TY - GEN
T1 - Walk-in NPC Behavior Based on RVO Using Waypoints
AU - Wicaksono, Georgius Bagas
AU - Hariadi, Mochamad
AU - Nugroho, Supeno Mardi Susiki
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Behavior is one of the major points for Artificial Intelligence (AI). One of the most common researches regarding AI behavior is the behavior in the navigation system, in order to generate navigation for AI to make it more natural. In some simulations, the pedestrian's behavior in navigation is not natural, predictable, and causes other unexpected events such as deadlock, and so on. This study employs the navigation system with Waypoints Navigation to determine paths or branches to take, also to restrict and to liberate AI in walking along the path, and the obstacle avoidance system from Reciprocal Velocity Obstacle (RVO) to assist in avoiding obstacles or other agents. Experiment results show that agents have various and unpredicted results in their behavior where first, the adjustment of parameters enables the number of the pedestrians randomly entering the branch path. Second, the possibility of the deadlock occurs can be reduced by 50 % or more, depends on the numbers of agents and value used in the parameters. Third, a balance between the number of pedestrians walking and standing still or idling can be achieved.
AB - Behavior is one of the major points for Artificial Intelligence (AI). One of the most common researches regarding AI behavior is the behavior in the navigation system, in order to generate navigation for AI to make it more natural. In some simulations, the pedestrian's behavior in navigation is not natural, predictable, and causes other unexpected events such as deadlock, and so on. This study employs the navigation system with Waypoints Navigation to determine paths or branches to take, also to restrict and to liberate AI in walking along the path, and the obstacle avoidance system from Reciprocal Velocity Obstacle (RVO) to assist in avoiding obstacles or other agents. Experiment results show that agents have various and unpredicted results in their behavior where first, the adjustment of parameters enables the number of the pedestrians randomly entering the branch path. Second, the possibility of the deadlock occurs can be reduced by 50 % or more, depends on the numbers of agents and value used in the parameters. Third, a balance between the number of pedestrians walking and standing still or idling can be achieved.
KW - AI Natural Behavior
KW - Artificial Intelligence
KW - Reciprocal Velocity Obstacle
KW - Waypoints
UR - http://www.scopus.com/inward/record.url?scp=85137872582&partnerID=8YFLogxK
U2 - 10.1109/ISITIA56226.2022.9855375
DO - 10.1109/ISITIA56226.2022.9855375
M3 - Conference contribution
AN - SCOPUS:85137872582
T3 - 2022 International Seminar on Intelligent Technology and Its Applications: Advanced Innovations of Electrical Systems for Humanity, ISITIA 2022 - Proceeding
SP - 92
EP - 97
BT - 2022 International Seminar on Intelligent Technology and Its Applications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd International Seminar on Intelligent Technology and Its Applications, ISITIA 2022
Y2 - 20 July 2022 through 21 July 2022
ER -