add actuated sensors & rbsensor

Project/Assets/ML-Agents/Examples/Soccer/Prefabs/BlueStriker.prefab

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Project/Assets/ML-Agents/Examples/Soccer/Scenes/SoccerTwos.unity

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Project/Assets/ML-Agents/Examples/Soccer/Scripts/AgentSoccer.cs

 using UnityEngine;
+using System.Collections.Generic;
+using Unity.MLAgents.Sensors;
 using Unity.MLAgents.Policies;
 
 public enum Team
     public float rotSign;
 
     EnvironmentParameters m_ResetParams;
+
+
+    [Header("ACTUATED RAY SENSOR")]
+    //Actuated RayS
+    public bool UseVectorObs = true;
+    public bool UseActuatedRaycastSensor = false;
+    // public List<RayPerceptionSensorComponent3D> RaySensorsList = new List<RayPerceptionSensorComponent3D>();
+    public RayPerceptionSensorComponent3D RaySensor;
+
+    public Vector2 MinMaxRayAngles = new Vector2(25, 120);
+    public Vector2 MinMaxSpherecastRadius = new Vector2(.25f, 1);
+    public float CurrentRayAngleLerp = .5f;
+    public float CurrentSpherecastRadiusLerp = .5f;
 
     public override void Initialize()
     {
         m_ResetParams = Academy.Instance.EnvironmentParameters;
     }
 
+    public override void CollectObservations(VectorSensor sensor)
+    {
+
+        if (UseVectorObs)
+        {
+            // // sensor.AddObservation((float)StepCount / (float)MaxStep); //Helps with credit assign?
+            // sensor.AddObservation(ThrowController.coolDownWait); //Held DBs Normalized
+            // sensor.AddObservation((float)currentNumberOfBalls/4); //Held DBs Normalized
+            // // sensor.AddObservation((float)HitPointsRemaining/(float)NumberOfTimesPlayerCanBeHit); //Remaining Hit Points Normalized
+            // sensor.AddObservation((float)HitPointsRemaining/(float)m_GameController.PlayerMaxHitPoints); //Remaining Hit Points Normalized
+            // sensor.AddObservation(Vector3.Dot(m_AgentRb.velocity, m_AgentRb.transform.forward)); //forward speed
+            // sensor.AddObservation(Vector3.Dot(m_AgentRb.velocity, m_AgentRb.transform.right)); //lateral speed
+            // sensor.AddObservation(m_AgentRb.angularVelocity);
+
+            if (UseActuatedRaycastSensor)
+            {
+                sensor.AddObservation(CurrentRayAngleLerp);
+                sensor.AddObservation(CurrentSpherecastRadiusLerp);
+            }
+        }
+    }
+
+    public void UpdateSensors()
+    {
+
+    }
+
     public void MoveAgent(ActionSegment<float> act)
     {
         var dirToGo = Vector3.zero;
         dirToGo += transform.right * right * m_LateralSpeed;
         rotateDir = -transform.up * rotate * m_RotateSpeed;
 
-        
+
+
+
+        // ACTUATED SENSOR STUFF
+        CurrentRayAngleLerp = (act[3] + 1)/2;
+        CurrentSpherecastRadiusLerp = (act[4] + 1)/2;
+        if (UseActuatedRaycastSensor)
+        {
+                RaySensor.MaxRayDegrees = Mathf.Lerp(MinMaxRayAngles.x, MinMaxRayAngles.y, CurrentRayAngleLerp);
+                RaySensor.SphereCastRadius = Mathf.Lerp(MinMaxSpherecastRadius.x, MinMaxSpherecastRadius.y, CurrentSpherecastRadiusLerp);
+
+            // foreach (var item in RaySensorsList)
+            // {
+            //     item.MaxRayDegrees = Mathf.Lerp(MinMaxRayAngles.x, MinMaxRayAngles.y, CurrentRayAngleLerp);
+            //     item.SphereCastRadius = Mathf.Lerp(MinMaxSpherecastRadius.x, MinMaxSpherecastRadius.y, CurrentSpherecastRadiusLerp);
+            // }
+        }
     }
 
     public override void OnActionReceived(ActionBuffers actionBuffers)

Project/Assets/ML-Agents/Examples/Soccer/TFModels/SoccerTwos-14999860.onnx.meta

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config/poca/Soccer.yaml

+behaviors:
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+    trainer_type: poca
+    hyperparameters:
+      batch_size: 2048
+      buffer_size: 20480
+      learning_rate: 0.0003
+      beta: 0.01
+      epsilon: 0.2
+      lambd: 0.95
+      num_epoch: 3
+      learning_rate_schedule: constant
+    network_settings:
+      normalize: false
+      hidden_units: 512
+      num_layers: 2
+      vis_encode_type: simple
+    reward_signals:
+      extrinsic:
+        gamma: 0.99
+        strength: 1.0
+    keep_checkpoints: 5
+    max_steps: 100000000
+    time_horizon: 1000
+    summary_freq: 10000
+    threaded: false
+    self_play:
+      save_steps: 50000
+      team_change: 200000
+      swap_steps: 2000
+      window: 10
+      play_against_latest_model_ratio: 0.5
+      initial_elo: 1200.0
+environment_parameters:
+  ball_touch:
+    curriculum:
+      - name: Lesson0 # The '-' is important as this is a list
+        completion_criteria:
+          measure: progress
+          behavior: SoccerTwos
+          signal_smoothing: true
+          min_lesson_length: 100
+          threshold: 0.01
+        value: 1.0
+      - name: Lesson1 # The '-' is important as this is a list
+        completion_criteria:
+          measure: progress
+          behavior: SoccerTwos
+          signal_smoothing: true
+          min_lesson_length: 100
+          threshold: 0.02
+        value: 0.5
+      - name: Lesson2 # The '-' is important as this is a list
+        value: 0.0
+#env_settings:
+#  num_envs: 3