Abstract
Mobile robots in industry are commonly used in warehouses and factories. To achieve the highest production rate, requirements for path planning algorithms have caused researchers to pay significant attention to this problem. The artificial potential field algorithm, which is a local path planning algorithm, has been previously modified to obtain higher smoothness of path, to solve the stagnation problem and to jump off the local minimum. The last itemized problem is taken into account in this paper—local minimum avoidance. Most of the modifications of artificial potential field algorithms focus on a mechanism to jump off a local minimum when robots stagnate. From the efficiency point of view, the mobile robot should bypass the local minimum instead of jumping off it. This paper proposes a novel artificial potential field supported by augmented reality to bypass the upcoming local minimum. The algorithm predicts the upcoming local minimum, and then the mobile robot’s perception is augmented to bypass it. The proposed method allows the generation of shorter paths compared with jumping-off techniques, due to lack of stagnation in a local minimum. This method was experimentally verified using a Husarion ROSbot 2.0 PRO mobile robot and Robot Operating System in a laboratory environment.
Highlights
In recent years, the path planning problem has been intensively researched due to manufacturing and warehouses robotization [1,2,3]
The artificial potential field (APF) algorithm is a local path planning algorithm that was proposed by Khatib in 1986 [9]
This paper proposes a novel APF supported by augmented reality (AR-APF) to detect an upcoming local minimum and generate a virtual wall to bypass it
Summary
The path planning problem has been intensively researched due to manufacturing and warehouses robotization [1,2,3]. Satisfactory results with much lower computation times can be obtained by sampling-based rapidlyexploring random tree (RRT) instead of linear search of trajectory points [7,8] Another problem related to global path planning algorithms is the dynamic environment. Any change of environment causes the previous result to be potentially non-executable due to collisions For these reasons, local path planning algorithms are still being intensively researched. The artificial potential field (APF) algorithm is a local path planning algorithm that was proposed by Khatib in 1986 [9] This method is based on the interaction of the electrostatic particles. This paper proposes a novel APF supported by augmented reality (AR-APF) to detect an upcoming local minimum and generate a virtual wall to bypass it Such an approach allows mobile robots to reduce the path length and is more efficient.
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