Vision-based impedance control

Research Overview

The integration of computer vision techniques for the accomplishment of autonomous interaction tasks represents a challenging research direction in the context of aerial robotics. In this paper, we consider the problem of contactbased inspection of a textured target of unknown geometry and pose. Exploiting state of the art techniques in computer graphics, tuned and improved for the task at hand, we designed a framework for the projection of a desired trajectory for the robot end-effector on a generically-shaped surface to be inspected.

Combining these results with previous work on energybased interaction control, we are laying the basis of what we call vision-based impedance control paradigm. To demonstrate the feasibility and the effectiveness of our methodology, we present the results of both realistic ROS/Gazebo simulations and preliminary experiments with a fully-actuated hexarotor
interacting with heterogeneous curved surfaces whose geometric description is not available a priori, provided that enough visual features on the target are naturally or artificially available to allow the integration of localization and mapping algorithms.

Publications

Ramy Rashad, Davide Bicego, Ran Jiao, Santiago Sanchez-Escalonilla, Stefano Stramigioli (2020) Towards vision-based impedance control for the contact inspection of unknown generically-shaped surfaces with a fully-actuated UAV, IEEE International Conference on Intelligent Robots and Systems(143081), p. 1605-1612, doi:10.1109/IROS45743.2020.9341203
B. Sirmacek, R. Rashad, P. Radl (2019) Autonomous uav-based 3d-reconstruction of structures for aerial physical interaction, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences – ISPRS Archives 42(2/W13), p. 601-605, doi:10.5194/isprs-archives-XLII-2-W13-601-2019

Patrick Radl, 3D reconstruction improvement by path planning towards physical interaction with a UAV, University of Twente (Jun 2019), Supervisors: R. Rashad, B. Sirma├žek, F. van der Heijden

Rajavarman Mathivanan, Texture Based Autonomous Reconstruction of 3D Point Cloud Model using Fully Actuated UAVs, University of Twente (Jul 2020), Supervisors: R. Rashad, D. Bicego, G. Krijnen
Gazebo simulation environment
Manual reconstruction of 3D point cloud
Autonomous reconstruction of 3D point cloud using