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Top Down Stealth Toolkit

The v2.1.1 update for Top Down Stealth Toolkit has gone live on the Marketplace.

ChangeLog:

  1. Added a location-based opacity system to the Vision Arc material, thus providing the option to fade out edges of the Vision Arcs.

vafade.jpg

The hardness of the edge fading system can be controlled through the ‘OpacityMaskHardness’ variable housed within the Vision Arc Manager components. And special thanks to [USER=“4015”]Luke di Rago[/USER] for sharing the code with me.

**Note: **All changes within the blueprints are marked with the boolean variable ‘Version2.1.1’ in order to easily identify the workflow changes introduced with this update. Comments are also written to describe the major changes. The new variables, functions, interfaces, & components added to existing blueprints are also marked within their event graphs.

New post going into details about the functioning of Global Alert Level system introduced in v2.1 update: Top Down Stealth Toolkit Basics: Global Alert Level System

Added to Tutorials/Concept Overviews section as well: Top Down Stealth Toolkit - #2 by Stormrage256 - Marketplace - Unreal Engine Forums

tutorial is missing
https://unrealpossibilities.blogspot.in/2016/07/top-down-stealth-toolkit-tutorial-how.html
It displays “Sorry, the page you were looking for in this blog does not exist.”
Can you fixed that? It is very important to me…
Thank you!

The old tutorial was taken down a while back because it was based on one of the earlier versions of the toolkit. I’ve published a new tutorial on how to start out with a new level. You can check it out here: Top Down Stealth Toolkit Tutorial: How to create a new level

As mentioned in the message, all the old tutorials will be ported over to the blog & updated to the latest version over the next few days. Let me know if you need help with anything in particular.

The v2.2.1 update of Top Down Stealth Toolkit has gone live on the Marketplace.

Change Log:

  1. Added Unreal Engine v4.19 compatibility.
  2. Removed redundant segments of logic from the Enemy AI & Player Character blueprints.

Bug Fixes:

  1. Fixed an issue with Stamina Bar being displayed as empty at the start of the level.
  2. Fixed a bug associated with surveillance cameras movement in the deactivated state.
  3. Fixed an issue with turrets failing to reacquire its active target after reactivation from a disabled state.

A free gameplay demo for the v2.2.1 edition of Top Down Stealth Toolkit (Windows) is now available at: Dropbox - File Deleted

All changes within the blueprints are tagged with the boolean variable ‘Version2_2_1’ in order to easily identify the alterations made in this update. Comments are also added to describe the major changes.

The v3.2 update has gone live on the Marketplace.

Change Log:

  1. Replaced the Line of Sight Visualization system with an improved version that uses a Divide & Conquer rule to detect edges, and thus deliver vastly increased performance over the previous brute force models.

It’s using the same workflow that’s employed in my new product, Line of SIght Visualization, & hence the same integration tutorial applies here as well for adding vision cones to custom characters.

As for performance benefits, you can check out raycast & vertex count for multiple configurations in this free gameplay demo: https://www.dropbox.com/s/610m79f69e…ayDemo.7z?dl=0. I’ve also conducted some tests using a normal EQS driven brute force approach here, which like the previous visualization system requires many times more raycasts to get similar levels of edge smoothness.

I’ve submitted the v4.22 compatibility update to the Marketplace. It should be available for download within the next few days.

While there are no other major changes in this update, I did come across an issue with the footstep noise pulse emitters sometimes shifting between visible and hidden states. If anyone else is facing the same issue after converting your projects to 4.22, just make sure to add the following add vector node in your BP_PulseFXGenerator blueprint.

It will make sure that the emitter will always be just a slight bit above the ground location.

Apart from that matter, there were a few behavior tree task blueprints that were shown to have names that were too long (during packaging) despite it being less than 260 characters. Renaming the classes fixed that one. And that’s about it. The toolkit should work quite fine in 4.22 once these issues are taken care of. If anyone’s having trouble with the process, you can reach out to me through this thread or the support email id.

The v4.23 update has been submitted to the Marketplace and should be available through the launcher this coming week. I have not come across any issues upon converting the project from 4.22 to 4.23. So it’s probably safe to do it in your own projects as well. But if anyone does come across some issue, just let me know.

Edit: The 4.23 version has gone live and is now available to download from the Marketplace.

I’ve started working on the next round of updates for Top Down Stealth Toolkit, starting with a new Mouse+Keyboard driven Movement/Aiming system for the player character. It’s still a work-in-progress, but I’ve shared a preview video on Youtube:

Also just wanted to point out that the new system will not be replacing the default purely keyboard driven movement, but will instead provide an alternate form of player control system.

Hi, I’ve submitted the v3.3 update to the Marketplace. As shown in the previous video (Top Down Stealth Toolkit v3.3 WIP: Cursor-Driven Player Movement/Aiming Animations - YouTube), it adds a secondary player control system where the player character always looks at the mouse cursor while walking. I’ve added some basic interpolation to make sure that the character doesn’t immediately look at the cursor location, but instead eases into the new rotation over time. Also sprinting cancels the aiming and the character will always face the direction of the sprint.

You can switch between the new control system and the old one by heading over to the “BP_GameMode_CoreGame” blueprint, and then setting the “Default Pawn Class” to BP_PlayerCharacter_Mouse+KeyboardControl or BP_PlayerCharacter_KeyboardControl.

Edit: The update has gone live on the Marketplace. You can identify all the new changes by searching for the Version3_3 Boolean variable in blueprints.

Can’t open the project ,when update to 2.43.3! Expect auther fix it! Thank’u!

Hi, that is most certainly a result of Unreal Engine waiting for the shaders to be compiled for the first time. Just keep it running for a while and the project should open once its done. You can find more details about it here: [Solved] Unreal Editor loading stuck at 45% - #12 by TheJamsh - C++ Gameplay Programming - Unreal Engine Forums

Thank’u,I get.

Is there way to decrees visual detection chase or disable response to visual perception? For example for equipping some sort of camouflage.

Hi @Norhaji , it’s not supported by default. On paper, it’s quite easy to make the player character invisible to the AI by not registering the player as a Target Stimulus. When you do that, the AI cannot will not search for the said Stimulus. For example, in the case of your player character, it can be achieved through the following logic:

As you can see below, the Patrol Guard can no longer see the player character as long as its turned off.

However, doing so will break some other systems when the AI accidentally walks over to where the player is standing. With the visual perception unable to see the player when cloaked, even if the motion perception (used when you enter the small circular ring around an AI guard) can know that there is something close by, it will not be able to do anything without actually seeing the player using visual perception. I’ll look into it and let you know what can be done about it.

Thanks for replay. It would be nice if motion perception on invisible target would trigger working state on guards.

Alright, so I was going over the implementation and was wondering what you had in mind regarding the design behind detection of invisible targets by enemy AI. Do you want them to ‘see’ the invisible player only when in close range (within the circle)? Or is it like once the motion perception detects the player within the circle, it can temporarily keep seeing even if the player goes outside range (basically the cloak cancelling out upon detection)?

Right now I need stealth device. So disabling perception kinda works. As for system modification I see it that way.

Lets add additional parameter to visibility sense generator, np. 0-100% and divide line of sight to zones. If 100% entering line of sight equals instant detection. Lower value is, shorter instant detection range becomes with some chance to trigger investigation when target is outside instant detection zone.
If visibility would be 0% entering motion perception zone should trigger investigation with ability to detect and break stealth for X time after looking directly at target in motion perception range.

Something like this.

Alright, got it. Dividing Line of Sight into zones is definitely something that I’m planning to look into for future updates, kind of along the lines of Shadow Tactics. But since it will involve making changes to the core design (from instant detection to a delayed detection), it’s going to be a while before the feature makes it into the toolkit.

As for the cloaking system, breaking stealth seems like a feasible idea. For example, if the motion perception detects something that is right in front of it, we can have a different response when compared to how it behaves when the stimulus is behind it. And since the AI can already interact with stimuli (like reactivating stunned guards), the same workflow could be used here to interact with the cloaked actor, thus causing it to break stealth. Once that happens, the Visual Perception can kick in and do its job as usual. I’ll try it out and let you know how it goes.

Hey @Norhaji , I found a much easier solution than the above approach to have the enemy AI detect cloaked targets in close range. No need to get the Motion Perception involved at all, but instead use a sort of multi-stage Visual Perception model. Will have to do a few more tests, but if everything checks out, I’ll share a tutorial showing how you can implement it in your game.