cam a22 4500 528784021 20201202084457.0 cr unu---uuuuu 180924s2018 xx sm 000 0 eng 10.3929/ethz-b-000284254 doi (ETHRESEARCH)oai:www.research-collection.ethz.ch:20.500.11850/284254 Fankhauser Péter Perceptive Locomotion for Legged Robots in Rough Terrain [Elektronische Daten] [Péter Fankhauser, Roland Y. Siegwart (Supervisor), Marco; id_orcid 0000-0002-4285-4990 Hutter (Supervisor), Jerry Pratt (Supervisor)] Zurich ETH Zurich 2018 194 p. Doctoral Thesis Open access ethresearch Robotic technologies will continue to enter new applications in addition to automated manufacturing and logistics. Once mobile robots can also operate outside of today's special facilities, they have the potential to relieve us of dirty and dangerous labor in various areas. However, for this purpose, these machines will need to be able to navigate autonomously in complex natural, urban, and industrial settings. This thesis addresses the development of locomotion skills for legged robots in challenging environments. Our work focuses on perceptive locomotion where exteroceptive sensing of the surrounding is exploited to plan and control the robot's motion. This enables quadrupedal robots to negotiate rough terrain through carefully selected contacts. In this work, we evaluate different sensing technologies and analyze their performance for local dense terrain mapping on a mobile robot. We include special conditions such as close range objects and the influence of ambient light as we find them in real-world applications. By modeling the error characteristics of the sensors, the robot can judge the quality of the resulting terrain reconstruction. As the robot moves, the surrounding is continuously mapped to capture new areas and update regions which have changed. We contribute with a mapping framework that models the terrain from a robot-centric perspective. To this end, we present a novel approach for the error propagation from the robot's state estimation to the representation of the map. This formulation allows for robust and high-rate local mapping that is independent of a global localization method. We introduce our approach to locomotion planning, which finds safe footholds along with collision-free swing-leg motions, leveraging the generated terrain map. A nonlinear optimization finds postures that respect kinematic and stability constraints. We experimentally verify this work with torque-controllable quadrupedal robots that autonomously traverse obstacles, such as rubble, steps, gaps, and stairs without prior knowledge of the scene or any additional equipment. The locomotion planner re-plans its motion at every step in real-time, to cope with disturbances and dynamic environments. For the control of the legged robot, we contribute architecturally to the versatile and task-oriented motion execution. This method enables the robust tracking of motion plans, even with significant mismatches between the models and reality. In addition to rough terrain locomotion, we demonstrate the integration of our method for applications, such as whole-body stair climbing, manipulation, jumping, docking, inspection, payload delivery, dancing, and more. Our approach is thoroughly validated with the quadrupedal robot ANYmal in realistic long-term missions for autonomous industrial inspection and search and rescue. Finally, we extend our work with the design and implementation of a collaborative navigation framework for ground and flying robots. The ground vehicle utilizes the data captured by the flying robot to navigate uncharted environments efficiently. In Copyright - Non-Commercial Use Permitted http://rightsstatements.org/page/InC-NC/1.0 ethresearch Legged locomotion ethresearch Legged robotics ethresearch Rough terrain ethresearch Rough terrain traversal ethresearch Real-world deployment ethresearch Perception ethresearch Sensor modeling ethresearch Sensor evaluation ethresearch Mapping ethresearch Terrain mapping ethresearch Terrain estimation ethresearch Whole-body control ethresearch Whole-body abstraction layer ethresearch Grid map ethresearch Elevation mapping ethresearch Free Gait ethresearch Robot control ethresearch Foothold planning ethresearch Motion planning ethresearch Trajectory planning ethresearch Foothold selection ethresearch Quadrupedal Robots ethresearch ANYmal ethresearch StarlETH ethresearch Collaborative navigation ethresearch Robot team ethresearch Electric engineering ethresearch Siegwart Roland Y. Supervisor dgs Hutter Marco; id_orcid 0000-0002-4285-4990 Supervisor dgs Pratt Jerry Supervisor dgs http://hdl.handle.net/20.500.11850/284254 text/html WWW-Backlink auf das Repository (Open access) BK020353 XK020053 XK020000 1 Doctoral Thesis ethresearch ETHRESEARCH ETHRESEARCH ETHRESEARCH Doctoral Thesis Open access ETHRESEARCH 856 40 http://hdl.handle.net/20.500.11850/284254 text/html WWW-Backlink auf das Repository (Open access) ETHRESEARCH 100 1- Fankhauser Péter ETHRESEARCH 700 1- Siegwart Roland Y. Supervisor dgs ETHRESEARCH 700 1- Hutter Marco; id_orcid 0000-0002-4285-4990 Supervisor dgs ETHRESEARCH 700 1- Pratt Jerry Supervisor dgs