Proceedings ArticleDOI
Evolutionary artificial potential fields and their application in real time robot path planning
Prahlad Vadakkepat,Kay Chen Tan,Wang Ming-Liang +2 more
- Vol. 1, pp 256-263
TLDR
Simulation results show that the proposed EAPF methodology is efficient and robust for robot path planning with non-stationary goals and obstacles.Abstract:
A new methodology named Evolutionary Artificial Potential Field (EAPF) is proposed for real-time robot path planning. The artificial potential field method is combined with genetic algorithms, to derive optimal potential field functions. The proposed EAPF approach is capable of navigating robot(s) situated among moving obstacles. Potential field functions for obstacles and goal points are also defined. The potential field functions for obstacles contain tunable parameters. The multi-objective evolutionary algorithm (MOEA) is utilized to identify the optimal potential field functions. Fitness functions such as goal-factor, obstacle-factor, smoothness-factor and minimum-pathlength-factor are developed for the MOEA selection criteria. An algorithm named escape-force is introduced to avoid the local minima associated with EAPF. Moving obstacles and moving goal positions were considered to test the robust performance of the proposed methodology. Simulation results show that the proposed methodology is efficient and robust for robot path planning with non-stationary goals and obstacles.read more
Citations
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Journal ArticleDOI
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Nguyen Cong Luong,Dinh Thai Hoang,Shimin Gong,Dusit Niyato,Ping Wang,Ying-Chang Liang,Dong In Kim +6 more
TL;DR: This paper presents a comprehensive literature review on applications of deep reinforcement learning (DRL) in communications and networking, and presents applications of DRL for traffic routing, resource sharing, and data collection.
Posted Content
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Nguyen Cong Luong,Dinh Thai Hoang,Shimin Gong,Dusit Niyato,Ping Wang,Ying-Chang Liang,Dong In Kim +6 more
TL;DR: In this paper, a comprehensive literature review on applications of deep reinforcement learning in communications and networking is presented, which includes dynamic network access, data rate control, wireless caching, data offloading, network security, and connectivity preservation.
Journal ArticleDOI
Optimal path planning of mobile robots: A review
P. Raja,S. Pugazhenthi +1 more
TL;DR: An overview of the research progress in path planning of a mobile robot for off-line as well as on-line environments is provided and shows that evolutionary optimization algorithms are computationally efficient and hence are increasingly being used in tandem with classic approaches while handling Non-deterministic Polynomial time hard problems.
Journal ArticleDOI
Path planning for mobile robots using Bacterial Potential Field for avoiding static and dynamic obstacles
TL;DR: It was demonstrated that the BPF outperforms the APF, GPF, and the PBPF methods by reducing the computational time to find the optimal path at least by a factor of 1.59.
Journal ArticleDOI
Path Planning for the Mobile Robot: A Review
TL;DR: The survey shows GA (genetic algorithm), PSO (particle swarm optimization algorithm), APF (artificial potential field), and ACO (ant colony optimization algorithm) are the most used approaches to solve the path planning of mobile robot.
References
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Journal ArticleDOI
Real-time obstacle avoidance for manipulators and mobile robots
TL;DR: This paper reformulated the manipulator con trol problem as direct control of manipulator motion in operational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and geometric transformation.
Journal ArticleDOI
The vector field histogram-fast obstacle avoidance for mobile robots
Johann Borenstein,Yoram Koren +1 more
TL;DR: A real-time obstacle avoidance method for mobile robots which has been developed and implemented, named the vector field histogram (VFH), permits the detection of unknown obstacles and avoids collisions while simultaneously steering the mobile robot toward the target.
Book
IROS '95 : proceedings of the 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems : human robot interaction and cooperative robots, August 5-9, 1995, Pittsburgh, Pennsylvania, USA
TL;DR: In this article, the authors focused on Human-Robot Interaction and Cooperative Robots (IROS '95) and showed that because the abilities of human and robot operations complement one another, cooperative work between the two will be beneficial.
Journal ArticleDOI
A comparative study on the path length performance of maze-searching and robot motion planning algorithms
TL;DR: A comparison shows that the special structure of graphs that correspond to planar environments with obstacles actually makes it possible to exceed the efficiency of general maze-searching algorithms.