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+# CONFIGURATION, WORKFLOWS & IMPLEMENTATION GUIDE
+
+**Document:** Part 5 of Robot Tuning System Architecture  
+**Coverage:** Default configurations, tuning workflows, implementation phases, and testing strategy
+
+---
+
+## DEFAULT CONFIGURATIONS
+
+All default values with detailed justifications.
+
+---
+
+### 1. Robot Physical Configuration
+
+```csharp
+public static class DefaultConfigurations
+{
+    public static RobotPhysicalConfig Physical => new()
+    {
+        // Wheelbase: Distance between left and right wheels
+        // Typical for small indoor robot: 0.3-0.5m
+        // Affects: Turning radius, stability
+        Wheelbase = 0.35f,  // meters
+        
+        // Wheel radius: Affects odometry calculations
+        // Typical: 0.05-0.1m for small robots
+        WheelRadius = 0.075f,  // meters
+        
+        // Max linear velocity: User-specified
+        MaxLinearVelocity = 1.5f,  // m/s
+        
+        // Max angular velocity: Calculated from max linear velocity
+        // ω_max ≈ 2 * v_max / wheelbase
+        // Conservative estimate: 2 * 1.5 / 0.35 ≈ 8.57 rad/s
+        // Use 6 rad/s for safety margin (~343°/s)
+        MaxAngularVelocity = 6.0f,  // rad/s
+        
+        // Max linear acceleration: For smooth motion
+        // 1.0 m/s² means 0 → 1.5 m/s in 1.5 seconds
+        // Typical range: 0.5-2.0 m/s²
+        MaxLinearAcceleration = 1.0f,  // m/s²
+        
+        // Max angular acceleration: User-specified
+        MaxAngularAcceleration = 1.0f,  // rad/s²
+        
+        // Robot mass: Estimated for small mobile robot
+        Mass = 25.0f  // kg
+    };
+}
+```
+
+---
+
+### 2. Control Timing Configuration
+
+```csharp
+public static ControlTimingConfig Timing => new()
+{
+    // Control loop frequency: 50Hz (20ms per cycle)
+    // Justification:
+    // - 10Hz: Too slow, robot will oscillate
+    // - 50Hz: Optimal for indoor navigation (balance performance/CPU)
+    // - 100Hz: Better but requires more CPU, marginal gains
+    // - 200Hz+: Overkill for this application
+    ControlLoopFrequency = 50,  // Hz
+    
+    // Encoder sampling: Match or exceed control frequency
+    EncoderSamplingRate = 50,  // Hz
+    
+    // Motor command rate: Match control frequency
+    MotorCommandRate = 50  // Hz
+};
+```
+
+---
+
+### 3. PID Controller Configuration
+
+```csharp
+public static VelocityPIDConfig PID => new()
+{
+    // Kp: Proportional gain
+    // Higher Kp = faster response but more overshoot
+    // Starting point: 0.8 (moderate response)
+    // Tuning range: 0.1-5.0
+    Kp = 0.8f,
+    
+    // Ki: Integral gain
+    // Eliminates steady-state error
+    // Keep small to avoid windup
+    // Starting point: 0.1
+    // Tuning range: 0.0-2.0
+    Ki = 0.1f,
+    
+    // Kd: Derivative gain
+    // Dampens oscillations, smooths response
+    // Starting point: 0.05 (gentle damping)
+    // Tuning range: 0.0-1.0
+    Kd = 0.05f,
+    
+    // Velocity limits
+    MaxVelocity = 1.5f,  // m/s (from physical config)
+    MinVelocity = 0.1f,  // m/s (minimum for robot to move)
+    
+    // Anti-windup: Prevent integral term from growing unbounded
+    IntegralWindupLimit = 0.5f,  // m/s
+    
+    // Output saturation: Ensure output stays within limits
+    OutputSaturationEnabled = true
+};
+```
+
+**PID Tuning Guidelines:**
+- Start with Kp only (Ki=0, Kd=0), increase until oscillation
+- Reduce Kp to 60% of oscillation value
+- Add Kd to dampen remaining oscillation
+- Add Ki last, only if steady-state error exists
+
+---
+
+### 4. Velocity Estimator Configuration
+
+```csharp
+public static VelocityEstimatorConfig Estimator => new()
+{
+    // Alpha filter: Exponential moving average for encoder
+    // Lower α (0.1-0.2): More filtering, more lag
+    // Higher α (0.3-0.4): Less filtering, more responsive
+    // Recommended: 0.3 for balance
+    AlphaFilter = 0.3f,
+    
+    // Blend ratio bounds
+    MinBlendRatio = 0.15f,  // Min 15% model, 85% encoder
+    MaxBlendRatio = 0.8f,   // Max 80% model, 20% encoder
+    DefaultBlendRatio = 0.6f,  // Start with 60% model
+    
+    // Adaptive blending thresholds
+    GoodTrackingThreshold = 0.12f,  // < 12% error
+    ModerateTrackingThreshold = 0.3f,  // < 30% error
+    
+    // CORRECTED blend ratios (based on architecture review):
+    // Good tracking → trust encoder more (model prediction matches reality)
+    GoodTrackingBlend = 0.3f,  // 30% model, 70% encoder
+    
+    // Moderate tracking → balanced
+    ModerateTrackingBlend = 0.5f,  // 50-50 blend
+    
+    // Poor tracking → trust model more (encoder may have slip)
+    PoorTrackingBlend = 0.7f,  // 70% model, 30% encoder
+    
+    // Confidence decay: How fast confidence drops
+    // 0.98 = slow decay (1% per cycle at 50Hz = ~2s to halve)
+    // 0.95 = medium decay
+    // 0.90 = fast decay
+    ConfidenceDecayRate = 0.98f,
+    
+    // Minimum confidence floor
+    MinConfidence = 0.3f  // Never go below 30%
+};
+```
+
+---
+
+### 5. Pure Pursuit Configuration
+
+```csharp
+public static PurePursuitConfig PurePursuit => new()
+{
+    // Lookahead minimum: Smallest lookahead distance
+    // Too small: Oscillation, overshoot corners
+    // Too large: Cuts corners, poor tracking
+    // Recommended: 0.2-0.4m for indoor robot
+    LookaheadMin = 0.3f,  // meters
+    
+    // Kdd: Lookahead velocity scaling factor
+    // lookahead = LookaheadMin + Kdd * |velocity|
+    // Kdd = 1.0 means 1 second lookahead time
+    // Kdd = 0.5 means 0.5 second lookahead
+    // Recommended: 0.8-1.5
+    Kdd = 1.0f,  // seconds
+    
+    // Lookahead maximum: Cap lookahead distance
+    // Prevents looking too far ahead at high speeds
+    // Recommended: 1.5-3.0m
+    LookaheadMax = 2.0f  // meters
+};
+```
+
+**Pure Pursuit Tuning Guidelines:**
+- Increase Kdd for smoother, more predictive tracking
+- Decrease Kdd for tighter, more reactive tracking
+- Increase LookaheadMin if robot oscillates
+- Decrease LookaheadMin if robot cuts corners
+
+---
+
+### 6. Path Following Configuration
+
+```csharp
+public static PathFollowingConfig PathFollowing => new()
+{
+    // Waypoint tolerance: How close to consider waypoint "reached"
+    WaypointTolerance = 0.15f,  // 15cm
+    
+    // Final goal tolerance: Tighter tolerance for final goal
+    FinalGoalTolerance = 0.05f,  // 5cm
+    
+    // Goal heading tolerance: Acceptable heading error at goal
+    GoalHeadingTolerance = 5f * MathF.PI / 180f,  // 5 degrees
+    
+    // Stop distance: When to start preparing to stop
+    StopDistance = 0.1f,  // 10cm before goal
+    
+    // Stop velocity: Threshold to consider robot "stopped"
+    StopVelocity = 0.05f  // 5cm/s
+};
+```
+
+---
+
+### 7. Safety Configuration
+
+```csharp
+public static SafetyConfig Safety => new()
+{
+    // Max cross-track error before abort
+    // 0.5m is reasonable for 10x20m indoor space
+    MaxCrossTrackError = 0.5f,  // meters
+    
+    // Max heading error before abort
+    // 45° means robot is severely off course
+    MaxHeadingError = 45f * MathF.PI / 180f,  // radians
+    
+    // Sustained error duration before abort
+    // 3 seconds allows recovery from temporary issues
+    MaxTrackingErrorDuration = 3000,  // milliseconds
+    
+    // Obstacle safety distances (for future sensors)
+    MinObstacleDistance = 0.3f,  // 30cm emergency stop
+    SafetyStopDistance = 0.5f,   // 50cm slow down
+    
+    // Emergency deceleration limit
+    EmergencyStopDeceleration = 2.0f  // m/s²
+};
+```
+
+---
+
+### 8. Acceptance Criteria Configuration
+
+```csharp
+public static AcceptanceCriteria Criteria => new()
+{
+    // PRIMARY: Tracking Accuracy (50% weight)
+    // Cross-track error RMS: 10cm is good for indoor robot
+    MaxCrossTrackErrorRMS = 0.10f,  // meters
+    
+    // Peak CTE: Allow double RMS as occasional spike
+    MaxCrossTrackErrorPeak = 0.20f,  // meters
+    
+    // Heading error: 10° RMS is acceptable
+    MaxHeadingErrorRMS = 10f * MathF.PI / 180f,  // radians
+    
+    // Goal position error: 5cm final accuracy
+    MaxGoalPositionError = 0.05f,  // meters
+    
+    // Goal heading error: 5° final accuracy
+    MaxGoalHeadingError = 5f * MathF.PI / 180f,  // radians
+    
+    // SECONDARY: Smoothness (30% weight)
+    // Max jerk: 5 m/s³ is smooth for human comfort
+    MaxJerk = 5.0f,  // m/s³
+    
+    // Max angular jerk: 10 rad/s³
+    MaxAngularJerk = 10.0f,  // rad/s³
+    
+    // TERTIARY: Efficiency (20% weight)
+    // Path length ratio: <15% deviation from optimal
+    MaxPathLengthRatio = 1.15f,  // 115% of optimal
+    
+    // Success rate: 90% of runs should pass
+    MinSuccessRate = 0.90f  // 90%
+};
+```
+
+---
+
+### 9. Scoring Weights
+
+```csharp
+public static ScoringWeights Weights => new()
+{
+    // How much each category contributes to overall score
+    TrackingAccuracy = 0.5f,  // 50%
+    Smoothness = 0.3f,        // 30%
+    Efficiency = 0.2f         // 20%
+};
+```
+
+---
+
+### 10. Parameter Bounds
+
+```csharp
+public static class ParameterBounds
+{
+    // PID bounds
+    public static Range KpRange = new(0.1f, 5.0f);
+    public static Range KiRange = new(0.0f, 2.0f);
+    public static Range KdRange = new(0.0f, 1.0f);
+    
+    // Estimator bounds
+    public static Range AlphaFilterRange = new(0.05f, 0.5f);
+    public static Range BlendRatioRange = new(0.1f, 0.9f);
+    public static Range ConfidenceDecayRange = new(0.90f, 0.99f);
+    
+    // Pure Pursuit bounds
+    public static Range KddRange = new(0.3f, 2.0f);
+    public static Range LookaheadMinRange = new(0.1f, 0.5f);
+    public static Range LookaheadMaxRange = new(0.5f, 3.0f);
+    
+    // Validation rules
+    public static List<ValidationRule> Rules => new()
+    {
+        new ValidationRule
+        {
+            Name = "LookaheadOrdering",
+            Check = (p) => p.PurePursuit.LookaheadMax > p.PurePursuit.LookaheadMin,
+            Message = "LookaheadMax must be greater than LookaheadMin"
+        },
+        new ValidationRule
+        {
+            Name = "BlendRatioOrdering",
+            Check = (p) => p.Estimator.GoodTrackingBlend <= p.Estimator.PoorTrackingBlend,
+            Message = "GoodTrackingBlend should be less than PoorTrackingBlend"
+        },
+        new ValidationRule
+        {
+            Name = "VelocityLimit",
+            Check = (p) => p.PID.MaxVelocity <= p.Physical.MaxLinearVelocity,
+            Message = "PID MaxVelocity cannot exceed physical limit"
+        }
+    };
+}
+```
+
+---
+
+## TUNING WORKFLOWS
+
+Detailed step-by-step workflows for different tuning scenarios.
+
+---
+
+### Workflow 1: Quick Start (First-Time User)
+
+**Goal:** Get robot moving with default settings and validate basic functionality.
+
+**Steps:**
+
+1. **Load Default Configuration** (5 min)
+   - Open dashboard
+   - Navigate to Configuration → Robot Settings
+   - Verify physical parameters (wheelbase, wheel radius)
+   - Click "Load Default Preset"
+
+2. **Run Baseline Test** (2 min)
+   - Select Test Scenario: "Straight Line 10m"
+   - Click "Run Test"
+   - Observe real-time visualization
+   - Wait for completion
+
+3. **Review Results** (3 min)
+   - Check overall score
+   - Identify which metrics fail (if any)
+   - Note: CTE RMS, jerk, smoothness
+
+4. **Decision Point:**
+   - Score > 80: Proceed to Workflow 2 (test other trajectories)
+   - Score 60-80: Proceed to Workflow 3 (manual tuning)
+   - Score < 60: Check robot hardware, retry
+
+**Expected Outcome:** Baseline performance established, ready for tuning.
+
+---
+
+### Workflow 2: Multi-Scenario Validation
+
+**Goal:** Test current configuration across all trajectory types.
+
+**Steps:**
+
+1. **Setup Batch Test** (2 min)
+   - Navigate to Tuning → Parameter Comparison
+   - Select all scenarios:
+     - Straight Line 10m
+     - Circle 2m Radius
+     - Circle 0.5m Radius
+   - Select current parameter set
+   - Click "Run Batch"
+
+2. **Monitor Progress** (10-15 min)
+   - Watch each test in sequence
+   - Note any failures or safety violations
+
+3. **Analyze Comparison** (5 min)
+   - View comparison table
+   - Identify weakest scenario
+   - Check metric breakdown per scenario
+
+4. **Decision Point:**
+   - All scenarios pass: Configuration is robust
+   - One scenario fails: Tune for that specific case
+   - Multiple scenarios fail: Need general tuning (Workflow 3)
+
+---
+
+### Workflow 3: Manual Iterative Tuning
+
+**Goal:** Hand-tune parameters to improve specific metrics.
+
+**Steps:**
+
+**Phase 1: Improve Tracking Accuracy (if CTE RMS > 0.10m)**
+
+1. **Diagnose Issue:**
+   - View trajectory plot
+   - Check if robot overshoots or undershoots corners
+   - Check if error is consistent or oscillating
+
+2. **If Robot Overshoots (cuts corners):**
+   - Decrease Pure Pursuit LookaheadMin: 0.3 → 0.25
+   - Decrease Kdd: 1.0 → 0.8
+   - Run test, check improvement
+
+3. **If Robot Undershoots (goes wide):**
+   - Increase Pure Pursuit LookaheadMin: 0.3 → 0.35
+   - Increase Kdd: 1.0 → 1.2
+   - Run test, check improvement
+
+4. **If Robot Oscillates:**
+   - Increase PID Kd: 0.05 → 0.15 (more damping)
+   - Increase Estimator AlphaFilter: 0.3 → 0.4 (more smoothing)
+   - Run test, check improvement
+
+5. **If Robot is Sluggish:**
+   - Increase PID Kp: 0.8 → 1.2 (faster response)
+   - Run test, check for overshoot
+
+**Phase 2: Improve Smoothness (if Jerk > 5.0 m/s³)**
+
+1. **Increase Damping:**
+   - Increase PID Kd: current → +0.1
+   - Run test
+
+2. **Smooth Velocity Estimates:**
+   - Decrease Estimator AlphaFilter: 0.3 → 0.2
+   - Run test
+
+3. **Reduce Aggressiveness:**
+   - Decrease PID Kp: current → -0.2
+   - Run test
+
+**Phase 3: Verify and Save**
+
+1. **Run Full Validation:**
+   - Test all scenarios with new parameters
+   - Ensure no regressions
+
+2. **Save Configuration:**
+   - Name: "Tuned_[Date]_v1"
+   - Add description of changes
+   - Click "Save"
+
+**Iteration:** Repeat phases as needed, aiming for <5 iterations.
+
+---
+
+### Workflow 4: Automated Optimization (Advanced)
+
+**Goal:** Use algorithm to find optimal parameters automatically.
+
+**Steps:**
+
+1. **Configure Optimization** (5 min)
+   - Navigate to Tuning → Auto Tuning
+   - Select algorithm: Bayesian Optimization
+   - Select parameters to tune:
+     - ☑ PID: Kp, Ki, Kd
+     - ☑ Pure Pursuit: Kdd
+     - ☐ Estimator: (keep fixed for first run)
+   - Set constraints:
+     - Max iterations: 30
+     - Early stopping: 1% improvement threshold
+
+2. **Define Objective** (2 min)
+   - Primary metric: Cross-Track Error RMS
+   - Secondary metric: Max Jerk (weight: 0.3)
+   - Test scenario: Circle 2m Radius
+
+3. **Start Optimization** (30-60 min)
+   - Click "Start Optimization"
+   - Monitor progress dashboard
+   - View live updates of best parameters found
+
+4. **Review Results** (10 min)
+   - Check final parameters
+   - Compare to baseline
+   - Review improvement %
+
+5. **Validate on Other Scenarios** (15 min)
+   - Run batch test with optimized parameters
+   - Ensure no regressions on other trajectories
+
+6. **Save or Iterate:**
+   - If satisfied: Save as "Optimized_v1"
+   - If not: Adjust weights, re-run optimization
+
+---
+
+### Workflow 5: A/B Testing Configurations
+
+**Goal:** Compare two parameter sets side-by-side.
+
+**Steps:**
+
+1. **Select Configurations** (2 min)
+   - Config A: "Default"
+   - Config B: "Tuned_v1"
+
+2. **Choose Test Scenario** (1 min)
+   - Straight Line 10m
+
+3. **Run Comparison** (5 min)
+   - Click "Run Comparison"
+   - System runs both tests sequentially
+
+4. **Analyze Results** (5 min)
+   - View side-by-side metrics table
+   - Check trajectory overlay plot
+   - Identify winner
+
+5. **Statistical Significance** (optional)
+   - Run 10 trials each
+   - Compare mean ± std deviation
+   - Determine if difference is significant
+
+---
+
+## IMPLEMENTATION PHASES
+
+Phased approach to building the system, prioritized by value and complexity.
+
+---
+
+### Phase 0: MVP (Weeks 1-3)
+
+**Goal:** Core functionality for manual tuning.
+
+**Features:**
+- ✅ Single test execution
+- ✅ Manual parameter adjustment UI
+- ✅ Real-time visualization (2D trajectory)
+- ✅ Basic metrics calculation
+- ✅ Save/load configurations
+- ✅ Data logging
+
+**Deliverables:**
+1. Working Blazor dashboard
+2. Integrated controllers (PID, Estimator, Pure Pursuit)
+3. Basic test executor
+4. SQLite database with core tables
+5. Real-time SignalR updates
+
+**Tech Stack:**
+- Blazor Server
+- Entity Framework Core + SQLite
+- SignalR
+- Plotly.NET for charts
+
+**Testing:**
+- Unit tests for controllers
+- Integration test for one full test run
+- Manual UI testing
+
+**Success Criteria:**
+- User can run a test and see results
+- Parameters can be adjusted and re-run
+- Metrics are calculated correctly
+
+---
+
+### Phase 1: Enhanced Tuning (Weeks 4-6)
+
+**Goal:** Multi-scenario testing and comparison.
+
+**Features:**
+- ✅ Batch testing
+- ✅ Configuration comparison
+- ✅ Test history viewer
+- ✅ Safety monitoring with abort
+- ✅ Parameter validation
+- ✅ CSV export
+
+**Deliverables:**
+1. Batch test executor
+2. Comparison UI components
+3. Enhanced database queries
+4. Safety monitor implementation
+5. Report generation (HTML/CSV)
+
+**Testing:**
+- Batch test with 3 scenarios
+- Comparison test with 3 configs
+- Safety violation test
+
+**Success Criteria:**
+- Batch tests complete without manual intervention
+- Comparison clearly shows best configuration
+- Safety system aborts on violations
+
+---
+
+### Phase 2: Advanced Analytics (Weeks 7-9) - OPTIONAL
+
+**Goal:** Deep insights and semi-automated tuning.
+
+**Features:**
+- ⭕ Statistical analysis
+- ⭕ Trend analysis over time
+- ⭕ Parameter sensitivity analysis
+- ⭕ Tuning suggestions
+- ⭕ PDF report generation
+
+**Deliverables:**
+1. Statistics calculator
+2. Trend visualization
+3. Suggestion engine (rule-based)
+4. PDF generator
+
+**Testing:**
+- Historical data analysis (50+ tests)
+- Suggestion accuracy validation
+
+**Success Criteria:**
+- Trends clearly visible
+- Suggestions improve results
+
+---
+
+### Phase 3: Automated Optimization (Weeks 10-13) - FUTURE
+
+**Goal:** Hands-off parameter optimization.
+
+**Features:**
+- ❌ Grid search
+- ❌ Random search
+- ❌ Bayesian optimization
+- ❌ Genetic algorithm
+- ❌ Multi-objective optimization
+
+**Deliverables:**
+1. Optimization framework
+2. Multiple algorithm implementations
+3. Hyperparameter tuning for optimizers
+4. Parallel evaluation (if multiple robots)
+
+**Complexity:** Very High (requires ML libraries)
+
+**Testing:**
+- Benchmark against manual tuning
+- Convergence tests
+- Robustness tests
+
+**Success Criteria:**
+- Automated optimization finds better params than manual in <1 hour
+- Reproducible results
+
+---
+
+## TESTING STRATEGY
+
+Comprehensive testing at all levels.
+
+---
+
+### 1. Unit Tests
+
+**Coverage Target:** >80% for domain logic
+
+**Key Tests:**
+
+```csharp
+// PID Controller Tests
+[Fact]
+public void PIDController_ProportionalOnly_CorrectOutput()
+{
+    var config = new VelocityPIDConfig { Kp = 1.0f, Ki = 0, Kd = 0 };
+    var pid = new PIDController(config);
+    
+    var output = pid.Calculate(error: 1.0f, dt: 0.02f);
+    
+    Assert.Equal(1.0f, output, precision: 2);
+}
+
+[Fact]
+public void PIDController_IntegralWindup_Clamped()
+{
+    var config = new VelocityPIDConfig 
+    { 
+        Kp = 0, 
+        Ki = 1.0f, 
+        Kd = 0,
+        IntegralWindupLimit = 0.5f
+    };
+    var pid = new PIDController(config);
+    
+    // Accumulate large error
+    for (int i = 0; i < 100; i++)
+        pid.Calculate(error: 1.0f, dt: 0.02f);
+    
+    var output = pid.Calculate(error: 1.0f, dt: 0.02f);
+    
+    Assert.True(output <= 0.5f);
+}
+
+// Velocity Estimator Tests
+[Fact]
+public void VelocityEstimator_GoodTracking_TrustsEncoder()
+{
+    var config = DefaultConfigurations.Estimator;
+    var estimator = new VelocityEstimator(config, new VelocitySignalProcessingConfig());
+    
+    var vHybrid = estimator.EstimateVelocity(
+        vCmd: 1.0f, 
+        vActual: 0.95f,  // Close to command (good tracking)
+        dt: 0.02f
+    );
+    
+    // Should blend more toward encoder (0.95) than model
+    Assert.True(vHybrid > 0.93f && vHybrid < 0.97f);
+}
+
+// Pure Pursuit Tests
+[Fact]
+public void PurePursuit_LookaheadScalesWithVelocity()
+{
+    var config = new PurePursuitConfig 
+    { 
+        LookaheadMin = 0.3f,
+        Kdd = 1.0f,
+        LookaheadMax = 2.0f
+    };
+    var pp = new PurePursuitController(config);
+    
+    var path = CreateStraightLinePath(10);
+    var pose = new Pose2D(0, 0, 0);
+    
+    pp.Calculate(pose, velocity: 0.5f, confidence: 1.0f, path);
+    var lookahead1 = pp.GetLookaheadDistance();
+    
+    pp.Calculate(pose, velocity: 1.0f, confidence: 1.0f, path);
+    var lookahead2 = pp.GetLookaheadDistance();
+    
+    Assert.True(lookahead2 > lookahead1);
+}
+```
+
+---
+
+### 2. Integration Tests
+
+```csharp
+[Fact]
+public async Task FullTestRun_StraightLine_Completes()
+{
+    // Arrange
+    var scenario = CreateStraightLineScenario(10);
+    var parameters = DefaultConfigurations.GetDefaultPreset();
+    var orchestrator = CreateOrchestrator();
+    
+    // Act
+    var result = await orchestrator.RunSingleTest(scenario, parameters);
+    
+    // Assert
+    Assert.Equal(TestStatus.Completed, result.Status);
+    Assert.NotNull(result.Metrics);
+    Assert.True(result.Metrics.CrossTrackErrorRMS < 0.20f);
+}
+
+[Fact]
+public async Task SafetyMonitor_ExcessiveCTE_AbortsTest()
+{
+    // Arrange
+    var scenario = CreateCircleScenario(0.5f); // Tight circle
+    var parameters = CreateBadParameters(); // Intentionally bad
+    var orchestrator = CreateOrchestrator();
+    
+    // Act
+    var result = await orchestrator.RunSingleTest(scenario, parameters);
+    
+    // Assert
+    Assert.Equal(TestStatus.Aborted, result.Status);
+    Assert.True(result.SafetyViolations.Any(v => v.Type == ViolationType.CrossTrackError));
+}
+```
+
+---
+
+### 3. Performance Tests
+
+```csharp
+[Fact]
+public void ControlLoop_MaintainsFrequency()
+{
+    var executor = CreateTestExecutor();
+    var scenario = CreateStraightLineScenario(5);
+    var parameters = DefaultConfigurations.GetDefaultPreset();
+    
+    var timestamps = new List<long>();
+    
+    executor.ExecuteAsync(
+        onStateUpdate: state => timestamps.Add(state.TimestampMs)
+    ).Wait();
+    
+    // Calculate actual frequency
+    var intervals = timestamps.Zip(timestamps.Skip(1), (a, b) => b - a);
+    var avgInterval = intervals.Average();
+    var actualFrequency = 1000.0 / avgInterval;
+    
+    Assert.InRange(actualFrequency, 48, 52); // 50Hz ± 2Hz
+}
+```
+
+---
+
+### 4. End-to-End Tests
+
+**Manual Test Plan:**
+
+1. **Happy Path Test**
+   - Load default config
+   - Run straight line test
+   - Verify metrics displayed
+   - Save configuration
+   - Reload and verify
+
+2. **Error Handling Test**
+   - Set invalid parameter (Kp = 100)
+   - Attempt to run test
+   - Verify error message shown
+   - Verify test doesn't start
+
+3. **Real-time Update Test**
+   - Start test
+   - Verify UI updates at ~10Hz
+   - Pause test
+   - Verify pause works
+   - Resume and complete
+
+4. **Comparison Test**
+   - Create 2 configs
+   - Run comparison
+   - Verify side-by-side display
+   - Export results
+
+---
+
+## DEPLOYMENT CHECKLIST
+
+Pre-deployment validation:
+
+- [ ] All unit tests pass
+- [ ] Integration tests pass
+- [ ] Performance tests pass
+- [ ] Manual E2E tests completed
+- [ ] Database migrations created
+- [ ] Default data seeded
+- [ ] Configuration files reviewed
+- [ ] Robot hardware tested
+- [ ] Emergency stop tested
+- [ ] Documentation complete
+- [ ] User manual created
+
+---
+
+This completes the Configuration, Workflows & Implementation Guide.