scholarly journals Flock Based Real Time Collision Avoidance Crowd Simulation

2015 ◽  
Author(s):  
Ziqi Wu ◽  
Xubo Yang
Keyword(s):  
Real Time ◽  
Collision Avoidance ◽  
Crowd Simulation

scholarly journals Avatar Locomotion in Crowd Simulation

2011 ◽  
Vol 10 (1) ◽  
pp. 13-19 ◽  
Author(s):  
Nuria Pelechano ◽  
Bernhard Spanlang ◽  
Alejandro Beacco
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Crowd Simulation ◽  
Character Animation ◽  
Upper Body ◽  
Virtual Characters ◽  
Continuous Space ◽  
Visual Results

This paper presents an Animation Planning Mediator (APM) designed to synthesize animations efficiently for virtual characters in real time crowd simulation. From a set of animation clips, the APM selects the most appropriate and modifies the skeletal configuration of each character to satisfy desired constraints (e.g. eliminating foot-sliding or restricting upper body torsion), while still providing natural looking animations. We use a hardware accelerated character animation library to blend animations increasing the number of possible locomotion types. The APM allows the crowd simulation module to maintain control of path planning, collision avoidance and response. A key advantage of our approach is that the APM can be integrated with any crowd simulator working in continuous space. We show visual results achieved in real time for several hundreds of agents, as well as the quantitative ac-curacy.

Longitudinal and lateral collision avoidance control strategy for intelligent vehicles

2021 ◽  
pp. 095440702110240
Author(s):  
Ziyu Zhang ◽  
Chunyan Wang ◽  
Wanzhong Zhao ◽  
Jian Feng
Keyword(s):  
Real Time ◽  
Collision Avoidance ◽  
Decentralized Control ◽  
Control Strategy ◽  
Centralized Control ◽  
Lateral Control ◽  
Time Performance ◽  
Collision Avoidance Control ◽  
Avoidance Control ◽  
Control Accuracy

In order to solve the problems of longitudinal and lateral control coupling, low accuracy and poor real-time of existing control strategy in the process of active collision avoidance, a longitudinal and lateral collision avoidance control strategy of intelligent vehicle based on model predictive control is proposed in this paper. Firstly, the vehicle nonlinear coupling dynamics model is established. Secondly, considering the accuracy and real-time requirements of intelligent vehicle motion control in pedestrian crossing scene, and combining the advantages of centralized control and decentralized control, an integrated unidirectional decoupling compensation motion control strategy is proposed. The proposed strategy uses two pairs of unidirectional decoupling compensation controllers to realize the mutual integration and decoupling in both longitudinal and lateral directions. Compared with centralized control, it simplifies the design of controller, retains the advantages of centralized control, and improves the real-time performance of control. Compared with the decentralized control, it considers the influence of longitudinal and lateral control, retains the advantages of decentralized control, and improves the control accuracy. Finally, the proposed control strategy is simulated and analyzed in six working conditions, and compared with the existing control strategy. The results show that the proposed control strategy is obviously better than the existing control strategy in terms of control accuracy and real-time performance, and can effectively improve vehicle safety and stability.

scholarly journals COLREG-Compliant Optimal Path Planning for Real-Time Guidance and Control of Autonomous Ships

2021 ◽  
Vol 9 (4) ◽  
pp. 405
Author(s):  
Raphael Zaccone
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Optimal Path ◽  
Open Water ◽  
Optimal Path Planning ◽  
Guidance And Control ◽  
Real Time Applications ◽  
And Control

While collisions and groundings still represent the most important source of accidents involving ships, autonomous vessels are a central topic in current research. When dealing with autonomous ships, collision avoidance and compliance with COLREG regulations are major vital points. However, most state-of-the-art literature focuses on offline path optimisation while neglecting many crucial aspects of dealing with real-time applications on vessels. In the framework of the proposed motion-planning, navigation and control architecture, this paper mainly focused on optimal path planning for marine vessels in the perspective of real-time applications. An RRT*-based optimal path-planning algorithm was proposed, and collision avoidance, compliance with COLREG regulations, path feasibility and optimality were discussed in detail. The proposed approach was then implemented and integrated with a guidance and control system. Tests on a high-fidelity simulation platform were carried out to assess the potential benefits brought to autonomous navigation. The tests featured real-time simulation, restricted and open-water navigation and dynamic scenarios with both moving and fixed obstacles.

scholarly journals A Probabilistic Model for Real-Time Semantic Prediction of Human Motion Intentions from RGBD-Data

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4141
Author(s):  
Wouter Houtman ◽  
Gosse Bijlenga ◽  
Elena Torta ◽  
René van de Molengraft
Keyword(s):  
Real Time ◽  
Collision Avoidance ◽  
Probabilistic Model ◽  
Real Life ◽  
Human Motion ◽  
Model Based ◽  
Multiple Hypotheses ◽  
Navigation Algorithms ◽  
The Right ◽  
Motion Behavior

For robots to execute their navigation tasks both fast and safely in the presence of humans, it is necessary to make predictions about the route those humans intend to follow. Within this work, a model-based method is proposed that relates human motion behavior perceived from RGBD input to the constraints imposed by the environment by considering typical human routing alternatives. Multiple hypotheses about routing options of a human towards local semantic goal locations are created and validated, including explicit collision avoidance routes. It is demonstrated, with real-time, real-life experiments, that a coarse discretization based on the semantics of the environment suffices to make a proper distinction between a person going, for example, to the left or the right on an intersection. As such, a scalable and explainable solution is presented, which is suitable for incorporation within navigation algorithms.

scholarly journals Parallel Motion Simulation of Large-Scale Real-Time Crowd in a Hierarchical Environmental Model

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Xin Wang ◽  
Jianhua Zhang ◽  
Massimo Scalia
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Simulation Method ◽  
Crowd Simulation ◽  
Motion Path ◽  
Motion Simulation ◽  
Environmental Model ◽  
Parallel Methods ◽  
Parallel Motion ◽  
Methods Numerical

This paper presents a parallel real-time crowd simulation method based on a hierarchical environmental model. A dynamical model of the complex environment should be constructed to simulate the state transition and propagation of individual motions. By modeling of a virtual environment where virtual crowds reside, we employ different parallel methods on a topological layer, a path layer and a perceptual layer. We propose a parallel motion path matching method based on the path layer and a parallel crowd simulation method based on the perceptual layer. The large-scale real-time crowd simulation becomes possible with these methods. Numerical experiments are carried out to demonstrate the methods and results.

scholarly journals Obstacle Avoidace Robot Using LabView

2015 ◽  
Vol 4 (3) ◽  
pp. 164
Author(s):  
Tasher Ali Sheikh ◽  
Swacheta Dutta ◽  
Smriti Baruah ◽  
Pooja Sharma ◽  
Sahadev Roy
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Autonomous Robotics ◽  
Continuous Transition ◽  
Heavy Burden ◽  
Avoidance Strategy ◽  
Small Period ◽  
Specific Amount

The concept of path planning and collision avoidance are two of the most common theories applied for designing and developing in advanced autonomous robotics applications. NI LabView makes it possible to implement real-time processor for obstacle avoidance. The obstacle avoidance strategy ensures that the robot whenever senses the obstacle stops without being collided and moves freely when path is free, but sometimes there exists a probability that once the path is found free and the robot starts moving, then within a fraction of milliseconds, the robot again sense the obstacle and it stops. This continuous swing of stop and run within a very small period of time may cause heavy burden on the system leading to malfunctioning of the components of the system. This paper deals with overcoming this drawback in a way that even after the robot calculates the path is free then also it will wait for a specific amount of time before running it. So as to confirm that if again the sensor detects the obstacle within that specified period then robot don’t need to transit its state suddenly thus avoiding continuous transition of run and stop. Thus it reduces the heavy burden on the system.

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