![]() ![]() Also I had to turn off some velocity clamping. I reduced the iteration count and used a large time step (30 Hertz) to show the effect well. I made a recording of the discrete and predictive prismatic joint solvers in Box2D. This works particularly well for some joint limits. So predictive constraints are proactive and try to anticipate constraint violations before they happen. ![]() This is necessary because the velocity constraint value can flip signs in the middle of the solver iterations. The downside is that I need two constraints: a lower limit constraint and an upper limit constraint. It even simplifies the solver because I don't need to track the limit state for the velocity solver. This is a very cheap modification to the joint limit solver and it has very nice results. ![]() The time step is \(\Delta t\) and the velocity constraint value is \(\dot\] We can use this formula to compute the new position constraint value based on the current position constraint value and the velocity constraint value: In the case of the prismatic joint the position constraint for the lower limit is: C = translation - lower_limit First we have the position constraint \(C\). Here is some math that shows how to use predictive limits. In that case I can apply an impulse so that the limit is reached but not exceeded. Based on the current position and velocities, I can determine if the limit would be violated once the positions are updated. However, suppose body velocities are such that the gap is closing. This is the position constraint \(C\), but in this case the constraint is not being violated yet. The idea is to measure the gap between the current position and the limit. To calculate how much time is needed to reach a given velocity v': t ln(v' / v) / (-d) Using the parameters from the question: t ln(1 / 10) / (-0.5) 4.605 The object needs 4,6 seconds to decelerate from 10 m/s to 1 m/s. Is there a simpler solution? We can draw inspiration from "A Different Approach for Continuous Physics" by Vincent Robert. Admittedly, this is also quite complicated for continuous collision. However, this is quite complicated, especially if there are multiple joints and multiple bodies involved. It might be possible to compute the time of impact of the joint on a limit and then use sub-stepping. Discrete simulation is reactive and it is alway trying to catch up to all the mistakes that have been made (kind of like my life at times). The reason this happens is because with discrete simulation the solver doesn't consider the joint limit until it is violated. However, with fast movement the drawer can temporarily end up in a bad state. A lower and upper limit can be set on a prismatic joint to keep the drawer from going in too deep or pulling out too far. For example, consider a filing cabinet where the drawers use prismatic (slider) joints. Joint limits can also suffer from fast movement. There are other artifacts due to discrete time steps. The Box2D continuous collision algorithm uses a time of impact (TOI) collision algorithm along with time sub-stepping for the response. This solves the problem of fast moving objects passing through each other due to discrete time steps. SetReferencePoint(display.Box2D has support for continuous collision. ![]() If anyone wants to continue working on those projects may do so freely.Īudio.fade ( [ ) Gideros Mobile - A 2D mobile development environment and game engine for. I still think CoronaSDK is an good alternative but simply, it’s not suited for us anymore…ītw, following CoronaSDK projects maintained by us will be discontinued as well. iOS port is written in Objective-C and integrated with Box2D and Chipmunk.
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