Andreas Bircher
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Andreas Bircher has a total of 10 co-authors. Here are the top co-authors by number of shared publications:
- Roland Siegwart
Autonomous Systems Lab (ASL), ETH Zürich, Zürich, Switzerland
3 shared publications - Kostas Alexis
University of Nevada, Reno
2 shared publications - Michael Burri
Autonomous Systems Lab at ETH Zurich, Leonhardstrasse 21, 8092 Zurich, Switzerland s
2 shared publications - Mina Kamel
D-MAVT, Autonomous Systems Lab, ETH Zurich, Zurich Switzerland 8092
2 shared publications - Sammy Omari
Autonomous Systems Lab at ETH Zurich, Leonhardstrasse 21, 8092 Zurich, Switzerland s
2 shared publications - Helen Oleynikova
Autonomous Systems Lab (ASL), ETH Zürich, Zürich, Switzerland
1 shared publication
Latest Publications
- Top Cited Papers
- 11 November 2016
- Published by Springer Nature in Autonomous Robots
- Vol. 42 (2) , 291-306
Receding horizon path planning for 3D exploration and surface inspection
- 11 November 2016
- Published by Springer Nature in Autonomous Robots
- Vol. 42 (2) , 291-306
Top Cited PapersReceding horizon path planning for 3D exploration and surface inspection
- 11 March 2016
- Published by Cambridge University Press (CUP) in Robotica
- Vol. 35 (6) , 1327-1340
An incremental sampling-based approach to inspection planning: the rapidly exploring random tree of trees
SUMMARY: A new algorithm, called rapidly exploring random tree of trees (RRTOT) is proposed, that aims to address the challenge of planning for autonomous structural inspection. Given a representation of a structure, a visibility model of an onboard sensor, an initial robot configuration and constraints, RRTOT computes inspection paths that provide full coverage. Sampling based techniques and a meta-tree structure consisting of multiple RRT* trees are employed to find admissible paths with decreasing cost. Using this approach, RRTOT does not suffer from the limitations of strategies that separate the inspection path planning problem into that of finding the minimum set of observation points and only afterwards compute the best possible path among them. Analysis is provided on the capability of RRTOT to find admissible solutions that, in the limit case, approach the optimal one. The algorithm is evaluated in both simulation and experimental studies. An unmanned rotorcraft equipped with a vision sensor was utilized as the experimental platform and validation of the achieved inspection properties was performed using3Dreconstruction techniques.
- 11 March 2016
- Published by Cambridge University Press (CUP) in Robotica
- Vol. 35 (6) , 1327-1340
An incremental sampling-based approach to inspection planning: the rapidly exploring random tree of trees
SUMMARY: A new algorithm, called rapidly exploring random tree of trees (RRTOT) is proposed, that aims to address the challenge of planning for autonomous structural inspection. Given a representation of a structure, a visibility model of an onboard sensor, an initial robot configuration and constraints, RRTOT computes inspection paths that provide full coverage. Sampling based techniques and a meta-tree structure consisting of multiple RRT* trees are employed to find admissible paths with decreasing cost. Using this approach, RRTOT does not suffer from the limitations of strategies that separate the inspection path planning problem into that of finding the minimum set of observation points and only afterwards compute the best possible path among them. Analysis is provided on the capability of RRTOT to find admissible solutions that, in the limit case, approach the optimal one. The algorithm is evaluated in both simulation and experimental studies. An unmanned rotorcraft equipped with a vision sensor was utilized as the experimental platform and validation of the achieved inspection properties was performed using3Dreconstruction techniques.
- 2 November 2015
- Published by Springer Nature in Autonomous Robots
- Vol. 40 (6) , 1059-1078
Three-dimensional coverage path planning via viewpoint resampling and tour optimization for aerial robots
- 2 November 2015
- Published by Springer Nature in Autonomous Robots
- Vol. 40 (6) , 1059-1078
Three-dimensional coverage path planning via viewpoint resampling and tour optimization for aerial robots