Overview of our Research Projects

WildCap

Autonomous Animal Motion Capture for Wildlife Conservation -- Understanding animal behavior, i.e., how they move and interact among each other and with their environment, is a fundamental requirement for addressing the most important ecological problems today. Read more here.

AeRoShip

 Autonomous Robotic Airships -- Lighter-than-air vehicles (LTAVs) such as rigid and nonrigid dirigibles, or airships, are clearly a superior choice for some applications like wildlife monitoring, sports event capture and continuous patrolling of forest regions for anti-poaching tasks. Read more here.

AirCap

Autonomous Aerial Motion Capture of Humans -- Human pose tracking and full body pose estimation and reconstruction in outdoor, unstructured environments is a highly relevant and challenging problem. Its wide range of applications includes search and rescue, managing large public gatherings, and coordinating outdoor sports events. Read more here.

AirCapRL

 Deep RL-based Aerial Motion Capture -- Realizing an aerial motion capture (MoCap) system for humans or animals involves several challenges. The system's robotic front-end must ensure that the subject is i) accurately and continuously followed by all aerial robots (UAVs), and ii) within the field of view (FOV) of the cameras of all robot. Read more here.

ActiveSLAM

Mobile robots that assist humans in everyday tasks are increasingly popular, both in workplaces and homes. Self-localization and environment mapping are the key building-block state-estimation functionalities of such robots, which enable robustness in higher level task performance, such as navigation, manipulation and interaction with humans. Most often, these robots operate in a previously-unknown environment, e.g., in a person’s house. To develop the aforementioned state-estimation functionalities, a popular approach is V-SLAM – visual simultaneous localization and mapping using on-board RGB cameras. Read more here.