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.
We develop a new generation of flying robotic systems capable of resilient navigational autonomy in such conditions. In this process we have been fielding "Gagarin" and the "Resilient Micro Flyer". Gagarin is a robot built in the framework of our DARPA Subterranean Challenge activities as Team CERBERUS. It is capable of comprehensive 3D mapping during autonomous exploration, object detection and localization, while it has been field verified in mines, tunnels, caves, and underground facilities. The Resilient Micro Flyer is a new attempt for a sub-500g autonomous aerial robotic explorer. 

Indicative Results of Ongoing & Previous Research

Resilient Collision-tolerant Navigation in Confined Environments

This work presents the design and autonomous navigation policy of the Resilient Micro Flyer, a new type of collision-tolerant robot tailored to flying through extremely confined environments and manhole-sized tubes. The robot maintains a low weight (sub-500g) and implements a combined rigid-compliant design through the integration of elastic flaps around its stiff collision-tolerant frame. 

Resilient Collision-tolerant Navigation in Confined Environments

This work presents the design, development and autonomous navigation of the alpha-version of our Resilient Micro Flyer, a new type of collision-tolerant small aerial robot tailored to traversing and searching within highly confined environments including manhole-sized tubes. The robot is particularly lightweight and agile, while it implements a rigid collision-tolerant design which renders it resilient during forcible interaction with the environment. 

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.

ASLquad Aerial Writer Demonstration

This video demonstrates the Aerial Physical Interaction Capabilities of the ASLquad as controller by a Hybrid Model Predictive Control Approach

Research Thrusts

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. 
In our design approach the robot is considered to be fully autonomous with no human intervention during the execution of its mission. This is not to assume that the human should never be present or in control. This is ensure that the robot can navigate safely and execute its mission even when human control is not possible or is not considered a viable approach.