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= false\n\nIsAvoidingMissile = \"T\"  \nIsAvoidingMissileUrgent = \"Y\"\nIsAvoidingMissilePanic = \"G\"\nGTFO = \"H\"\nTakeControl = \"U\" \nAntiCollide = \"I\"\nAntiCollideCritical = \"J\"\n\nPanicTti  = 0.45\nUrgentTti = 1.00\t\t\t\t\nWarnedTti = 1.50\t\nLastRunTime = 0\nAvoidanceRadius = 20\nAltMin = 60\nSpeedMin = 20\nMinAltitude = 50\nMaxAltitude = 600\nPredictTime = 0.3\n\nDebugControlOutputs = true\nExampleControlVal = \"K\"\n\n\nAvoidCollisionsFriendly = false\nAvoidCollisionsEnemy = true\nAvoidCollisionsRadius = 10\t\t-- reserved area around ourselves and other craft\nAvoidanceTurnRate = 20 \t\t\t-- how quickly we turn to avoid collisions.  High values may interfere with other behaviors\nAvoidanceTimeThreshold = 0.3 \t\t-- Seconds Ahead to avoid collision\n\n\nfunction CallComplexControl(I, keyRequested)\n\n    --T G Y H U J I K O L up down left right\n\n    if keyRequested == nil then return end\n    if string.len(keyRequested) == 0 then return end\n\n    keyRequested = string.upper(keyRequested)\n\n    stim = 0\n    if     keyRequested == \"T\" then stim = 1 \n    elseif keyRequested == \"G\" then stim = 2 \n    elseif keyRequested == \"Y\" then stim = 3 \n    elseif keyRequested == \"H\" then stim = 4 \n    elseif keyRequested == \"U\" then stim = 5 \n    elseif keyRequested == \"J\" then stim = 6 \n    elseif keyRequested == \"I\" then stim = 7 \n    elseif keyRequested == \"K\" then stim = 8 \n    elseif keyRequested == \"O\" then stim = 9 \n    elseif keyRequested == \"L\" then stim = 10 \n    elseif keyRequested == \"UP\" then stim = 11 \n    elseif keyRequested == \"DOWN\" then stim = 12 \n    elseif keyRequested == \"LEFT\" then stim = 13 \n    elseif keyRequested == \"RIGHT\" then stim = 14 end\n\n    if stim > 0 then \n        I:RequestComplexControllerStimulus(stim) \n        if DebugControlOutputs then\n            I:Log(\"ComplexKey Output: \" .. keyRequested)\n        end\n    else\n        if DebugControlOutputs then\n            I:Log(\"Requested Output '\" .. keyRequested .. \"' not recognized\")\n        end\n    end\n\nend\n\n\nfunction GetNumberOfWarnings(I)      \n\t  if unexpected_condition then error() end   \n\t  return I:GetNumberOfWarnings()       \nend\n\nfunction GetMissileWarnings(I,ii)    \n\t  if unexpected_condition then error() end   \n\t  return I:GetMissileWarning(ii)\nend\n\n\nfunction Jink(I)\n\tI:Log(\"RunningJink\")\nI:Log(I:GetTime())\n\tFrameTime = I:GetTimeSinceSpawn() - LastRunTime\nI:Log(FrameTime)\nif FrameTime == 0 then return false end\n\n\tLastRunTime = I:GetTimeSinceSpawn()\n\n\n\tI:Log(LastRunTime)\nI:Log(\"Check\")\n\n\tif I:GetNumberOfTargets(0) > 0 then\n\n \t\ttargetPosInfoJink = I:GetTargetPositionInfo(0, 0)\n \t\ttargetAltitudeJink = targetPosInfo.AltitudeAboveSeaLevel\n\n\t\t\n\t\t\n\t\tif CurrPos == nil then \n\t\t\tPrevPos = I:GetConstructPosition()\n\t\t\t\n\t\telse \n\t\t\tPrevPos = CurrPos\n\t\t\t \n\t\tend\n\t\tCurrPos = I:GetConstructPosition()\n\n\n\t\t\n\t\tif CurrVel == nil then \n\t\t\tPrevVel = I:GetVelocityVector()\n\t\t\t\n\t\telse\n\t\t\tPrevVel = CurrVel\n\t\t\t\n\t\tend\n\n\t\tCurrVel = I:GetVelocityVector()\n\n\t\tAcc = (CurrVel - PrevVel) / FrameTime\nI:Log(string.format(\"Acc x:%.2f y:%.2f z:%.2f\", Acc.x, Acc.y, Acc.z))\n\n\t \ttargetPosJink = targetPosInfoJink.Position\n \t\ttargetDirJink = targetPosInfoJink.Direction\n\n\n\t\t worldDirection = CurrPos - targetPosJink\n\n\t\tif targetVelJink == nil then \nTargetPrevVel = targetPosInfoJink.Velocity\n\nelse\n\n\t\nTargetPrevVel = targetVelJink\n\t\t\t\nI:Log(string.format(\"TargetPrevVel x:%.2f y:%.2f z:%.2f\", TargetPrevVel.x, TargetPrevVel.y, TargetPrevVel.z))\n\nend\n\ntargetVelJink = targetPosInfoJink.Velocity\nI:Log(string.format(\"targetVel x:%.2f y:%.2f z:%.2f\", targetVel.x, targetVel.y, targetVel.z))\nTargetAcc = (targetVelJink - TargetPrevVel) / FrameTime\nI:Log(string.format(\"TargetAcc x:%.2f y:%.2f z:%.2f\", TargetAcc.x, TargetAcc.y, TargetAcc.z))\nTargetSpeedJink = targetVelJink.magnitude\n\t\t distance = worldDirection.magnitude\n\t\t targetDot = Vector3.Dot(targetVelJink/TargetSpeedJink, worldDirection/distance)\nTargetFuturePosition = targetPosJink + targetVelJink * PredictTime + 0.5 * TargetAcc * PredictTime ^2\nTargetFutureVel = targetVelJink + TargetAcc * PredictTime\n\n\n\t\tTargetFutureSpeed = TargetFutureVel.magnitude\n\n\t\tFuturePos_Euler = CurrPos + CurrVel * PredictTime + (Acc * PredictTime ^ 2 ) / 2\n\t\tFuturePos_Verlet = 2 * CurrPos - PrevPos + Acc * PredictTime ^ 2 \n\t\t\n\n\t\tFutureWorldDir = FuturePos_Verlet - TargetFuturePosition\n\t\tFutureDistance = FutureWorldDir.magnitude\n\n\n\t\tFutureTargetDot = Vector3.Dot(TargetFutureVel/TargetFutureSpeed, FutureWorldDir/FutureDistance)\n\n\n\n\t\t behind = targetDot < 0.25\n\t\t PointAtUs = (targetDot > 0.707) or (FutureTargetDot > 0.707)  \nI:Log(tostring(PointAtUs))\n\n\n\nif PointAtUs == true and TargetSpeedJink > SpeedMin then\n                 \n\t\t\tCallComplexControl(I, GTFO)\n                 \tI:Log(tostring(GTFO))\n                 \tI:Log(\"Jink\")\nI:LogToHud(\"Jinking\")\nend\nend\nend\n\n\nfunction AvoidCollisions(I)\n\n\tif AvoidCollisionsFsiendly == false and AvoidCollisionsEnemy == false then return false end --we do not avoid.\n\n\t--Collect some variables about myself.\n\tmyPos = I:GetConstructPosition()\n\tmyVel = I:GetVelocityVector()\n\tmySpeed = I:GetVelocityMagnitude()\n\tlocalTerrain = I:GetTerrainAltitudeForLocalPosition(0,0,0)\n\trealMinAlt = math.max(localTerrain + MinAltitude, MinAltitude)\n\tmyLowAlt = (MaxAltitude - realMinAlt)/4 + realMinAlt\n\tmyHiAlt =  MaxAltitude - (MaxAltitude - realMinAlt)/4\n\n\t--Create placeholders for craft we are about to inspect.\n\tnearestCollisionPos = Vector3(9999999,9999999,9999999)\n\tnearestTti = 9999999\n\tnearestDotTargetToMe = 0\n\tnearestDotMeToTarget = 0\n\tsource = 0\n\n\t--try and anticipate my future position along this path.\n\tmyFuturePos = I:GetConstructPosition() + (I:GetVelocityVector().normalized + I:GetVelocityVector().forward) * SpeedCurrent\n\n\t--parse a list of all friendlies and determine how likely we are to collide in the near future.\n\t--predictions are TTI based (comparing relative speed * DOT, since we don't know what direction everyone will turn in soon)\n\tif AvoidCollisionsFriendly and I:GetFriendlyCount() > 0 then\n\t\tfor ii=0,I:GetFriendlyCount()-1,1 do\n\t\t\n\t\t\ttargetPosInfo = I:GetFriendlyInfo(ii)\n\t\t\ttargetSizeVector = targetPosInfo.PositiveSize - targetPosInfo.NegativeSize\n\n\t\t\ttargetPos = targetPosInfo.CenterOfMass\n\t\t\ttargetVel = targetPosInfo.Velocity\n\n\t\t\tTargetDirection = myPos - targetPos\n\t\t\tMyDirection = targetPos - myPos\n\n\t\t\tdistance = (MyDirection.magnitude - AvoidCollisionsRadius) - targetSizeVector.magnitude\n\t\t\ttargetSpeed = targetVel.magnitude\n\t\t\t\n\t\t\ttargetDot = Vector3.Dot(targetVel.normalized, TargetDirection.normalized)\n\t\t\tmyDot = Vector3.Dot(myVel.normalized, MyDirection.normalized)\n\t\t\trelativeSpeed = (targetSpeed*targetDot + mySpeed*myDot)\n\t\t\ttti = 99999\n\t\t\t\n\t\t\tif relativeSpeed > 0 then tti = distance / relativeSpeed end\n\t\t\t\n\t\t\tif tti < nearestTti then --We record a new nearest collision threat.\n\t\t\t\tnearestCollisionPos = targetPos\n\t\t\t\tnearestTti = tti\n\t\t\t\tnearestDotTargetToMe = targetDot\n\t\t\t\tnearestDotMeToTarget = myDot\n\t\t\t\tsource = 1\n\t\t\tend\n\n\t\tend\n\tend\n\t\n\t--Do the same, but now for enemies.\n\ttargetCount = I:GetNumberOfTargets(0)\n\tif AvoidCollisionsEnemy and targetCount > 0 then\n\t\tfor ii=0,targetCount-1,1 do\n\t\t\ttargetPosInfo = I:GetTargetPositionInfo(0, ii)\n\n\t\t\ttargetPos = targetPosInfo.Position\n\t\t\ttargetVel = targetPosInfo.Velocity\n\n\t\t\tTargetDirection = myPos - targetPos\n\t\t\tMyDirection = targetPos - myPos\n\n\t\t\tdistance = (MyDirection.magnitude - AvoidCollisionsRadius*2)\n\t\t\ttargetSpeed = targetVel.magnitude\n\t\t\t\n\t\t\ttargetDot = Vector3.Dot(targetVel.normalized, TargetDirection.normalized)\n\t\t\tmyDot = Vector3.Dot(myVel.normalized, MyDirection.normalized)\n\t\t\trelativeSpeed = (targetSpeed*targetDot + mySpeed*myDot)\n\t\t\ttti = 99999\n\n\t\t\tif relativeSpeed > 0 then tti = distance / relativeSpeed end\n\n\t\t\tif tti < nearestTti then --We record a new nearest collision threat.\n\t\t\t\tnearestCollisionPos = targetPos\n\t\t\t\tnearestTti = tti\n\t\t\t\tnearestDotTargetToMe = targetDot\n\t\t\t\tnearestDotMeToTarget = myDot\n\t\t\t\tsource = 2\n\t\t\tend\n\n\t\tend\n\tend\n\n\t--now we know the most likely near future collision...\n\n\tif source == 0 or nearestTti > AvoidanceTimeThreshold or nearestCollisionPos == nil then return false end -- we found no targets worth avoiding\n\tif DebugAIMode == true and source > 0 then I:Log(string.format(\"Collision tti %.2f\", nearestTti)) end\n\n\tAvoidPosInfo = I:GetTargetPositionInfoForPosition(0, nearestCollisionPos.x,nearestCollisionPos.y,nearestCollisionPos.z)\n\n\t--if our imminent collision is less than 1/4 of our TTI threshold away, it's critical, so we will turn harder.\n\tif nearestTti < AvoidanceTimeThreshold/4 then ttiCritical = true end\n\n\tif ttiCritical then \n\t\tCallComplexControl(I, AntiCollideCritical)\n\n\tI:LogToHud(\"AvoidingCollision\")\n\t\t\n\tif DebugAIMode then\n\t\tI:Log(\"Avoiding Collision\")\n\tend\n\tif source == 1 or source == 2 then\n\t\treturn true --We're avoiding\n\telse\n\t\treturn false  --We're safe\n\tend\nend\nend \n\n\nfunction MissileAvoidance(I)\n\t\n\tmissileRan, NumberOfWarnings = pcall(GetNumberOfWarnings, I) \n\t\t\n\tif not missileRan then \n\t\n\t\tI:Log(\"Captured GetMissileWarnings Error: \" .. NumberOfWarnings)\n\t\n\treturn \n\tend\n\t\n\tif UseMissileAvoidance == false or NumberOfWarnings == 0 then return false end -- no dodge needed \n\t\n\tPanicMissilesFound = 0\n\tUrgentMissilesFound = 0\n\tWarnedMissilesFound = 0\n\t\n\tPanicMissilePos = {}\n\tUrgentMissilePos = {}\n\tWarnedMissilePos = {}\n\n\n\tmyPos = I:GetConstructPosition()\n\tmyVel = I:GetVelocityVector()\n\tmySpeed = I:GetVelocityMagnitude()\n\n\t\n\tfor ii=0,NumberOfWarnings-1,1 do\n\n\t\tmissileInfoRan, MissileInfo = pcall(GetMissileWarnings,I, ii) \n\t\t\n\t\tif not missileInfoRan  then\n\t\t\tI:Log(\"Captured GetMissileWarnings Error: \" .. MissileInfo)\n\t\tend\n\t\t\n\t\tif MissileInfo == nil then goto continue end\n\n\tif missileInfoRan then\n\t\t\tif MissileInfo.Valid then\n\t\t\t\t\n\t\t\t\ttargetPos = MissileInfo.Position\n\t\t\t\ttargetVel = MissileInfo.Velocity\n\t\t\t\t\n\t\t\t\tMissileDirection = myPos - targetPos\n\t\t\t\tMyDirection = targetPos - myPos\n\t\t\t\t\n\t\t\t\tdistance = MyDirection.magnitude - AvoidanceRadius\n\t\t\t\ttargetSpeed = targetVel.magnitude\n\t\t\t\t\n\t\t\t\ttargetDot = Vector3.Dot(targetVel.normalized, MissileDirection.normalized)\n\t\t\t\tmyDot = Vector3.Dot(myVel.normalized, MyDirection.normalized)\n\t\t\t\t\n\t\t\t\ttti = 99999\n\t\t\t\trelativeSpeed = (targetSpeed*targetDot + mySpeed*myDot)\n\t\t\t\t\n\t\t\t\tif relativeSpeed > 0 then tti = distance / relativeSpeed end\n\t\t\t\n\n\t\t\t\tif tti < PanicTti then\n\t\t\t\t\tPanicMissilesFound = PanicMissilesFound + 1\n\t\t\t\t\ttable.insert(PanicMissilePos, targetPos)\n\t\t\t\t\t\n\t\t\t\telseif tti < UrgentTti then\n\t\t\t\t\tUrgentMissilesFound = UrgentMissilesFound + 1\n\t\t\t\t\ttable.insert(UrgentMissilePos, targetPos)\n\t\t\t\t\t\n\t\t\t\telseif tti < WarnedTti then\n\t\t\t\t\tWarnedMissilesFound = WarnedMissilesFound + 1\n\t\t\t\t\ttable.insert(WarnedMissilePos, targetPos)\n\t\t\t\tend\n\t\t\t\t\n\t\t\tend\n\t\tend\n\t\t ::continue::\n\tend\n\n\tI:Log(string.format(\"MISSILES! Panic: %.0f  Urgent: %.0f Warned: %.0f Ignored: %.0f\", PanicMissilesFound, UrgentMissilesFound, WarnedMissilesFound, NumberOfWarnings - (UrgentMissilesFound + WarnedMissilesFound)))\n\t\t\t\n\tif PanicMissilesFound + WarnedMissilesFound + UrgentMissilesFound == 0 then return false end --no missiles need avoiding.\n\t\n\tI:LogToHud(string.format(\"MISSILES! Panic: %.0f  Urgent: %.0f Warned: %.0f Ignored: %.0f\", PanicMissilesFound, UrgentMissilesFound, WarnedMissilesFound, NumberOfWarnings - (UrgentMissilesFound + WarnedMissilesFound)))\n\n\t\t\n\tif PanicMissilesFound > 0 then\n\t\tCallComplexControl(I, IsAvoidingMissilePanic)\n\telseif UrgentMissilesFound > 0 then \n\t\tCallComplexControl(I, IsAvoidingMissileUrgent) \n\telseif WarnedMissilesFound > 0 then\n\t\tCallComplexControl(I, IsAvoidingMissile)\n\telse\n\tend\n\tI:Log(\"Avoiding Missile\")\n\t\n\n\n\treturn true -- we are dodging missiles\n\n\n\nend\n\n\nfunction SetCurrentValues(I)\n\t\n\t \n\n\tSpeedCurrent = I:GetVelocityMagnitude()\n\tAltitudeCurrent = math.min(I:GetConstructPosition().y, I:GetConstructPosition().y - I:GetTerrainAltitudeForLocalPosition(0,0,0))\nend\n\n\n\n\nfunction Update(I)\n\n    UpdateRan, UpdateError = pcall(SafeUpdate,I) \n    if not UpdateRan  then\n        I:ClearLogs()\n        I:Log(\"Error In Update(I): \" .. UpdateError)\n    end\nend\n\nfunction SafeUpdate(I)\n\tI:ClearLogs()\n\t\n\t--InitAI(I)\n\tSetCurrentValues(I)\n\t\n\tif MissileAvoidance(I) then return end\n\tif AvoidCollisions(I) then return end\n\tif Jink(I) then return end\n\t\nend\n"],"BlockStringDataIds":[57],"GameVersion":"3.4.2.1","PersistentSubObjectIndex":8,"PersistentBlockIndex":116,"AuthorDetails":{"Valid":true,"ForeignBlocks":0,"CreatorId":"c2a29816-cb33-4a48-b986-21ba93ad6c33","ObjectId":"a2bf94a7-6dbd-4ab6-a580-d5984ce18ddf","CreatorReadableName":"EigenFunction","HashV1":"a55551c6b290bc99dca7d10ea26b4a4d"},"BlockCount":387}}