| 1. |
- Hajieghrary, Hadi, 1983, et al.
(författare)
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Bayesian Optimization-based Nonlinear Adaptive PID Controller Design for Robust Mobile Manipulation
- 2022
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Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; 2022-August, s. 1009-1016
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Konferensbidrag (refereegranskat)abstract
- In this paper, we propose to use a nonlinear adaptive PID controller to regulate the joint variables of a mobile manipulator. The motion of the mobile base forces undue disturbances on the joint controllers of the manipulator. In designing a conventional PID controller, one should make a trade-off between the performance and agility of the closed-loop system and its stability margins. The proposed nonlinear adaptive PID controller provides a mechanism to relax the need for such a compromise by adapting the gains according to the magnitude of the error without expert tuning. Therefore, we can achieve agile performance for the system while seeing damped overshoot in the output and track the reference as close as possible, even in the presence of external disturbances and uncertainties in the modeling of the system. We have employed a Bayesian optimization approach to choose the parameters of a nonlinear adaptive PID controller to achieve the best performance in tracking the reference input and rejecting disturbances. The results demonstrate that a well-designed nonlinear adaptive PID controller can effectively regulate a mobile manipulator's joint variables while carrying an unspecified heavy load and an abrupt base movement occurs.
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| 2. |
- Hajieghrary, Hadi, 1983, et al.
(författare)
-
Bayesian Optimization based Nonlinear Adaptive PID Design for Robust Control of the Joints at Mobile Manipulators
- 2022
-
Ingår i: IEEE International Conference on Automation Science and Engineering. - 2161-8070 .- 2161-8089. ; , s. 1009-1016
-
Konferensbidrag (refereegranskat)abstract
- In this paper, we propose to use a nonlinear adaptive PID controller to regulate the joint variables of a mobile manipulator. The motion of the mobile base forces undue disturbances on the joint controllers of the manipulator. In designing a conventional PID controller, one should make a trade-off between the performance and agility of the closed-loop system and its stability margins. The proposed nonlinear adaptive PID controller provides a mechanism to relax the need for such a compromise by adapting the gains according to the magnitude of the error without expert tuning. Therefore, we can achieve agile performance for the system while seeing damped overshoot in the output and track the reference as close as possible, even in the presence of external disturbances and uncertainties in the modeling of the system. We have employed a Bayesian optimization approach to choose the parameters of a nonlinear adaptive PID controller to achieve the best performance in tracking the reference input and rejecting disturbances. The results demonstrate that a well-designed nonlinear adaptive PID controller can effectively regulate a mobile manipulator’s joint variables while carrying an unspecified heavy load and an abrupt base movement occurs.
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| 3. |
- Tafnakaji, Sevag, et al.
(författare)
-
Benchmarking Local Motion Planners for Navigation of Mobile Manipulators
- 2023
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Ingår i: 2023 IEEE/SICE International Symposium on System Integration, SII 2023.
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Konferensbidrag (refereegranskat)abstract
- There are various trajectory planners for mobile manipulators. It is often challenging to compare their performance under similar circumstances due to differences in hardware, dissimilarity of tasks and objectives, as well as uncertainties in measurements and operating environments. In this paper, we propose a simulation framework to evaluate the performance of the local trajectory planners to generate smooth, and dynamically and kinematically feasible trajectories for mobile manipulators in the same environment. We focus on local planners as they are key components that provide smooth trajectories while carrying a load, react to dynamic obstacles, and avoid collisions. We evaluate two prominent local trajectory planners, Dynamic-Window Approach (DWA) and Time Elastic Band (TEB) using the metrics that we introduce. Moreover, our software solution is applicable to any other local planners used in the Robot Operating System (ROS) framework, without additional programming effort.
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| 4. |
- Zhang, Ze, 1995, et al.
(författare)
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Prescient Collision-Free Navigation of Mobile Robots with Iterative Multimodal Motion Prediction of Dynamic Obstacles
- 2023
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Ingår i: IEEE Robotics and Automation Letters. - 2377-3766. ; 8:9, s. 5488-5495
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Tidskriftsartikel (refereegranskat)abstract
- To explore safe interactions between a mobile robot and dynamic obstacles, this paper presents a comprehensive approach to collision-free navigation in dynamic indoor environments. The approach integrates multimodal motion predictions of dynamic obstacles with predictive control for obstacle avoidance. Multimodal Motion Prediction (MMP) is achieved by a deep-learning method that predicts multiple plausible future positions. By repeating the MMP for each time offset in the future, multi-time-step MMPs are obtained. A nonlinear Model Predictive Control (MPC) solver uses the prediction outcomes to achieve collision-free trajectory tracking for the mobile robot. The proposed integration of multimodal motion prediction and trajectory tracking outperforms other non-deep-learning methods in complex scenarios. The approach enables safe interaction between the mobile robot and stochastic dynamic obstacles.
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