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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":[43],"GameVersion":"3.9.2.5","PersistentSubObjectIndex":8,"PersistentBlockIndex":197,"AuthorDetails":{"Valid":true,"ForeignBlocks":0,"CreatorId":"c2a29816-cb33-4a48-b986-21ba93ad6c33","ObjectId":"3bae1140-d0f3-4b53-a305-88cac9c5d2f0","CreatorReadableName":"EigenFunction","HashV1":"4d34d27092abf396793c8d9fe2f9e828"},"BlockCount":276}}