Rough Terrain Motion Planning for Actively Reconfigurable Mobile Robots

  • Bewegungsplanung für Roboter mit variabler Fahrwerksgeometrie in unwegsamem Gelände

Brunner, Michael; Schlick, Christopher (Thesis advisor); Flemisch, Frank Ole (Thesis advisor)

Aachen : Publikationsserver der RWTH Aachen University (2015)
Dissertation / PhD Thesis

Aachen, Techn. Hochsch., Diss., 2015


In the aftermath of the Tohoku earthquake and the nuclear meltdown at the power plant of Fukushima Daiichi in 2011, reconfigurable robots like the iRobot Packbot were deployed. Instead of humans, the robots were used to investigate contaminated areas. Other incidents are the two major earthquakes in Northern Italy in May 2012. Besides many casualties, a large number of historical buildings was severely damaged. Due to the imminent danger of collapse, it was too dangerous for rescue personnel to enter many of the buildings. Therefore, the sites were inspected by reconfigurable robots, which are able to traverse the rubble and debris of the partially destroyed buildings. This thesis develops a navigation system enabling wheeled and tracked robots to safely traverse rough terrain and challenging structures. It consists of a planning mechanism and a controller. The focus of this thesis, however, is on the contribution to motion planning. The planning scheme employs a hierarchical approach to motion planning for actively reconfigurable robots in rough environments. Using a map of the environment the algorithm estimates the traversability under the consideration of uncertainties. Based on this analysis, an initial path search determines an approximate solution with respect to the robot’s operating limits.Subsequently, a detailed planning step refines the initial path where it is required. The refinement step considers the robot’s actuators and stability in addition to the quantities of the first search. Determining the robot-terrain interaction is very important in rough terrain. This thesis presents two path refinement approaches: a deterministic and a randomized approach. The experimental evaluation investigates the separate components of the planning scheme, the robot-terrain interaction for instance.In simulation as well as in real world experiments the evaluation demonstrates the necessity of such a planning algorithm in rough terrain and it provides strong evidence for the generality and the usability of the algorithm with real robots.