Yazar "Alhassow, Mustafa Mohammed" seçeneğine göre listele

Listeleniyor 1 - 3 / 3
  • [ X ]
    Öğe
    Car-like robot path planning based on voronoi and Q-learning algorithms
    (ICEET, 2021) Alhassow, Mustafa Mohammed; Ata, Oğuz; Atilla, Doğu Çağdaş
    This paper discusses a differential path planning issue for the mobile robot depending on Voronoi diagram (VD) and Q-learning algorithms (QL). The issues with re-arranging paths in a dynamic environment with obstructions are treated as an issue of looking for the best route between the start and target stage. Since the car-like robot is differentially system and its mathematically involved with the inward state of impediment because of that some modification will be embedded like the orientation method. This is a unique instance of a solitary vehicle, which just goes ahead at a consistent speed and can just turn left also, right. Voronoi diagram presents the world encompassing brilliant specialists for robots, computer games, and military issues, so improving the dependability, of arranging the environment using it will help and decrease Q learning calculations by re-updating the Q-table, according to the new state, also decreasing both existence intricacy, relies upon earlier information that came from the environment. The work arrangement was tested for a 2D environment. The result of the proposed work showed better performance in time, speed, and length of the path also it can be utilized as an alternate style of guides. A comparison with other related works is performed and the result of these comparisons showed that our work provides a good trajectory with performance.
  • [ X ]
    Öğe
    Multi-agents path planning for a mobile robot in a dynamic warehouse environment
    (Springer Science and Business Media Deutschland, 2023) Alhassow, Mustafa Mohammed; Ata, Oğuz; Atilla, Doğu Çağdaş
    Route planning in robotic systems is a critical and complex task in any environment. Robotic systems allow multiple robots to accomplish multiple goals simultaneously. Many mobile service robots are now used in warehouses to reduce operating and overhead costs. Large warehouses may have multiple robots to handle a large number of tasks. Route planning means finding the best route, i.e. the route without collisions. Optimizing both parameters can be a daunting task. By properly addressing the problem of route planning between robots, we can improve the efficiency of the operation of the entire warehouse. At the beginning, every robot will navigate to its desired goal by funding the optimal route without collisions with other robots. In this work, a relative study with the notable route plan was presented. The proposed intelligent approach was presented for a multi-robot system that finds the best collision-free path in the warehouse and processes the storage box. This paper proposes a sensible variety metric for multi-robotic structures to intelligently become aware of goals and take the best minimum paths to attain them without encountering collisions. Using an intelligent variety metric to discover the route that we want to reach our goal. The proposed planning path are similar to different works including A *, RNN, PRM and heuristics. Three exclusive times of the warehouse have been taken into consideration to carry out experiments with parameters including route length, common route, and elapsed time. Experiments with 800 pods and sixteen robots have said overall performance enhancements of as much as 2.3%, common route length, and elapsed time of 11%.
  • Küçük Resim
    Öğe
    Obstacle avoidance capability for multi-target path planning in different styles of search
    (Tech Science Press, 2024) Alhassow, Mustafa Mohammed; Ata, Oğuz; Atilla, Doğu Çağdaş
    This study investigates robot path planning for multiple agents, focusing on the critical requirement that agents can pursue concurrent pathways without collisions. Each agent is assigned a task within the environment to reach a designated destination. When the map or goal changes unexpectedly, particularly in dynamic and unknown environments, it can lead to potential failures or performance degradation in various ways. Additionally, priority inheritance plays a significant role in path planning and can impact performance. This study proposes a Conflict- Based Search (CBS) approach, introducing a unique hierarchical searchmechanism for planning paths formultiple robots. The study aims to enhance flexibility in adapting to different environments. Three scenarioswere tested, and the accuracy of the proposed algorithm was validated. In the first scenario, path planning was applied in unknown environments, both stationary and mobile, yielding excellent results in terms of time to arrival and path length,with a time of 2.3 s. In the second scenario, the algorithmwas applied to complex environments containing sharp corners and unknown obstacles, resulting in a time of 2.6 s, with the algorithm also performing well in terms of path length. In the final scenario, themulti-objective algorithmwas tested in awarehouse environment containing fixed,mobile, andmulti-targeted obstacles, achieving a result of up to 100.4 s. Based on the results and comparisons with previous work, the proposed method was found to be highly effective, efficient, and suitable for various environments.