• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.2
• /
• pp.389-397
• /
• 2011

The global dynamic window approach (DWA) is widely used to generate the shortest path of mobile robots considering obstacles and kinematic constraints. However, the dynamic constraints of robots should be considered to generate the minimum-time path. We propose a modified global DWA considering the dynamic constraints of robots. The reference path is generated using A* algorithm and smoothed by cardinal spline function. The trajectory is then generated to follows the reference path in the minimum time considering the robot dynamics. Finally, the local path is generated using the dynamic window which includes additional terms of speed and orientation. Simulation and experimental results are presented to verify the performance of the proposed method.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.24 no.1
• /
• pp.61-69
• /
• 2021

Recently, autonomous navigation technology is actively being developed due to the increasing demand of an unmanned surface vehicle(USV). Local planning is essential for the USV to safely reach its destination along paths. the dynamic window approach(DWA) algorithm is a well-known navigation scheme as a local path planning. However, the existing DWA algorithm does not consider path line tracking, and the fixed weight coefficient of the evaluation function, which is a core part, cannot provide flexible path planning for all situations. Therefore, in this paper, we propose a new DWA algorithm that can follow path lines in all situations. Fixed weight coefficients were trained using reinforcement learning(RL) which has been actively studied recently. We implemented the simulation and compared the existing DWA algorithm with the DWA algorithm proposed in this paper. As a result, we confirmed the effectiveness of the proposed algorithm.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.12 no.5
• /
• pp.295-301
• /
• 2017

Recently, autonomous navigation technology, obstacle recognition, and obstacle collision avoidance technology are actively being developed for an unmanned surface vehicle (USV). The path to move from the current location to the destination should be planned, in order for an USV to autonomously operate safely to its destination. The dynamic window approach (DWA) is a well-known navigation scheme as a local path planning. The DWA algorithm derives the linear velocity and angular velocity by evaluating the destination direction, velocity, and distance from the obstacle. However, because DWA algorithm does not consider tracking the path, when using only the DWA algorithm, the ship may navigate away from the path line after avoiding obstacles. In this paper, we propose an improved DWA algorithm that can follow path line. And we implemented the simulation and compared the existing DWA algorithm with the improved DWA algorithm proposed in this paper. As a result, it is confirmed that the proposed DWA algorithm follows the path line better.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.7
• /
• pp.624-630
• /
• 2007

The dynamic window approach(DWA) is a well known technique for reactive collision avoidance. It shows safe and efficient performance in real-world experiments. However, a robot can get stuck in local minima because no information about the connectivity of the free space is used to determine the motion. The global DWA can solve this problem of local minima by adding a navigation function. Even with the global DWA, it is still difficult for a robot to execute an abrupt change in its direction, for example, entering from the corridor to a doorway. This paper proposes a modified global DWA using the included angles of waypoints extracted from an optimal path. This scheme enables the robot to decelerate in advance before turning into the doorway. Therefore the robot can reach the goal position more safely and efficiently at high speeds.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.94-96
• /
• 2021

In this paper, we develop a new navigation algorithm for industrial mobile robots to arrive at the destination in unknown environment. To achieve this, we suggest a navigation algorithm that combines Dynamic Window Approach (DWA) and Dijkstra path planning algorithm. We compare Local Dynamic Window Approach (LDWA), Global Dynamic Window Approach(GDWA), Rapidly-exploring Random Tree (RRT) Algorithm. The navigation algorithm using Dijkstra algorithm combined with LDWA and GDWA makes mobile robots to reach the destination. and obstacles faced during the path planning process of LDWA and GDWA. Then, we compare on time taken to arrive at the destination, obstacle avoidance and computation complexity of each algorithm. To overcome the limitation, we seek ways to use the optimized navigation algorithm for industrial use.

• The Journal of Korea Robotics Society
• /
• v.3 no.3
• /
• pp.212-218
• /
• 2008

Collision avoidance is a fundamental and important task of an autonomous mobile robot for safe navigation in real environments with high uncertainty. Obstacles are classified into static and dynamic obstacles. It is difficult to avoid dynamic obstacles because the positions of dynamic obstacles are likely to change at any time. This paper proposes a scheme for vision-based avoidance of dynamic obstacles. This approach extracts object candidates that can be considered moving objects based on the labeling algorithm using depth information. Then it detects moving objects among object candidates using motion vectors. In case the motion vectors are not extracted, it can still detect the moving objects stably through their color information. A robot avoids the dynamic obstacle using the dynamic window approach (DWA) with the object path estimated from the information of the detected obstacles. The DWA is a well known technique for reactive collision avoidance. This paper also proposes an algorithm which autonomously registers the obstacle color. Therefore, a robot can navigate more safely and efficiently with the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.871-875
• /
• 2003

To detect and avoid obstacles is one of the important tasks of mobile navigation. In a real environment, when a mobile robot encounters dynamic obstacles, it is required to simultaneously detect and avoid obstacles for its body safely. In previous vision system, mobile robot has used it as either a passive sensor or an active sensor. This paper proposes a new obstacle detection algorithm that uses a stereo camera as both a passive sensor and an active sensor. Our system estimates the distances from obstacles by both passive-correspondence and active-correspondence using laser slit. The system operates in three steps. First, a far-off obstacle is detected by the disparity from stereo correspondence. Next, a close obstacle is acquired from laser slit beam projected in the same stereo image. Finally, we implement obstacle avoidance algorithm, adopting the modified Dynamic Window Approach (DWA), by using the acquired the obstacle's distance.

• Journal of Broadcast Engineering
• /
• v.25 no.5
• /
• pp.734-741
• /
• 2020

This article proposes a new pedestrian avoidance algorithm for social robots that coexist and communicate with humans and do not induce stress caused by invasion of psychological safety distance(Social Distance). To redefine the pedestrian model, pedestrians are clustered according to the pedestrian's gait characteristics(straightness, speed) and a social distance is defined for each pedestrian cluster. After modeling pedestrians(obstacles) with the social distances, integrated navigation algorithm is completed by applying the newly defined pedestrian model to commercial obstacle avoidance and path planning algorithms. To show the effectiveness of the proposed algorithm, two commercial obstacle avoidance & path planning algorithms(the Dynamic Window Approach (DWA) algorithm and the Timed Elastic Bands (TEB) algorithm) are used. Four cases were experimented in applying and non-applying the new pedestrian model, respectively. Simulation results show that the proposed algorithm can significantly reduce the stress index of pedestrians without loss of traveling time.