Combined dynamics and kinematics networked fuzzy task priority motion planning for underwater vehicle-manipulator systems

The underwater vehicle-manipulator systems (UVMS) face significant challenges in trajectory tracking and motion planning because of external disturbance (current and payload) and kinematic redundancy. Former algorithms can finish the tracking of end-effector (EE) and free of singularity redundancy solution alone. However, only a few analytical studies have been conducted on coordinated motion planning of UVMS considering the dynamics controller. This article introduces a combined dynamics and kinematics networked fuzzy task priority motion planning method to solve the above problems. It avoids the assumption of perfect dynamic control. Firstly, to eliminate the kinematics error, a dynamic transformation method from joint space to task space is proposed. Without chattering, an outer loop sliding mode controller is designed for tracking EE’s trajectory. Further, to ensure the underwater vehicle’ posture stability and joint constraint, a task priority frame with kinematics error is used to planning the coordinated motion of UVMS, in which the posture and joint limits map into the null space of prioritized tasks, and weight gains are adopted to guarantee orthogonality of secondary tasks. On top of that, the gain weighted are updated by the networked fuzzy logic. The proposed algorithm achieves better coordinated motion planning and tracking performance. Effectiveness is validated by numerical simulation.

A modified genetic algorithm for task assignment of heterogeneous unmanned aerial vehicle system

This study deals with the task assignment problem of heterogeneous unmanned aerial vehicle (UAV) system with the limited resources and task priority constraints. The optimization model which comprehensively considers the resource consumption, task completion effect, and workload balance is formulated. Then, a concept of fuzzy elite degree is proposed to optimize and balance the transmission of good genes and the variation strength of population during the operations of algorithm. Based on the concept, we propose the fuzzy elite strategy genetic algorithm (FESGA) to efficiently solve the complex task assignment problem. In the proposed algorithm, two unlock methods are presented to solve the deadlock problem in the random optimization process; a sudden threat countermeasure (STC) mechanism is presented to help the algorithm quickly respond to the change of task environment caused by sudden threats. The simulation results demonstrate the superiority of the proposed algorithm. Meanwhile, the effectiveness and feasibility of the algorithm in workload balance and task priority constraints are verified.

Time Management untuk Hidup Lebih Efisien dan Efektif

Pengabdian Kepada Masyarakat ini bertujuan untuk menyiapkan para anggota Yayasan Raudlatul Makfufin di Buaran Serpong bisa secara mandiri melakukan pekerjaan secara efektif dan efisien atas segala kekurangan mereka. Berdasarkan hasil observasi, para anggota Yayasan masih sulit mengatur waktu mereka antara pekerjaan dan urusan pribadi dengan keluarga. Para anggota sendiri adalah para wirausaha yang sangat membutuhkan masukan dalam membagi waktu mereka yang terbatas agar lebih produktif. Target dari pengabdian ini adalah seluruh warga Taman Tunanetra Yayasan Raudlatul Makfufin di Buaran Serpong. Hasil dari Pengabdian Kepada Masyarakat ini terbukti bahwa warga taman tuna netra Yayasan Raudlatul Makfufin di Buaran Serpong mampu mengelola waktu dalam mengerjakan aktivitas yang terencana. Hal ini dapat terlihat bagai­mana para peserta dapat membuat jadwal masing masing dengan menggunakan 6 langkah yaitu Brainstorming, Breakdown Task, Priority Scale, membuat agenda yang Smart, membuat to do List dan Stop Doing List.

Task Priority-Based Cached-Data Prefetching and Eviction Mechanisms for Performance Optimization of Edge Computing Clusters

The rapid evolution of the Internet of Things (IoT) and the development of cloud computing have endorsed a new computing paradigm called edge computing, which brings the computing resources to the edge of the network. Due to low computing power and small data storage at the edge nodes, the task must be assigned to the computing nodes, where their associated data is available, to reduce overheads caused by data transmissions in the network. The proposed scheme named task priority-based data-prefetching scheduler (TPDS) tries to improve the data locality through available cached and prefetching data for offloading tasks to the edge computing nodes. The proposed TPDS prioritizes the tasks in the queue based on the available cached data in the edge computing nodes. Consequently, it increases the utilization of cached data and reduces the overhead caused by data eviction. The simulation results show that the proposed TPDS can be effective in terms of task scheduling and data locality.

A Unifying Task Priority Approach for Autonomous Underwater Vehicles Integrating Homing and Docking Maneuvers

This research proposes a unified guidance and control framework for Autonomous Underwater Vehicles (AUVs) based on the task priority control approach, incorporating various behaviors such as path following, terrain following, obstacle avoidance, as well as homing and docking to stationary and moving stations. The integration of homing and docking maneuvers into the task priority framework is thus a novel contribution of this paper. This integration allows, for example, to execute homing maneuvers close to uneven seafloor or obstacles, ensuring the safety of the AUV, as safety tasks can be given the highest priority. Furthermore, another contribution shown in the paper is that the proposed approach tackles a wide range of scenarios without ad hoc solutions. Indeed, the proposed approach is well suited for both the emerging trend of resident AUVs, which stay underwater for a long period inside garage stations, exiting to perform inspection and maintenance missions and homing back to them, and for AUVs that are required to dock to moving stations such as surface vehicles, or towed docking stations. The proposed techniques are studied in a simulation setting, taking into account the rich number of aforementioned scenarios.