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Design of a direct collocation model predictive control framework for legged locomotion based on whole-body dynamics and explicit contact phases
Roos, R.A. (2020) Design of a direct collocation model predictive control framework for legged locomotion based on whole-body dynamics and explicit contact phases.
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| Abstract: | To increase the walking performance of active exoskeletons, and legged robots in general, model predictive techniques can provide more dynamic and robust control. Model predictive control (MPC) can optimize a trajectory and corresponding inputs for a given model, in a given setting. MPC has been used for legged locomotion before, though previous works tend to use simplified dynamics and therefore do not optimize the robot joint torques. In this work we set out to design an MPC framework for legged locomotion that includes whole-body dynamics, such that trajectories can be generated that are efficient in joint torque. MPC based on implicit contact would be preferable, but showed infeasible with the direct collocation method. Instead an approach with explicit contact, based on predefined stance and swing phases, was used. This is an extension of TOWR [1], with the addition of whole-body dynamics. MuJoCo was used to model the system dynamics and IPOPT as numerical optimizer. The framework proved effective in locomotion generation and versatile to robot models, terrains and gaits. For a wide variety of robot types gait trajectories are optimized. However, the optimized trajectories are ineffective when applied in an MPC simulation. |
| Item Type: | Essay (Master) |
| Faculty: | ET: Engineering Technology |
| Programme: | Electrical Engineering MSc (60353) |
| Link to this item: | https://purl.utwente.nl/essays/85467 |
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