411 lines
10 KiB
C++
411 lines
10 KiB
C++
//========= Copyright Valve Corporation, All rights reserved. ============//
|
|
//
|
|
// Purpose:
|
|
//
|
|
// $NoKeywords: $
|
|
//=============================================================================//
|
|
|
|
#include "cbase.h"
|
|
|
|
#include "ai_movesolver.h"
|
|
#include "ndebugoverlay.h"
|
|
|
|
// memdbgon must be the last include file in a .cpp file!!!
|
|
#include "tier0/memdbgon.h"
|
|
|
|
//-----------------------------------------------------------------------------
|
|
|
|
inline float V_round( float f )
|
|
{
|
|
return (float)( (int)( f + 0.5 ) );
|
|
}
|
|
|
|
//-----------------------------------------------------------------------------
|
|
// CAI_MoveSolver
|
|
//-----------------------------------------------------------------------------
|
|
|
|
// The epsilon used by the solver
|
|
const float AIMS_EPS = 0.01;
|
|
|
|
|
|
//-----------------------------------------------------------------------------
|
|
// Visualization
|
|
//-----------------------------------------------------------------------------
|
|
void CAI_MoveSolver::VisualizeRegulations( const Vector& origin )
|
|
{
|
|
if ( m_Regulations.Count() )
|
|
{
|
|
CAI_MoveSuggestions regulations;
|
|
regulations.AddVectorToTail( m_Regulations );
|
|
NormalizeSuggestions( ®ulations[0], (®ulations[0]) + regulations.Count() );
|
|
|
|
Vector side1, mid, side2;
|
|
for (int i = regulations.Count(); --i >= 0; )
|
|
{
|
|
// Compute the positions of the angles...
|
|
float flMinAngle = regulations[i].arc.center - regulations[i].arc.span * 0.5f;
|
|
float flMaxAngle = regulations[i].arc.center + regulations[i].arc.span * 0.5f;
|
|
|
|
side1 = UTIL_YawToVector( flMinAngle );
|
|
side2 = UTIL_YawToVector( flMaxAngle );
|
|
mid = UTIL_YawToVector( regulations[i].arc.center );
|
|
|
|
// Stronger weighted ones are bigger
|
|
if ( regulations[i].weight < 0 )
|
|
{
|
|
float flLength = 10 + 40 * ( regulations[i].weight * -1.0);
|
|
side1 *= flLength;
|
|
side2 *= flLength;
|
|
mid *= flLength;
|
|
|
|
side1 += origin;
|
|
side2 += origin;
|
|
mid += origin;
|
|
|
|
NDebugOverlay::Triangle(origin, mid, side1, 255, 0, 0, 48, true, 0.1f );
|
|
NDebugOverlay::Triangle(origin, side2, mid, 255, 0, 0, 48, true, 0.1f );
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
//-------------------------------------
|
|
// Purpose: The actual solver function. Reweights according to type and sums
|
|
// all the suggestions, identifying the best.
|
|
//-------------------------------------
|
|
bool CAI_MoveSolver::Solve( const AI_MoveSuggestion_t *pSuggestions, int nSuggestions, AI_MoveSolution_t *pResult)
|
|
{
|
|
//---------------------------------
|
|
//
|
|
// Quick out
|
|
//
|
|
if ( !nSuggestions )
|
|
return false;
|
|
|
|
if ( nSuggestions == 1 && m_Regulations.Count() == 0 && pSuggestions->type == AIMST_MOVE )
|
|
{
|
|
pResult->dir = pSuggestions->arc.center;
|
|
return true;
|
|
}
|
|
|
|
//---------------------------------
|
|
//
|
|
// Setup
|
|
//
|
|
CAI_MoveSuggestions suggestions;
|
|
|
|
suggestions.EnsureCapacity( m_Regulations.Count() + nSuggestions );
|
|
|
|
suggestions.CopyArray( pSuggestions, nSuggestions);
|
|
suggestions.AddVectorToTail( m_Regulations );
|
|
|
|
// Initialize the solver
|
|
const int NUM_SOLUTIONS = 120;
|
|
const int SOLUTION_ANG = 360 / NUM_SOLUTIONS;
|
|
|
|
COMPILE_TIME_ASSERT( ( 360 % NUM_SOLUTIONS ) == 0 );
|
|
|
|
struct Solution_t
|
|
{
|
|
// The sum bias
|
|
float bias;
|
|
float highBias;
|
|
AI_MoveSuggestion_t *pHighSuggestion;
|
|
};
|
|
|
|
Solution_t solutions[NUM_SOLUTIONS] = { { 0, 0, NULL } };
|
|
|
|
//---------------------------------
|
|
|
|
// The first thing we do is reweight and normalize the weights into a range of [-1..1], where
|
|
// a negative weight is a repulsion. This becomes a bias for the solver.
|
|
// @TODO (toml 06-18-02): this can be made sligtly more optimal by precalculating regulation adjusted weights
|
|
Assert( suggestions.Count() >= 1 );
|
|
NormalizeSuggestions( &suggestions[0], (&suggestions[0]) + suggestions.Count() );
|
|
|
|
//
|
|
// Add the biased suggestions to the solutions
|
|
//
|
|
for ( int iSuggestion = 0; iSuggestion < suggestions.Count(); ++iSuggestion )
|
|
{
|
|
AI_MoveSuggestion_t ¤t = suggestions[iSuggestion];
|
|
|
|
// Convert arc values to solution indices relative to right post. Right is angle down, left is angle up.
|
|
float halfSpan = current.arc.span * 0.5;
|
|
int center = V_round( ( halfSpan * NUM_SOLUTIONS ) / 360 );
|
|
int left = ( current.arc.span * NUM_SOLUTIONS ) / 360;
|
|
|
|
float angRight = current.arc.center - halfSpan;
|
|
|
|
if (angRight < 0.0)
|
|
angRight += 360;
|
|
|
|
int base = ( angRight * NUM_SOLUTIONS ) / 360;
|
|
|
|
// Sweep from left to right, summing the bias. For positive suggestions,
|
|
// the bias is further weighted to favor the center of the arc.
|
|
const float positiveDegradePer180 = 0.05; // i.e., lose 5% of weight by the time hit 180 degrees off center
|
|
const float positiveDegrade = ( positiveDegradePer180 / ( NUM_SOLUTIONS * 0.5 ) );
|
|
|
|
for ( int i = 0; i < left + 1; ++i )
|
|
{
|
|
float bias = 0.0;
|
|
|
|
if ( current.weight > 0)
|
|
{
|
|
int iOffset = center - i;
|
|
float degrade = abs( iOffset ) * positiveDegrade;
|
|
|
|
if ( ( (current.flags & AIMS_FAVOR_LEFT ) && i > center ) ||
|
|
( (current.flags & AIMS_FAVOR_RIGHT) && i < center ) )
|
|
{
|
|
degrade *= 0.9;
|
|
}
|
|
|
|
bias = current.weight - ( current.weight * degrade );
|
|
}
|
|
else
|
|
bias = current.weight;
|
|
|
|
int iCurSolution = (base + i) % NUM_SOLUTIONS;
|
|
|
|
solutions[iCurSolution].bias += bias;
|
|
if ( bias > solutions[iCurSolution].highBias )
|
|
{
|
|
solutions[iCurSolution].highBias = bias;
|
|
solutions[iCurSolution].pHighSuggestion = ¤t;
|
|
}
|
|
}
|
|
}
|
|
|
|
//
|
|
// Find the best solution
|
|
//
|
|
int best = -1;
|
|
float biasBest = 0;
|
|
|
|
for ( int i = 0; i < NUM_SOLUTIONS; ++i )
|
|
{
|
|
if ( solutions[i].bias > biasBest )
|
|
{
|
|
best = i;
|
|
biasBest = solutions[i].bias;
|
|
}
|
|
}
|
|
|
|
if ( best == -1 )
|
|
return false; // no solution
|
|
|
|
//
|
|
// Construct the results
|
|
//
|
|
float result = best * SOLUTION_ANG;
|
|
|
|
// If the matching suggestion is within the solution, use that as the result,
|
|
// as it is valid and more precise.
|
|
const float suggestionCenter = solutions[best].pHighSuggestion->arc.center;
|
|
|
|
if ( suggestionCenter > result && suggestionCenter <= result + SOLUTION_ANG )
|
|
result = suggestionCenter;
|
|
|
|
pResult->dir = result;
|
|
|
|
return true;
|
|
}
|
|
|
|
//-------------------------------------
|
|
// Purpose: Adjusts the suggestion weights according to the type of the suggestion,
|
|
// apply the appropriate sign, ensure values are in expected ranges
|
|
//-------------------------------------
|
|
|
|
struct AI_MoveSuggWeights
|
|
{
|
|
float min;
|
|
float max;
|
|
};
|
|
|
|
static AI_MoveSuggWeights g_AI_MoveSuggWeights[] = // @TODO (toml 06-18-02): these numbers need tuning
|
|
{
|
|
{ 0.20, 1.00 }, // AIMST_MOVE
|
|
{ -0.00, -0.25 }, // AIMST_AVOID_DANGER
|
|
{ -0.00, -0.25 }, // AIMST_AVOID_OBJECT
|
|
{ -0.00, -0.25 }, // AIMST_AVOID_NPC
|
|
{ -0.00, -0.25 }, // AIMST_AVOID_WORLD
|
|
{ -1.00, -1.00 }, // AIMST_NO_KNOWLEDGE
|
|
{ -0.60, -0.60 }, // AIMST_OSCILLATION_DETERRANCE
|
|
{ 0.00, 0.00 }, // AIMST_INVALID
|
|
};
|
|
|
|
void CAI_MoveSolver::NormalizeSuggestions( AI_MoveSuggestion_t *pBegin, AI_MoveSuggestion_t *pEnd )
|
|
{
|
|
while ( pBegin != pEnd )
|
|
{
|
|
const float min = g_AI_MoveSuggWeights[pBegin->type].min;
|
|
const float max = g_AI_MoveSuggWeights[pBegin->type].max;
|
|
|
|
Assert( pBegin->weight >= -AIMS_EPS && pBegin->weight <= 1.0 + AIMS_EPS );
|
|
|
|
if ( pBegin->weight < AIMS_EPS ) // zero normalizes to zero
|
|
pBegin->weight = 0.0;
|
|
else
|
|
pBegin->weight = ( ( max - min ) * pBegin->weight ) + min;
|
|
|
|
while (pBegin->arc.center < 0)
|
|
pBegin->arc.center += 360;
|
|
|
|
while (pBegin->arc.center >= 360)
|
|
pBegin->arc.center -= 360;
|
|
|
|
++pBegin;
|
|
}
|
|
}
|
|
|
|
//-------------------------------------
|
|
|
|
bool CAI_MoveSolver::HaveRegulationForObstacle( CBaseEntity *pEntity)
|
|
{
|
|
for ( int i = 0; i < m_Regulations.Count(); ++i )
|
|
{
|
|
if ( m_Regulations[i].hObstacleEntity != NULL &&
|
|
pEntity == m_Regulations[i].hObstacleEntity.Get() )
|
|
{
|
|
return true;
|
|
}
|
|
}
|
|
return false;
|
|
}
|
|
|
|
//-----------------------------------------------------------------------------
|
|
//
|
|
// Commands and tests
|
|
//
|
|
|
|
#ifdef DEBUG
|
|
CON_COMMAND(ai_test_move_solver, "Tests the AI move solver system")
|
|
{
|
|
#ifdef DEBUG
|
|
const float EPS = 0.001;
|
|
#endif
|
|
DevMsg( "Beginning move solver tests...\n" );
|
|
|
|
CAI_MoveSolver solver;
|
|
AI_MoveSolution_t solution;
|
|
int i;
|
|
|
|
//
|
|
// Value in, no regulations, should yield value out
|
|
//
|
|
{
|
|
DevMsg( "Simple... " );
|
|
|
|
for (i = 0; i < 360; ++i)
|
|
{
|
|
Assert( solver.Solve( AI_MoveSuggestion_t( AIMST_MOVE, 1, i, 180 ), &solution ) );
|
|
Assert( solution.dir == (float)i );
|
|
|
|
}
|
|
|
|
DevMsg( "pass.\n" );
|
|
solver.ClearRegulations();
|
|
}
|
|
|
|
//
|
|
// Two values in, should yield the first
|
|
//
|
|
{
|
|
DevMsg( "Two positive... " );
|
|
|
|
AI_MoveSuggestion_t suggestions[2];
|
|
|
|
suggestions[0].Set( AIMST_MOVE, 1.0, 180, 100 );
|
|
suggestions[1].Set( AIMST_MOVE, 0.5, 0, 100 );
|
|
|
|
Assert( solver.Solve( suggestions, 2, &solution ) );
|
|
Assert( solution.dir == (float)suggestions[0].arc.center );
|
|
|
|
|
|
DevMsg( "pass.\n" );
|
|
solver.ClearRegulations();
|
|
}
|
|
|
|
//
|
|
// Two values in, first regulated, should yield the second
|
|
//
|
|
{
|
|
DevMsg( "Avoid one of two... " );
|
|
|
|
AI_MoveSuggestion_t suggestions[2];
|
|
|
|
solver.AddRegulation(AI_MoveSuggestion_t( AIMST_AVOID_OBJECT, 1, 260, 60 ) );
|
|
|
|
suggestions[0].Set( AIMST_MOVE, 1.0, 270, 45 );
|
|
suggestions[1].Set( AIMST_MOVE, 1.0, 0, 45 );
|
|
|
|
Assert( solver.Solve( suggestions, 2, &solution ) );
|
|
Assert( solution.dir == (float)suggestions[1].arc.center );
|
|
|
|
|
|
DevMsg( "pass.\n" );
|
|
solver.ClearRegulations();
|
|
}
|
|
|
|
//
|
|
// No solution
|
|
//
|
|
{
|
|
DevMsg( "No solution... " );
|
|
|
|
AI_MoveSuggestion_t suggestions[2];
|
|
|
|
suggestions[0].Set( AIMST_MOVE, 1.0, 270, 90 );
|
|
suggestions[1].Set( AIMST_AVOID_OBJECT, 1.0, 260, 180 );
|
|
|
|
Assert( !solver.Solve( suggestions, 2, &solution ) );
|
|
|
|
DevMsg( "pass.\n" );
|
|
solver.ClearRegulations();
|
|
}
|
|
|
|
//
|
|
// Nearest solution, in tolerance
|
|
//
|
|
{
|
|
DevMsg( "Nearest solution, in tolerance... " );
|
|
|
|
AI_MoveSuggestion_t suggestions[2];
|
|
|
|
suggestions[0].Set( AIMST_MOVE, 1.0, 278, 90 );
|
|
suggestions[1].Set( AIMST_AVOID_OBJECT, 1.0, 260, 24 );
|
|
|
|
Assert( solver.Solve( suggestions, 2, &solution ) );
|
|
Assert( solution.dir == (float)suggestions[0].arc.center );
|
|
|
|
DevMsg( "pass.\n" );
|
|
solver.ClearRegulations();
|
|
}
|
|
|
|
//
|
|
// Nearest solution
|
|
//
|
|
{
|
|
DevMsg( "Nearest solution... " );
|
|
|
|
AI_MoveSuggestion_t suggestions[2];
|
|
|
|
suggestions[0].Set( AIMST_MOVE, 1.0, 270, 90 );
|
|
suggestions[1].Set( AIMST_AVOID_OBJECT, 1.0, 260, 40 );
|
|
|
|
Assert( solver.Solve( suggestions, 2, &solution ) );
|
|
Assert( solution.dir - 282 < EPS ); // given 60 solutions
|
|
|
|
DevMsg( "pass.\n" );
|
|
solver.ClearRegulations();
|
|
}
|
|
|
|
}
|
|
#endif
|
|
|
|
//=============================================================================
|
|
|