand, and safeguard the biological resources of one of the most biodiverse countries on Earth.

No abstract

No abstract

Abstract-Nowadays, deploying service robots and adapting their services to a new environment is a task which might require several days. This is an important problem of robotics in general, but specially when the goal is to bring robots to our everyday life. In this paper we present a multi-agent intelligent space, which consists on intelligent cameras and autonomous guide robots. The deployment of the system does not require expertise and can be done in a short period of time. The cameras detect situations requiring the robots' guiding services, inform the robots accordingly, and support the robots navigation towards the goal areas, without the need of a map of the environment. An example of these situations requiring the robot guide service could be a group of persons entering a museum. In this sense, we also present an adaptive person follower behaviour intended to be the basis of a route learning process, necessary to offer the guide service.

No abstract