Stable and efficient collision detection scheme for hip-surgery training system

Sun

et al. 2021

Sensors

Mobile construction machineries are accident-prone on a dynamic construction site, as the site environment is constantly changing and continuous safety monitoring by human beings is impossible. These accidents usually happen in the form of machinery overturning or collapsing into risk areas, including the foundation pit, slopes, or soft soil area. Therefore, preventing mobile construction machineries from entering risk areas is the key. However, currently, there is a lack of practical safety management techniques to achieve this. Utilizing a wireless sensor device to collect the location information of mobile construction machineries, this research develops a safety warning algorithm to prevent the machineries moving into risk area and reduces onsite overturning or collapsing accidents. A modified axis aligned bounding box method is proposed according to the movement patterns of mobile construction machineries, and the warning algorithm is developed based on the onsite safety management regulations. The algorithm is validated in a real case simulation when machinery enters the warning zone. The simulation results showed that the overall algorithm combining the location sensing technology and the modified bounding box method could detect risk and give warnings in a timely manner. This algorithm can be implemented for the safety monitoring of mobile construction machineries in daily onsite management.

Section: The Bounding Box Methodsmentioning

confidence: 99%

A Safety Warning Algorithm Based on Axis Aligned Bounding Box Method to Prevent Onsite Accidents of Mobile Construction Machineries

Sun

et al. 2021

Sensors

“…The surgical instrument model and the bounding volume hierarchy inside the virtual sphere only needs to detect each other, which saves the time of collision detection between the surgical instrument model and other hierarchical structures. 16…”

Section: The Methods Of Hybrid Bounding Volume Hierarchy Based On Virtmentioning

confidence: 99%

Design and Application of Bounding Volume Hierarchy Collision Detection Algorithm Based on Virtual Sphere

Chen

Yang

2019

J. Mech. Med. Biol.

Self Cite

The result of collision detection is closely related to the further deformation or cutting action of soft tissue. In order to further improve the efficiency and stability of collision detection, in this paper, a collision detection algorithm of bounding volume hierarchy based on virtual sphere was proposed. The proposed algorithm was validated and the results show that the detection efficiency of the bounding volume hierarchy algorithm based on virtual sphere is higher than that of the serial hybrid bounding volume hierarchy algorithm and the parallel hybrid bounding volume hierarchy algorithm. Different collision detection algorithms were tested and the results show that the collision detection algorithm based on virtual sphere has high detection efficiency and good stability. As the number of triangular patches increased, the advantage was more and more obvious. Finally, the proposed algorithm was applied to two large and medium-sized virtual scenes to implement the collision detection between the vastus lateralis muscle, thigh and surgical instrument. Based on the virtual sphere, the collision detection algorithm of bounding volume hierarchy can implement efficient and stable collision detection in a virtual surgery system. Meanwhile, the algorithm can be combined with other acceleration algorithms (such as the multithread acceleration algorithm) to further improve detection efficiency. models. Detection algorithm should meet the authenticity requirement and fluency requirement, and can implement real-time user interaction. 1 At present, the collision detection algorithm can be divided into two categories, one is based on temporal domain, the other is based on spatial domain. The collision detection algorithm based on temporal domain is divided into static collision detection, constant collision detection and discrete collision detection. [2][3][4] The collision detection algorithm based on spatial domain is divided into collision detection algorithm based on entity space and collision detection algorithm based on image space. 5 In recent years, with the development of research on virtual surgery, the researches on the collision detection of the human tissue model in the virtual scene are gradually increasing. 6 Good simulation results in some research have been achieved.Bournemouth University in the UK has developed a collision detection in a virtual scene with a rectum as an environmental model. They used a geometric projection method to handle the collision, which directly corrected the positions of spheres after a contact was detected. In this method, there was no need to compute the penalty forces and hence the solving process was speeded up.Researchers from Kagawa University in Japan developed a fast collision detection algorithm based on axis-aligned bounding box (AABB) method for the virtual reality training system. In this algorithm, there are two key collision detection areas: Area I: the area around the catheter tip and Area II: the previous collision area. Area I is a dynamic area and it will chang...

“…For example, Wang et al proposed the imitating longitude and latitude method. 156 Existing methods have not been able to deal with the CD for concave models very well, few methods can directly detect collision without dividing them into convex models.…”

Section: Future Potentialmentioning

confidence: 99%

A review of collision detection for deformable objects

Computer Animation & Virtual

Cao

2021

Self Cite

In the process of simulating and modeling real objects, the phenomenon of objects penetrating each other may occur in the model, which is unrealistic and then the research of collision detection (CD) is generated. As a bottleneck of virtual environment simulation, researchers have conducted in-depth research on CD, especially the CD of deformable objects. In this paper, we briefly review the related research on CD of deformable objects regarding relevant literature. First, we briefly introduce previous reviews of CD. Second, we review the popular research methods and limitations of CD between deformable objects. Third, we review the popular research methods and limitations of self-collision detection in deformable objects. Finally, we discuss future directions of development.This review can be used as a reference for the application of CD in all directions.