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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 = 50\nAltMin = 60\nSpeedMin = 20\nMinAltitude = 50\nMaxAltitude = 600\nPredictTime = 0.5\n\nDebugControlOutputs = true\nExampleControlVal = \"K\"\n\n\nAvoidCollisionsFriendly = false\nAvoidCollisionsEnemy = true\nAvoidCollisionsRadius = 30\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 = 0.45 \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":[30],"GameVersion":"4.1.2.0","PersistentSubObjectIndex":8,"PersistentBlockIndex":112,"AuthorDetails":{"Valid":true,"ForeignBlocks":0,"CreatorId":"c2a29816-cb33-4a48-b986-21ba93ad6c33","ObjectId":"8472d933-8ac1-48e0-bbf1-0ea825d16eba","CreatorReadableName":"EigenFunction","HashV1":"564945700e9a2875a3475077569f373c"},"BlockCount":343}}