Christian Ott - Academia.edu (original) (raw)
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Papers by Christian Ott
2014 IEEE-RAS International Conference on Humanoid Robots, 2014
IEEE Robotics & Automation Magazine, 2016
Industrial Robot: An …, 2007
Proceedings of the 19th International Conference on CLAWAR 2016, 2016
We address the problem of generating and stabilising a periodic walking pattern for a biped robot... more We address the problem of generating and stabilising a periodic walking pattern for a biped robot. A novel control framework based on adaptive oscillators combined with dynamic movement primitives was proposed. The proposed control system is a multi step process, where in the first step the system learns the dynamic walking trajectory which is demonstrated by imitating a spring loaded inverted pendulum (SLIP) controller. The learning process is completely autonomous and it is done in real time. In the second step the periodic dynamic pattern is executed using a low gain feedback controller combined with feed forward torque/force control signals. This allows compliant behaviour, smooth interaction with unstructured environment and generates stable ”open-loop” walking pattern. Compared with the SLIP walking control the proposed approach is more robust since it can produce stable walking pattern on a wider interval of forward walking velocity. The proposed control also allows smooth mo...
2014 IEEE-RAS International Conference on Humanoid Robots, 2014
IEEE Robotics & Automation Magazine, 2016
Industrial Robot: An …, 2007
Proceedings of the 19th International Conference on CLAWAR 2016, 2016
We address the problem of generating and stabilising a periodic walking pattern for a biped robot... more We address the problem of generating and stabilising a periodic walking pattern for a biped robot. A novel control framework based on adaptive oscillators combined with dynamic movement primitives was proposed. The proposed control system is a multi step process, where in the first step the system learns the dynamic walking trajectory which is demonstrated by imitating a spring loaded inverted pendulum (SLIP) controller. The learning process is completely autonomous and it is done in real time. In the second step the periodic dynamic pattern is executed using a low gain feedback controller combined with feed forward torque/force control signals. This allows compliant behaviour, smooth interaction with unstructured environment and generates stable ”open-loop” walking pattern. Compared with the SLIP walking control the proposed approach is more robust since it can produce stable walking pattern on a wider interval of forward walking velocity. The proposed control also allows smooth mo...