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Online Traversability Analysis of unknown Obstacles for mobile autonomous Robots

Brandl, Sascha (2017):
Online Traversability Analysis of unknown Obstacles for mobile autonomous Robots.
Darmstadt, Technische Universitaet Darmstadt, Department of Computer Science (SIM), [Master Thesis]

Abstract

Crossing challenging terrain or unknown obstacles blocking the pathway is a crucial ability for autonomous mobile robots. In some situations such as narrow corridors, crossing the obstacle is indeed the only option. The robot must be able to use its sensory system to analyze the obstacle and find a safe way for crossing. In this thesis, an approach is proposed tackling such tasks for track-based robots equipped with a multi- DoF sensor arm for exploration, and flippers to adapt the geometry of the tracks towards the ground. In order to use the sensor arm to explore the obstacle, the Fixed Sampling Positions exploration (FSP) was developed in this thesis. By using fixed sampling positions and a Next Best View approach, the FSP suggests suitable sensor poses to obtain a point cloud of the obstacle and adapts to already obtained sensor data by utilizing a 3D occupancy map. In the next step, the point cloud is used to measure the stability of the robot on the obstacle. Furthermore, a stability map is computed by utilizing the Force Angle Stability metric as a stability measurement. The map can then be used to find the most stable path for a crossing attempt consisting of estimated robot positions while crossing the obstacle. For a proof of concept, a state machine was developed which utilized the estimated robot positions to plan for appropriate flipper and arm movement during the crossing. The proposed approach was evaluated on a robot system in simulation and on the real robot.

Item Type: Master Thesis
Erschienen: 2017
Creators: Brandl, Sascha
Title: Online Traversability Analysis of unknown Obstacles for mobile autonomous Robots
Language: English
Abstract:

Crossing challenging terrain or unknown obstacles blocking the pathway is a crucial ability for autonomous mobile robots. In some situations such as narrow corridors, crossing the obstacle is indeed the only option. The robot must be able to use its sensory system to analyze the obstacle and find a safe way for crossing. In this thesis, an approach is proposed tackling such tasks for track-based robots equipped with a multi- DoF sensor arm for exploration, and flippers to adapt the geometry of the tracks towards the ground. In order to use the sensor arm to explore the obstacle, the Fixed Sampling Positions exploration (FSP) was developed in this thesis. By using fixed sampling positions and a Next Best View approach, the FSP suggests suitable sensor poses to obtain a point cloud of the obstacle and adapts to already obtained sensor data by utilizing a 3D occupancy map. In the next step, the point cloud is used to measure the stability of the robot on the obstacle. Furthermore, a stability map is computed by utilizing the Force Angle Stability metric as a stability measurement. The map can then be used to find the most stable path for a crossing attempt consisting of estimated robot positions while crossing the obstacle. For a proof of concept, a state machine was developed which utilized the estimated robot positions to plan for appropriate flipper and arm movement during the crossing. The proposed approach was evaluated on a robot system in simulation and on the real robot.

Place of Publication: Darmstadt
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Simulation, Systems Optimization and Robotics Group
Date Deposited: 06 Jun 2019 06:08
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