Funding Source: Max Planck Institute Grassroots Funding
Motivation: 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. In indoor settings, similar applications usually make use of body-mounted sensors, artificial markers and static cameras. While such markers might still be usable in outdoor scenarios, dynamic ambient lighting conditions and the impossibility of having environment-fixed cameras make the overall problem difficult. On the other hand, body-mounted sensors are not feasible in several situations (e.g., large crowds of people). Therefore, our approach to the aforementioned problem involves a team of micro aerial vehicles (MAVs) tracking subjects by using only on-board monocular cameras and computational units, without any subject-fixed sensor or marker.
Goals and Objectives:
AirCap's goal is to achieve markerless, unconstrained, human motion capture (mocap) in unknown and unstructured outdoor environments. To that end, our objectives are
 Deep Neural Network-based Cooperative Visual Tracking through Multiple Micro Aerial Vehicles, Price, E., Lawless, G., Ludwig, R., Martinovic, I., Buelthoff, H. H., Black, M. J., Ahmad, A., IEEE Robotics and Automation Letters, Robotics and Automation Letters, 3(4):3193-3200, IEEE, October 2018, Also accepted and presented in the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
 Markerless Outdoor Human Motion Capture Using Multiple Autonomous Micro Aerial Vehicles, Saini, N., Price, E., Tallamraju, R., Enficiaud, R., Ludwig, R., Martinović, I., Ahmad, A., Black, M., Proceedings 2019 IEEE/CVF International Conference on Computer Vision (ICCV), pages: 823-832, IEEE, October 2019
 Active Perception based Formation Control for Multiple Aerial Vehicles, Tallamraju, R., Price, E., Ludwig, R., Karlapalem, K., Bülthoff, H. H., Black, M. J., Ahmad, A., IEEE Robotics and Automation Letters, Robotics and Automation Letters, 4(4):4491-4498, IEEE, October 2019
 AirCap – Aerial Outdoor Motion Capture, Ahmad, A., Price, E., Tallamraju, R., Saini, N., Lawless, G., Ludwig, R., Martinovic, I., Bülthoff, H. H., Black, M. J.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019), Workshop on Aerial Swarms, November 2019.
 Decentralized MPC based Obstacle Avoidance for Multi-Robot Target Tracking Scenarios, Tallamraju, R., Rajappa, S., Black, M. J., Karlapalem, K., Ahmad, A.
2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), pages: 1-8, IEEE, August 2018
 An Online Scalable Approach to Unified Multirobot Cooperative Localization and Object Tracking, Ahmad, A., Lawless, G., Lima, P., IEEE Transactions on Robotics (T-RO), 33, pages: 1184 - 1199, October 2017