Physics Substepping: Full Update Or Collision Only?

Aug 13, 2025 by Natalie Brooks 52 views

Physics Substepping: Full Update or Collision Resolution?

Hey guys, let's dive into a crucial aspect of physics simulation: physics substepping. When you're building a game or any application that relies on realistic physics, stability is key. No one wants objects clipping through walls or exploding for no reason! That's where substeps come in. But the big question is: should we apply these substeps to the entire physics update, or just the collision resolution and constraint solving parts? Let's break it down and figure out what's best for your simulation.

Understanding Physics Substepping

First off, what exactly is physics substepping? Imagine you have a physics engine that updates the world 60 times per second. That means each frame, the engine calculates the positions, velocities, and interactions of all your objects. But sometimes, that single update isn't enough. Fast-moving objects might tunnel through thin walls, or complex interactions between objects might lead to instability. Substepping is like taking smaller steps within each frame. Instead of one big update, you divide the frame into multiple smaller substeps. This gives the physics engine more chances to accurately resolve collisions and constraints, leading to a much more stable and believable simulation. The core idea of substepping is to enhance the accuracy and stability of your physics simulation by dividing each frame into smaller time increments. This approach is particularly beneficial when dealing with fast-moving objects or complex interactions, where a single, larger time step might lead to inaccuracies or instability. The fundamental concept behind substepping involves breaking down the main simulation loop into several smaller steps. Instead of calculating the physics for an entire frame in one go, the simulation advances the physics by a fraction of the frame time in each substep. This allows the physics engine to more accurately capture the dynamics of the system, especially in scenarios where forces and velocities change rapidly. Think of it like slowing down a fast-paced scene in a movie to catch all the details; substepping allows the physics engine to examine the simulation in more detail over time. Each substep involves updating the positions, velocities, and orientations of objects, as well as resolving collisions and applying constraints. By performing these calculations more frequently within a single frame, the simulation can better handle situations where objects are moving quickly or where multiple interactions occur simultaneously. This leads to a more stable and realistic simulation, reducing the likelihood of objects passing through each other or exhibiting erratic behavior. The number of substeps per frame is a crucial parameter that needs to be carefully chosen. Increasing the number of substeps generally improves accuracy and stability but also increases the computational cost. A higher substep count means the physics engine has to perform more calculations per frame, which can impact performance, especially in complex simulations with many objects. Therefore, finding the right balance between accuracy and performance is essential when configuring the substepping parameters for your physics engine. Substepping plays a vital role in enhancing the robustness of collision detection and response. With smaller time increments, the simulation is less likely to miss collisions between objects, especially fast-moving ones. This is because the smaller steps allow the engine to check for collisions more frequently, reducing the chances of objects tunneling through each other. Furthermore, substepping improves the accuracy of collision response calculations. By resolving collisions in smaller increments, the simulation can more accurately apply impulse forces and adjust velocities, leading to more realistic and stable interactions. In summary, physics substepping is a technique that involves dividing each frame into multiple smaller steps to improve the accuracy and stability of a physics simulation. This approach is particularly effective in scenarios with fast-moving objects and complex interactions, where a single, larger time step might lead to inaccuracies or instability. By carefully choosing the number of substeps per frame, developers can strike a balance between accuracy and performance, resulting in a more robust and believable simulation. Substepping is not just a performance optimization technique; it's a fundamental aspect of creating realistic and stable physics simulations. It allows us to bridge the gap between the discrete world of computer calculations and the continuous world of physics. By understanding how substepping works, you can make informed decisions about how to configure your physics engine and achieve the results you're looking for.

The Two Main Approaches to Physics Substepping

So, we've established why substepping is important, but let's get to the core of the question: how do we apply it? There are two primary ways to approach this, and each has its own pros and cons. Let's get into the nitty-gritty of these approaches.

1. Substepping the Entire Physics Update

This approach involves running every stage of the physics update multiple times per frame. That includes:

Applying forces and torques: This is where you add gravity, motor forces, or any other external influences to your objects.
Integrating motion: This is where the physics engine calculates the new positions and velocities of objects based on the forces acting on them.
Collision detection: This is where the engine figures out which objects are colliding with each other.
Collision resolution: This is where the engine calculates the response to collisions, like bouncing or sliding.
Constraint solving: This is where the engine enforces constraints, like joints or hinges, to keep objects connected and behaving correctly.

Substepping the entire update is like slowing down time for the whole physics world. It's the most comprehensive approach, but it also comes with the highest computational cost. When you opt to substep the entire physics update process, you're essentially treating each substep as a miniature simulation within the larger frame. This means that every phase of the physics calculation—from applying forces and integrating motion to collision detection, collision resolution, and constraint solving—is executed multiple times per frame. This holistic approach to substepping offers several advantages, but it also introduces certain trade-offs that need to be carefully considered. One of the primary benefits of substepping the entire update is the enhanced accuracy and stability it provides to the simulation. By breaking down the simulation into smaller time increments, the physics engine can more precisely track the movement and interactions of objects. This is particularly crucial in scenarios involving fast-moving objects or complex interactions, where a single, larger time step might lead to inaccuracies or missed collisions. The smaller substeps allow the engine to capture subtle changes in motion and resolve collisions more effectively, resulting in a more realistic and stable simulation. Furthermore, substepping the entire update can significantly improve the robustness of constraint solving. Constraints, such as joints or hinges, play a vital role in maintaining the structural integrity of simulated objects and systems. However, solving constraints accurately can be computationally challenging, especially in complex scenarios with multiple interacting constraints. By performing constraint solving within each substep, the simulation can iteratively refine the solution, leading to more stable and accurate constraint behavior. This can prevent issues like joint drift or unexpected object separations, which can undermine the realism of the simulation. Despite its advantages, substepping the entire update comes with a significant computational cost. Each substep requires the engine to perform all the physics calculations from scratch, which can quickly add up, especially in simulations with a large number of objects and interactions. The increased computational load can impact performance, leading to lower frame rates or slower simulation speeds. Therefore, it's crucial to carefully consider the performance implications of substepping the entire update and strike a balance between accuracy and computational efficiency. In practice, the decision to substep the entire update often depends on the specific requirements of the simulation. For applications that prioritize accuracy and stability, such as scientific simulations or high-fidelity games, substepping the entire update might be the preferred approach. However, for simulations where performance is a critical concern, alternative substepping strategies or optimization techniques might be necessary to maintain a smooth frame rate. Substepping the entire physics update is a powerful technique for enhancing the accuracy and stability of physics simulations. By breaking down the simulation into smaller time increments and performing all physics calculations within each substep, the engine can more effectively track the movement and interactions of objects, resolve collisions, and enforce constraints. However, the increased computational cost of this approach necessitates careful consideration of performance trade-offs. Ultimately, the choice of whether to substep the entire update depends on the specific requirements of the simulation and the desired balance between accuracy and performance. This approach tends to produce the most stable and accurate results, as it addresses potential issues at every stage of the physics simulation pipeline. However, this comes at a cost. Since every calculation is performed multiple times, the computational overhead is significantly higher compared to other substepping methods. This can be a major concern for performance-critical applications, especially those with a large number of objects or complex interactions. Despite the performance implications, substepping the entire update is often the preferred method in applications where accuracy and stability are paramount. Scientific simulations, high-fidelity games, and engineering applications frequently benefit from this approach. In these scenarios, the increased computational cost is justified by the improved realism and reliability of the simulation. Furthermore, advancements in hardware and software optimization techniques have made it increasingly feasible to use full substepping in a wider range of applications. Modern processors are capable of handling substantial computational loads, and optimized physics engines can efficiently distribute calculations across multiple cores. This allows developers to leverage the benefits of full substepping without sacrificing performance. In conclusion, substepping the entire physics update is a comprehensive approach that offers enhanced accuracy and stability but comes with a higher computational cost. The decision to use this method depends on the specific requirements of the simulation, the available hardware resources, and the desired balance between accuracy and performance. For applications that demand the highest levels of realism and reliability, full substepping is often the optimal choice. However, for performance-sensitive applications, alternative substepping strategies or optimization techniques may be necessary.

2. Substepping Collision Resolution and Constraint Solving

This approach focuses on the most problematic parts of the physics update: the collision resolution and constraint solving stages. The idea here is that these stages are the most likely to cause instability, especially when dealing with high-speed collisions or complex constraints. So, instead of substepping the entire update, we only apply substeps to these specific stages. This means:

Applying forces and torques is done once per frame.
Integrating motion is done once per frame.
Collision detection is done once per frame.
Collision resolution is substeped
Constraint solving is substeped

This approach is a good middle ground between accuracy and performance. It's less computationally expensive than substepping the entire update, but it still provides a significant boost in stability. When you opt to substep only the collision resolution and constraint solving stages of the physics update, you're strategically targeting the areas of the simulation that are most prone to instability and inaccuracies. This approach offers a balance between accuracy and performance, making it a popular choice for many physics-based applications. The rationale behind this approach is that collision resolution and constraint solving are often the most computationally intensive and error-prone parts of the physics simulation. Collisions involve calculating contact points, normals, and impulses, while constraint solving requires enforcing relationships between objects, such as joints or hinges. These calculations can be particularly challenging when dealing with fast-moving objects, complex geometries, or a large number of constraints. By focusing substepping efforts on these stages, the simulation can achieve a significant improvement in stability and accuracy without incurring the full computational cost of substepping the entire update. Substepping collision resolution allows the simulation to more accurately handle interactions between objects, especially in scenarios where collisions occur at high speeds or involve complex shapes. The smaller substeps enable the engine to detect and resolve collisions more precisely, reducing the likelihood of objects passing through each other or exhibiting unrealistic behavior. This is particularly important for simulations that require a high degree of realism, such as games or virtual reality applications. Similarly, substepping constraint solving improves the stability and accuracy of constraint-based systems. Constraints play a crucial role in maintaining the structural integrity of simulated objects and systems, but solving them accurately can be computationally challenging. By performing constraint solving within each substep, the simulation can iteratively refine the solution, leading to more stable and realistic constraint behavior. This can prevent issues like joint drift or unexpected object separations, which can undermine the realism of the simulation. Compared to substepping the entire update, substepping collision resolution and constraint solving offers a significant performance advantage. By limiting substepping to the most critical stages of the simulation, the computational overhead is reduced, allowing for higher frame rates and smoother performance. This makes this approach particularly well-suited for applications where performance is a primary concern, such as mobile games or simulations running on resource-constrained devices. However, it's important to note that substepping only collision resolution and constraint solving might not address all potential sources of instability in the simulation. For example, inaccuracies in the integration of motion can still lead to problems, especially in scenarios with highly dynamic forces or rapidly changing velocities. Therefore, it's crucial to carefully evaluate the specific requirements of the simulation and consider whether substepping the entire update might be necessary to achieve the desired level of stability and accuracy. Substepping collision resolution and constraint solving is a strategic approach to improving the stability and accuracy of physics simulations. By focusing substepping efforts on the most critical stages of the simulation, this approach offers a balance between performance and accuracy, making it a popular choice for many applications. While it might not address all potential sources of instability, it provides a significant improvement in the handling of collisions and constraints, leading to more realistic and stable simulations. This method can provide a significant boost in stability without the full performance cost. By substepping only the collision resolution and constraint solving phases, the computational overhead is reduced, making it a more efficient option for many applications. This approach is particularly effective in scenarios where the primary sources of instability are related to collisions and constraints. However, it's important to recognize that it might not address issues arising from other parts of the physics update, such as the integration of motion. If the forces acting on objects are highly dynamic or change rapidly, inaccuracies in the integration step can still lead to problems. Despite this limitation, substepping collision resolution and constraint solving is a widely used technique in game development and other real-time simulation applications. It offers a good balance between stability, accuracy, and performance, making it a practical choice for a wide range of scenarios. Furthermore, it can be combined with other optimization techniques to achieve even better performance without sacrificing simulation quality. In conclusion, substepping collision resolution and constraint solving is a strategic approach that targets the most critical aspects of the physics update. It offers a significant improvement in stability and accuracy while minimizing the performance impact. This makes it a valuable tool for developers seeking to create realistic and stable physics simulations without exceeding their computational budget.

Which Approach Should You Choose?

Okay, so we've looked at the two main options, but how do you decide which one is right for your project? The best approach really depends on a few key factors:

Complexity of your simulation: If you have a simple simulation with relatively few objects and interactions, substepping only collision resolution and constraint solving might be enough. But if you're dealing with a complex scene with lots of objects, constraints, and high-speed collisions, substepping the entire update might be necessary.
Performance budget: How much processing power can you afford to dedicate to physics? If you're targeting a low-end device or need to maintain a very high frame rate, you'll probably want to stick with substepping only collision resolution and constraint solving. But if you have more headroom, substepping the entire update can provide the best results.
Desired level of accuracy: How important is it that your simulation is perfectly stable and realistic? If you're building a serious scientific simulation, you'll likely want to prioritize accuracy and go with substepping the entire update. But if you're building a casual game, you might be able to get away with a less accurate but more performant approach.

Let's break this down a little further with some examples:

Simple 2D platformer: Substepping collision resolution and constraint solving is likely sufficient.
Fast-paced racing game: You might need to substepping the entire update due to high-speed collisions.
Physics-based puzzle game: Substepping collision resolution and constraint solving could be a good balance.
Realistic vehicle simulation: Substepping the entire update is probably necessary for accuracy.

Ultimately, the best way to figure out what works for you is to experiment! Try both approaches and see how they perform in your specific scenario. Profile your code to identify bottlenecks and see where you can optimize. Don't be afraid to tweak your substepping settings to find the sweet spot between accuracy and performance. The decision between substepping the entire physics update and substepping only the collision resolution and constraint solving stages is a crucial one that can significantly impact the performance and stability of your simulation. To make the best choice for your project, it's essential to carefully consider the complexity of your simulation, your performance budget, and the desired level of accuracy. A simple simulation with relatively few objects and interactions may not require the comprehensive approach of substepping the entire update. In such cases, substepping only the collision resolution and constraint solving stages can provide a sufficient level of stability without incurring excessive computational costs. This approach is particularly well-suited for applications where performance is a primary concern, such as mobile games or simulations running on resource-constrained devices. However, if you're dealing with a complex scene that involves a large number of objects, intricate constraints, and high-speed collisions, substepping the entire update might be necessary to achieve the desired level of stability and realism. The increased computational cost is often justified in these scenarios, as the comprehensive approach ensures that all aspects of the physics simulation are accurately handled. Your performance budget plays a significant role in determining the appropriate substepping strategy. If you're targeting a low-end device or need to maintain a very high frame rate, you'll likely want to prioritize performance and opt for substepping only collision resolution and constraint solving. This approach minimizes the computational overhead, allowing your simulation to run smoothly even on less powerful hardware. On the other hand, if you have more processing power available, substepping the entire update can provide the best results, albeit at a higher computational cost. The desired level of accuracy is another critical factor to consider. If you're building a serious scientific simulation or an application where precise physics behavior is essential, you'll likely want to prioritize accuracy and go with substepping the entire update. This approach ensures that your simulation is as stable and realistic as possible, even under challenging conditions. However, if you're building a casual game or an application where perfect accuracy is not paramount, you might be able to get away with a less accurate but more performant approach, such as substepping only collision resolution and constraint solving. To illustrate these considerations, let's look at a few examples. For a simple 2D platformer game, substepping collision resolution and constraint solving is likely sufficient. The interactions between objects are relatively simple, and the performance demands are typically not excessive. In contrast, a fast-paced racing game with high-speed collisions might require substepping the entire update to ensure that collisions are handled accurately and the simulation remains stable. A physics-based puzzle game could benefit from a balanced approach, where substepping collision resolution and constraint solving provides a good trade-off between accuracy and performance. Finally, a realistic vehicle simulation, where precise handling and stability are crucial, would likely require substepping the entire update. Ultimately, the best way to determine the optimal substepping strategy for your project is to experiment and profile your code. Try both approaches, measure their performance in your specific scenario, and identify any bottlenecks. Don't hesitate to tweak your substepping settings to find the sweet spot between accuracy and performance. Remember, there's no one-size-fits-all solution, and the ideal approach may vary depending on the unique characteristics of your simulation. By carefully considering your simulation's complexity, your performance budget, and your desired level of accuracy, and by experimenting with different substepping strategies, you can ensure that your physics simulation is both stable and performant.

Other Tips for Improving Physics Stability

Substepping is a powerful tool, but it's not the only trick in the book! Here are a few other things you can do to improve the stability of your physics simulation:

Use a stable integration method: The way you integrate motion can have a big impact on stability. Some integration methods, like Euler integration, are simple but prone to instability, especially with larger time steps. Other methods, like Verlet integration or Runge-Kutta methods, are more stable but also more computationally expensive.
Clamp velocities: High velocities can lead to instability, so it's often a good idea to clamp the maximum velocity of your objects. This can prevent objects from gaining too much speed and causing problems.
Use penetration depth correction: When objects collide, they might penetrate each other slightly. Penetration depth correction is a technique for moving objects apart after a collision to prevent them from getting stuck or clipping through each other.
Tweak collision parameters: Physics engines often have parameters that control how collisions are handled, like restitution (bounciness) and friction. Adjusting these parameters can sometimes improve stability.
Use smaller time steps: Even without substepping, using a smaller fixed time step can improve stability. However, this will also increase the computational cost.

By combining these techniques with substepping, you can create a robust and stable physics simulation that behaves the way you expect it to. Physics simulation is a complex field, and stability can be a tricky issue to tackle. However, by understanding the techniques available and experimenting with different approaches, you can create realistic and reliable simulations for your projects. Substepping is a fundamental technique for enhancing physics simulation stability, but it's just one piece of the puzzle. To achieve truly robust and believable physics, it's essential to consider other factors and employ a variety of complementary techniques. The integration method used to update object positions and velocities plays a crucial role in simulation stability. Simple methods like Euler integration, while computationally efficient, can be prone to inaccuracies and instability, particularly when dealing with larger time steps or rapidly changing forces. More advanced methods, such as Verlet integration and Runge-Kutta methods, offer improved stability and accuracy but come at a higher computational cost. The choice of integration method should be carefully considered based on the specific requirements of the simulation and the available performance budget. Clamping velocities is another effective technique for preventing instability. Unbounded velocities can lead to objects tunneling through each other or exhibiting erratic behavior. By setting a maximum velocity limit, you can prevent objects from gaining excessive speed and ensure a more stable simulation. This technique is particularly useful in scenarios involving impulsive forces or collisions, where velocities can change dramatically in a short period of time. Penetration depth correction is a technique used to address the issue of objects interpenetrating during collisions. Due to the discrete nature of physics simulations, objects may sometimes overlap slightly after a collision. Penetration depth correction involves moving the objects apart to eliminate the overlap, preventing them from getting stuck or clipping through each other. This technique is essential for maintaining the realism and stability of collision response. The parameters that govern collision handling, such as restitution (bounciness) and friction, can also significantly impact simulation stability. Restitution determines the amount of energy conserved during a collision, while friction affects the resistance to motion between colliding surfaces. Adjusting these parameters can help to prevent issues like excessive bouncing or objects sliding uncontrollably. Careful tuning of collision parameters is often necessary to achieve realistic and stable collision behavior. Even without substepping, using a smaller fixed time step can improve simulation stability. Smaller time steps allow the physics engine to more accurately capture the dynamics of the system, reducing the likelihood of inaccuracies and instability. However, decreasing the time step increases the computational cost, as the simulation needs to perform more calculations per unit of time. Therefore, it's essential to strike a balance between stability and performance when choosing the time step size. By combining these techniques with substepping, you can create a physics simulation that is both robust and stable. No single technique is a silver bullet, and the optimal approach often involves a combination of methods tailored to the specific requirements of the simulation. Physics simulation is a complex field, and achieving stability can be challenging. However, by understanding the various techniques available and experimenting with different approaches, you can create realistic and reliable simulations for your projects. Remember, the key is to understand the underlying principles of physics and the limitations of computer simulations. With a solid understanding of these concepts, you can make informed decisions about how to configure your physics engine and achieve the desired level of stability and realism. Physics simulation is not just about writing code; it's about understanding the physics of the world around us and translating that knowledge into a virtual environment.

In Conclusion

Choosing the right substepping approach for your physics simulation is a balancing act. There's no one-size-fits-all answer, and the best approach depends on the specifics of your project. By understanding the trade-offs between accuracy and performance, and by experimenting with different techniques, you can create a physics simulation that's both stable and performant. So go forth and simulate, my friends, and may your objects never clip through walls again! In the realm of physics simulation, the quest for stability is an ongoing pursuit. There's no magic bullet or one-size-fits-all solution, and the ideal approach often depends on the unique characteristics of your project. The choice of substepping strategy, whether it's substepping the entire physics update or focusing on collision resolution and constraint solving, is a crucial decision that requires careful consideration. It's a balancing act between accuracy and performance, where the goal is to achieve a simulation that is both realistic and computationally feasible. Understanding the trade-offs between different approaches is essential for making informed decisions. Substepping the entire update offers the highest level of accuracy and stability but comes at a higher computational cost. Substepping only collision resolution and constraint solving provides a more performance-efficient alternative, but it might not address all potential sources of instability. Experimentation is key to finding the right balance for your project. Try different approaches, measure their performance, and analyze the results. Don't be afraid to tweak your settings and iterate until you achieve the desired outcome. Remember, physics simulation is an iterative process, and the best results often come from a combination of techniques and careful tuning. The specifics of your project will ultimately dictate the most appropriate approach. A simple simulation with few objects and interactions might not require the same level of substepping as a complex simulation with numerous objects and intricate constraints. The performance budget you have available will also influence your decision. If you're targeting a low-end device or need to maintain a high frame rate, you'll likely need to prioritize performance over accuracy. The desired level of realism is another crucial factor. If you're building a scientific simulation or a high-fidelity game, you'll likely need to prioritize accuracy and stability. However, if you're building a casual game or an application where perfect realism is not essential, you might be able to compromise on accuracy to gain performance. By carefully considering these factors and experimenting with different techniques, you can create a physics simulation that meets the specific needs of your project. Remember, physics simulation is not just about writing code; it's about understanding the underlying physics principles and applying them in a virtual environment. With a solid understanding of these principles and a willingness to experiment, you can create simulations that are both realistic and engaging. So, go forth and simulate, my friends! Embrace the challenge, experiment with different approaches, and don't be afraid to push the boundaries of what's possible. May your objects move with grace and collide with purpose, and may your simulations never again suffer the indignity of objects clipping through walls.