Abstract: A near-optimal solution to the path-unconstrained time-optimal trajectory planning prob... more Abstract: A near-optimal solution to the path-unconstrained time-optimal trajectory planning prob-lem is described in this paper. While traditional trajectory planning strategies are entirely based on kinematic considerations, manipulator dynamics are usually neglected altogether. The strategy pre-sented in this work has two distinguishing features. Firstly, the trajectory planning problem is reformu-lated as an optimal control problem, which is in turn solved using Pontryagin’s maximum/minimum principle. This approach merges the traditional division of trajectory planning followed by trajectory tracking into one process. Secondly, the feedback form compensates for the dynamic approximation errors derived from linearization and the fundamental parameter uncertainty of the dynamic equations of motion. This approach can cope with exible robots as well as rigid links. The terminal phase of the motion is controlled by a feedforward controller to reduce chatter vibrations. Results from s...
We propose a sampling-based motion-planning algorithm equipped with an information-theoretic conv... more We propose a sampling-based motion-planning algorithm equipped with an information-theoretic convergence criterion for incremental informative motion planning. The proposed approach allows dense map representations and incorporates the full state uncertainty into the planning process. The problem is formulated as a constrained maximization problem. Our approach is built on rapidly exploring information-gathering algorithms and benefits from the advantages of sampling-based optimal motion-planning algorithms. We propose two information functions and their variants for fast and online computations. We prove an information-theoretic convergence for an entire exploration and information-gathering mission based on the least upper bound of the average map entropy. A natural automatic stopping criterion for information-driven motion control results from the convergence analysis. We demonstrate the performance of the proposed algorithms using three scenarios: comparison of the proposed info...
This work presents a hybrid position-force control of robots for surface polishing using task pri... more This work presents a hybrid position-force control of robots for surface polishing using task priority. The robot force control is designed using sliding mode ideas in order to benefit from its inherent robustness and low computational cost. In order to avoid the chattering drawback typically present in sliding mode control, several chattering-free controllers are evaluated and tested. A distinctive feature of the method is that the sliding mode force task is defined using not only equality constraints but also inequality constraints, which are satisfied using conventional and nonconventional sliding mode control, respectively. Moreover, a lower priority tracking controller is defined to follow the desired reference trajectory on the surface being polished. The applicability and the effectiveness of the proposed approach considering the mentioned chattering-free controllers are substantiated by experimental results using a redundant 7R manipulator.
Abstract: A near-optimal solution to the path-unconstrained time-optimal trajectory planning prob... more Abstract: A near-optimal solution to the path-unconstrained time-optimal trajectory planning prob-lem is described in this paper. While traditional trajectory planning strategies are entirely based on kinematic considerations, manipulator dynamics are usually neglected altogether. The strategy pre-sented in this work has two distinguishing features. Firstly, the trajectory planning problem is reformu-lated as an optimal control problem, which is in turn solved using Pontryagin’s maximum/minimum principle. This approach merges the traditional division of trajectory planning followed by trajectory tracking into one process. Secondly, the feedback form compensates for the dynamic approximation errors derived from linearization and the fundamental parameter uncertainty of the dynamic equations of motion. This approach can cope with exible robots as well as rigid links. The terminal phase of the motion is controlled by a feedforward controller to reduce chatter vibrations. Results from s...
We propose a sampling-based motion-planning algorithm equipped with an information-theoretic conv... more We propose a sampling-based motion-planning algorithm equipped with an information-theoretic convergence criterion for incremental informative motion planning. The proposed approach allows dense map representations and incorporates the full state uncertainty into the planning process. The problem is formulated as a constrained maximization problem. Our approach is built on rapidly exploring information-gathering algorithms and benefits from the advantages of sampling-based optimal motion-planning algorithms. We propose two information functions and their variants for fast and online computations. We prove an information-theoretic convergence for an entire exploration and information-gathering mission based on the least upper bound of the average map entropy. A natural automatic stopping criterion for information-driven motion control results from the convergence analysis. We demonstrate the performance of the proposed algorithms using three scenarios: comparison of the proposed info...
This work presents a hybrid position-force control of robots for surface polishing using task pri... more This work presents a hybrid position-force control of robots for surface polishing using task priority. The robot force control is designed using sliding mode ideas in order to benefit from its inherent robustness and low computational cost. In order to avoid the chattering drawback typically present in sliding mode control, several chattering-free controllers are evaluated and tested. A distinctive feature of the method is that the sliding mode force task is defined using not only equality constraints but also inequality constraints, which are satisfied using conventional and nonconventional sliding mode control, respectively. Moreover, a lower priority tracking controller is defined to follow the desired reference trajectory on the surface being polished. The applicability and the effectiveness of the proposed approach considering the mentioned chattering-free controllers are substantiated by experimental results using a redundant 7R manipulator.
IEEE Conference on Industrial Electronics and Applications, 2018
The paper presents a review of the spatial prediction problem in the environmental monitoring app... more The paper presents a review of the spatial prediction problem in the environmental monitoring applications by utilizing stationary and mobile robotic wireless sensor networks. First, the problem of selecting the best subset of stationary wireless sensors monitoring environmental phenomena in terms of sensing quality is surveyed. Then, predictive inference approaches and sampling algorithms for mobile sensing agents to optimally observe spatially physical processes in the existing works are analysed.
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Papers by Jaime Valls Miro