Collision-tolerant Aerial Robotics
A special branch of our research relates to collision-tolerant aerial robotics and exploiting this unique capability in enabling for agile, faster and resilient navigation in the most challenging environments and conditions. Among others the process of designing the systems and autonomy for collision-tolerant flying robots aims to render the navigation of extreme environments seamless. Settings of particular interest include but are not limited to:
- Subterranean environments, such as underground mines, caves and urban infrastructure (e.g., subway) presenting cases of visual degradation including darkness, smoke, dust and more.
- Industrial facilities, such as those of the oil and gas and power generation industries, both during normal operations and in case of an accident.
- Urban structures in search and rescue scenarios, such as an earthquake, where the navigation task is of very high risk.
Indicative Results of Ongoing & Previous Research
DARPA SubT Urban Circuit: Collision-tolerant Exploration of Staircases using Aerial Robots
In this video we present the autonomous exploration of a staircase with four sub-levels and the transition between two floors of the Satsop Nuclear Power Plant during the DARPA Subterranean Challenge Urban Circuit. The utilized system is a collision-tolerant flying robot capable of multi-modal Localization And Mapping fusing LiDAR, vision and inertial sensing. Autonomous exploration and navigation through the staircase is enabled through a Graph-based Exploration Planner.
Motion Primitives-based Path Planning for Fast and Agile Exploration using Aerial Robots
This work presents a novel path planning strategy for fast and agile exploration using aerial robots. Tailored to the combined need for large-scale exploration of challenging and confined environments, despite the limited endurance of micro aerial vehicles, the proposed planner employs motion primitives to identify admissible paths that search the configuration space, while exploiting the dynamic flight properties of small aerial robots.
Contact-based Navigation Path Planning for Aerial Robots
In this work, we present a path planning method for exploiting contact by aerial robots to enable the traversal of highly anomalous surfaces. Apart from sliding in contact, the proposed strategy introduces a new locomotion modality of azimuth rotations perpendicular to the surface, dubbed the flying cartwheel mode. The developed planner is based on the mechanics of optimal sampling-based methods and exploits a surface traversability metric to decide when to switch from sliding to flying cartwheel mode and vice versa.
To implement the vision of resiliently autonomous collision-tolerant aerial robotics we conduct research across the following domains:
- Collision-tolerant Flying Robot Design to maximize the inherent resilience of the physical embodiment. We seek lightweight designs that are either very rigid or exploit compliance.
- Embedded Real-time Multi-modal Robotic Perception for resilient localization and mapping even in the most degraded conditions. We seek approaches that are robust for each of their modalities (e.g., camera, thermal vision, LiDAR) and fuse them in a comprehensive multi-modal approach.
- Robust and High Performance Control for agile flight and ability to withstand forcible disturbances during intended and unintended physical interaction.
- Reinforcement Learning-based Map-free Autonomous Navigation and exploration of very large-scale environments at high speeds.