Abstract
With the goal of enabling the exploitation of impacts in robotic manipulation, a new framework is presented for control of robotic manipulators that are tasked to execute nominally simultaneous impacts. In this framework, we employ tracking of time-invariant reference vector fields corresponding to the ante- and post-impact motion, increasing its applicability over similar conventional tracking control approaches. The ante- and post-impact references are coupled through a rigid impact map, and are extended to overlap around the area where the impact is expected to take place, such that the reference corresponding to the actual contact state of the robot can always be followed. As a sequence of impacts at the different contact points will typically occur, resulting in uncertainty of the contact mode and unreliable velocity measurements, a new interim control mode catered towards time-invariant references is formulated. In this mode, a position feedback signal is derived from the ante-impact velocity reference, which is used to enforce sustained contact in all contact points without using velocity feedback. With an eye towards real implementation, the approach is formulated using a QP control framework, and is validated using numerical simulations both on a rigid robot with a hard inelastic contact model and on a realistic robot model with flexible joints and compliant partially elastic contact model.
| Original language | English |
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| Title of host publication | Proceedings of the American Control Conference, ACC 2023 |
| Publisher | Institute of Electrical and Electronics Engineers |
| Pages | 46-53 |
| Number of pages | 8 |
| ISBN (Electronic) | 979-8-3503-2806-6 |
| DOIs | |
| Publication status | Published - 3 Jul 2023 |
| Event | 2023 American Control Conference, ACC 2023 - San Diego, United States Duration: 31 May 2023 → 2 Jun 2023 |
Conference
| Conference | 2023 American Control Conference, ACC 2023 |
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| Abbreviated title | ACC 2023 |
| Country/Territory | United States |
| City | San Diego |
| Period | 31/05/23 → 2/06/23 |
Funding
This work was partially supported by the Research Project I.AM. through the European Union H2020 program under GA 871899.
| Funders | Funder number |
|---|---|
| European Union's Horizon 2020 - Research and Innovation Framework Programme | 871899 |