This paper presents a novel hybrid dynamic path planning algorithm termed GIBi-rrt-IDWA, which enhances global path planning by amalgamating the Bi-rrtalgorithm with the local path planning capabilities of the refine...
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This paper presents a novel hybrid dynamic path planning algorithm termed GIBi-rrt-IDWA, which enhances global path planning by amalgamating the Bi-rrtalgorithm with the local path planning capabilities of the refined DWA algorithm. Through enhancements in node expansion techniques, Improvements in Tree Expansion to eliminate redundancy, and improvements in Sample Point Generation to augment the Bi-rrtalgorithm, the algorithm achieves heightened search efficiency and path security, ultimately leading to the derivation of globally optimal trajectories. The motion model for USV is refined to encompass environmental factors such as winds and currents, pertinent to marine contexts. Furthermore, the evaluation function of the DWA algorithm undergoes enhancements, incorporating elements from heuristic functions within the A* algorithm and radar-based assessment of search range. These improvements facilitate expedited Goal point tracking and fortify the USV's capability to navigate around hazards. Experimental findings corroborate the efficacy of the GIBi-rrt-IDWA algorithm, showcasing its superiority over conventional DWA algorithm and IDWA algorithm. Notably, the algorithm demonstrates prowess in generating shorter and safer trajectories, adeptly navigating through intricate and dynamic waterside environments. Consequently, it improves path planning strategies' adaptability and resilience, allowing USVs to navigate more safely and efficiently.
On-orbit servicing and active debris removal missions will rely on the use of unmanned satellite equipped with a manipulator. Capture of the target object will be the most challenging phase of these missions. During t...
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On-orbit servicing and active debris removal missions will rely on the use of unmanned satellite equipped with a manipulator. Capture of the target object will be the most challenging phase of these missions. During the capture manoeuvre, the manipulator must avoid collisions with elements of the target object (e.g., solar panels). The dynamic equations of the satellite-manipulator system must be used during the trajectory planning because the motion of the manipulator influences the position and orientation of the satellite. In this paper, we propose application of the bidirectional rapidly exploring random trees (Birrt) algorithm for planning a collision-free trajectory of a manipulator mounted on a free-floating satellite. A new approach based on pseudo-velocities method (PVM) is used for construction of nodes of the trajectory tree. Initial nodes of the second tree are selected from the set of potential final configurations of the system. The proposed method is validated in numerical simulations performed for a planar case (3-DoF manipulator). The obtained results are compared with the results obtained with two other trajectory planning methods based on the rrtalgorithm. It is shown that in a simple test scenario, the proposed Birrt PVM algorithm results in a lower manipulator tip position error. In a more difficult test scenario, only the proposed method was able to find a solution. Practical applicability of the Birrt PVM method is demonstrated in experiments performed on a planar air-bearing microgravity simulator where the trajectory is realised by a manipulator mounted on a mock-up of the free-floating servicing satellite.
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