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368 行
15 KiB
368 行
15 KiB
using System;
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using UnityEngine;
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using Unity.MLAgents;
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using Unity.Barracuda;
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using Unity.MLAgents.Actuators;
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using Unity.MLAgentsExamples;
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using Unity.MLAgents.Sensors;
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using Random = UnityEngine.Random;
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[RequireComponent(typeof(JointDriveController))] // Required to set joint forces
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public class CrawlerAgent : Agent
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{
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//The type of crawler behavior we want to use.
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//This setting will determine how the agent is set up during initialization.
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public enum CrawlerAgentBehaviorType
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{
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CrawlerDynamic,
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CrawlerDynamicVariableSpeed,
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CrawlerStatic,
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CrawlerStaticVariableSpeed
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}
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[Tooltip(
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"VariableSpeed - The agent will sample random speed magnitudes while training.\n" +
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"Dynamic - The agent will run towards a target that changes position.\n" +
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"Static - The agent will run towards a static target. "
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)]
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public CrawlerAgentBehaviorType typeOfCrawler;
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//Crawler Brains
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//A different brain will be used depending on the CrawlerAgentBehaviorType selected
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[Header("NN Models")] public NNModel crawlerDyModel;
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public NNModel crawlerDyVSModel;
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public NNModel crawlerStModel;
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public NNModel crawlerStVSModel;
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[Header("Walk Speed")]
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[Range(0.1f, m_maxWalkingSpeed)]
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[SerializeField]
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[Tooltip(
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"The speed the agent will try to match.\n\n" +
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"TRAINING:\n" +
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"For VariableSpeed envs, this value will randomize at the start of each training episode.\n" +
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"Otherwise the agent will try to match the speed set here.\n\n" +
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"INFERENCE:\n" +
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"During inference, VariableSpeed agents will modify their behavior based on this value " +
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"whereas the CrawlerDynamic & CrawlerStatic agents will run at the speed specified during training "
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)]
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//The walking speed to try and achieve
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private float m_TargetWalkingSpeed = m_maxWalkingSpeed;
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const float m_maxWalkingSpeed = 15; //The max walking speed
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//The current target walking speed. Clamped because a value of zero will cause NaNs
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public float TargetWalkingSpeed
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{
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get { return m_TargetWalkingSpeed; }
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set { m_TargetWalkingSpeed = Mathf.Clamp(value, .1f, m_maxWalkingSpeed); }
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}
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//Should the agent sample a new goal velocity each episode?
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//If true, TargetWalkingSpeed will be randomly set between 0.1 and m_maxWalkingSpeed in OnEpisodeBegin()
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//If false, the goal velocity will be m_maxWalkingSpeed
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private bool m_RandomizeWalkSpeedEachEpisode;
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//The direction an agent will walk during training.
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[Header("Target To Walk Towards")] public Transform dynamicTargetPrefab; //Target prefab to use in Dynamic envs
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public Transform staticTargetPrefab; //Target prefab to use in Static envs
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private Transform m_Target; //Target the agent will walk towards during training.
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[Header("Body Parts")] [Space(10)] public Transform body;
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public Transform leg0Upper;
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public Transform leg0Lower;
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public Transform leg1Upper;
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public Transform leg1Lower;
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public Transform leg2Upper;
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public Transform leg2Lower;
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public Transform leg3Upper;
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public Transform leg3Lower;
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//This will be used as a stabilized model space reference point for observations
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//Because ragdolls can move erratically during training, using a stabilized reference transform improves learning
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OrientationCubeController m_OrientationCube;
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//The indicator graphic gameobject that points towards the target
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DirectionIndicator m_DirectionIndicator;
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JointDriveController m_JdController;
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[Header("Foot Grounded Visualization")]
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[Space(10)]
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public bool useFootGroundedVisualization;
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public MeshRenderer foot0;
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public MeshRenderer foot1;
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public MeshRenderer foot2;
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public MeshRenderer foot3;
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public Material groundedMaterial;
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public Material unGroundedMaterial;
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public override void Initialize()
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{
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SetAgentType();
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m_OrientationCube = GetComponentInChildren<OrientationCubeController>();
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m_DirectionIndicator = GetComponentInChildren<DirectionIndicator>();
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m_JdController = GetComponent<JointDriveController>();
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//Setup each body part
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m_JdController.SetupBodyPart(body);
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m_JdController.SetupBodyPart(leg0Upper);
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m_JdController.SetupBodyPart(leg0Lower);
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m_JdController.SetupBodyPart(leg1Upper);
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m_JdController.SetupBodyPart(leg1Lower);
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m_JdController.SetupBodyPart(leg2Upper);
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m_JdController.SetupBodyPart(leg2Lower);
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m_JdController.SetupBodyPart(leg3Upper);
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m_JdController.SetupBodyPart(leg3Lower);
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}
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/// <summary>
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/// Spawns a target prefab at pos
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/// </summary>
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/// <param name="prefab"></param>
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/// <param name="pos"></param>
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void SpawnTarget(Transform prefab, Vector3 pos)
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{
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m_Target = Instantiate(prefab, pos, Quaternion.identity, transform);
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}
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/// <summary>
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/// Set up the agent based on the typeOfCrawler
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/// </summary>
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void SetAgentType()
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{
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var behaviorParams = GetComponent<Unity.MLAgents.Policies.BehaviorParameters>();
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switch (typeOfCrawler)
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{
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case CrawlerAgentBehaviorType.CrawlerDynamic:
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{
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behaviorParams.BehaviorName = "CrawlerDynamic"; //set behavior name
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if (crawlerDyModel)
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behaviorParams.Model = crawlerDyModel; //assign the model
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m_RandomizeWalkSpeedEachEpisode = false; //do not randomize m_TargetWalkingSpeed during training
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SpawnTarget(dynamicTargetPrefab, transform.position); //spawn target
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break;
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}
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case CrawlerAgentBehaviorType.CrawlerDynamicVariableSpeed:
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{
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behaviorParams.BehaviorName = "CrawlerDynamicVariableSpeed"; //set behavior name
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if (crawlerDyVSModel)
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behaviorParams.Model = crawlerDyVSModel; //assign the model
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m_RandomizeWalkSpeedEachEpisode = true; //randomize m_TargetWalkingSpeed during training
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SpawnTarget(dynamicTargetPrefab, transform.position); //spawn target
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break;
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}
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case CrawlerAgentBehaviorType.CrawlerStatic:
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{
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behaviorParams.BehaviorName = "CrawlerStatic"; //set behavior name
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if (crawlerStModel)
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behaviorParams.Model = crawlerStModel; //assign the model
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m_RandomizeWalkSpeedEachEpisode = false; //do not randomize m_TargetWalkingSpeed during training
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SpawnTarget(staticTargetPrefab, transform.TransformPoint(new Vector3(0, 0, 1000))); //spawn target
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break;
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}
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case CrawlerAgentBehaviorType.CrawlerStaticVariableSpeed:
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{
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behaviorParams.BehaviorName = "CrawlerStaticVariableSpeed"; //set behavior name
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if (crawlerStVSModel)
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behaviorParams.Model = crawlerStVSModel; //assign the model
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m_RandomizeWalkSpeedEachEpisode = true; //randomize m_TargetWalkingSpeed during training
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SpawnTarget(staticTargetPrefab, transform.TransformPoint(new Vector3(0, 0, 1000))); //spawn target
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break;
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}
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}
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}
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/// <summary>
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/// Loop over body parts and reset them to initial conditions.
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/// </summary>
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public override void OnEpisodeBegin()
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{
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foreach (var bodyPart in m_JdController.bodyPartsDict.Values)
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{
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bodyPart.Reset(bodyPart);
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}
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//Random start rotation to help generalize
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body.rotation = Quaternion.Euler(0, Random.Range(0.0f, 360.0f), 0);
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UpdateOrientationObjects();
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//Set our goal walking speed
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TargetWalkingSpeed =
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m_RandomizeWalkSpeedEachEpisode ? Random.Range(0.1f, m_maxWalkingSpeed) : TargetWalkingSpeed;
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}
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/// <summary>
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/// Add relevant information on each body part to observations.
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/// </summary>
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public void CollectObservationBodyPart(BodyPart bp, VectorSensor sensor)
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{
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//GROUND CHECK
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sensor.AddObservation(bp.groundContact.touchingGround); // Is this bp touching the ground
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if (bp.rb.transform != body)
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{
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sensor.AddObservation(bp.currentStrength / m_JdController.maxJointForceLimit);
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}
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}
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/// <summary>
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/// Loop over body parts to add them to observation.
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/// </summary>
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public override void CollectObservations(VectorSensor sensor)
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{
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var cubeForward = m_OrientationCube.transform.forward;
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//velocity we want to match
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var velGoal = cubeForward * TargetWalkingSpeed;
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//ragdoll's avg vel
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var avgVel = GetAvgVelocity();
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//current ragdoll velocity. normalized
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sensor.AddObservation(Vector3.Distance(velGoal, avgVel));
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//avg body vel relative to cube
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sensor.AddObservation(m_OrientationCube.transform.InverseTransformDirection(avgVel));
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//vel goal relative to cube
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sensor.AddObservation(m_OrientationCube.transform.InverseTransformDirection(velGoal));
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//rotation delta
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sensor.AddObservation(Quaternion.FromToRotation(body.forward, cubeForward));
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//Add pos of target relative to orientation cube
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sensor.AddObservation(m_OrientationCube.transform.InverseTransformPoint(m_Target.transform.position));
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RaycastHit hit;
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float maxRaycastDist = 10;
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if (Physics.Raycast(body.position, Vector3.down, out hit, maxRaycastDist))
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{
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sensor.AddObservation(hit.distance / maxRaycastDist);
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}
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else
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sensor.AddObservation(1);
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foreach (var bodyPart in m_JdController.bodyPartsList)
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{
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CollectObservationBodyPart(bodyPart, sensor);
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}
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}
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public override void OnActionReceived(ActionBuffers actionBuffers)
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{
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// The dictionary with all the body parts in it are in the jdController
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var bpDict = m_JdController.bodyPartsDict;
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var continuousActions = actionBuffers.ContinuousActions;
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var i = -1;
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// Pick a new target joint rotation
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bpDict[leg0Upper].SetJointTargetRotation(continuousActions[++i], continuousActions[++i], 0);
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bpDict[leg1Upper].SetJointTargetRotation(continuousActions[++i], continuousActions[++i], 0);
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bpDict[leg2Upper].SetJointTargetRotation(continuousActions[++i], continuousActions[++i], 0);
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bpDict[leg3Upper].SetJointTargetRotation(continuousActions[++i], continuousActions[++i], 0);
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bpDict[leg0Lower].SetJointTargetRotation(continuousActions[++i], 0, 0);
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bpDict[leg1Lower].SetJointTargetRotation(continuousActions[++i], 0, 0);
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bpDict[leg2Lower].SetJointTargetRotation(continuousActions[++i], 0, 0);
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bpDict[leg3Lower].SetJointTargetRotation(continuousActions[++i], 0, 0);
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// Update joint strength
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bpDict[leg0Upper].SetJointStrength(continuousActions[++i]);
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bpDict[leg1Upper].SetJointStrength(continuousActions[++i]);
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bpDict[leg2Upper].SetJointStrength(continuousActions[++i]);
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bpDict[leg3Upper].SetJointStrength(continuousActions[++i]);
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bpDict[leg0Lower].SetJointStrength(continuousActions[++i]);
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bpDict[leg1Lower].SetJointStrength(continuousActions[++i]);
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bpDict[leg2Lower].SetJointStrength(continuousActions[++i]);
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bpDict[leg3Lower].SetJointStrength(continuousActions[++i]);
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}
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void FixedUpdate()
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{
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UpdateOrientationObjects();
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// If enabled the feet will light up green when the foot is grounded.
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// This is just a visualization and isn't necessary for function
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if (useFootGroundedVisualization)
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{
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foot0.material = m_JdController.bodyPartsDict[leg0Lower].groundContact.touchingGround
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? groundedMaterial
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: unGroundedMaterial;
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foot1.material = m_JdController.bodyPartsDict[leg1Lower].groundContact.touchingGround
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? groundedMaterial
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: unGroundedMaterial;
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foot2.material = m_JdController.bodyPartsDict[leg2Lower].groundContact.touchingGround
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? groundedMaterial
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: unGroundedMaterial;
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foot3.material = m_JdController.bodyPartsDict[leg3Lower].groundContact.touchingGround
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? groundedMaterial
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: unGroundedMaterial;
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}
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var cubeForward = m_OrientationCube.transform.forward;
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// Set reward for this step according to mixture of the following elements.
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// a. Match target speed
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//This reward will approach 1 if it matches perfectly and approach zero as it deviates
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var matchSpeedReward = GetMatchingVelocityReward(cubeForward * TargetWalkingSpeed, GetAvgVelocity());
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// b. Rotation alignment with target direction.
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//This reward will approach 1 if it faces the target direction perfectly and approach zero as it deviates
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var lookAtTargetReward = (Vector3.Dot(cubeForward, body.forward) + 1) * .5F;
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AddReward(matchSpeedReward * lookAtTargetReward);
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}
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/// <summary>
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/// Update OrientationCube and DirectionIndicator
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/// </summary>
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void UpdateOrientationObjects()
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{
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m_OrientationCube.UpdateOrientation(body, m_Target);
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if (m_DirectionIndicator)
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{
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m_DirectionIndicator.MatchOrientation(m_OrientationCube.transform);
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}
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}
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/// <summary>
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///Returns the average velocity of all of the body parts
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///Using the velocity of the body only has shown to result in more erratic movement from the limbs
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///Using the average helps prevent this erratic movement
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/// </summary>
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Vector3 GetAvgVelocity()
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{
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Vector3 velSum = Vector3.zero;
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Vector3 avgVel = Vector3.zero;
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//ALL RBS
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int numOfRB = 0;
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foreach (var item in m_JdController.bodyPartsList)
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{
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numOfRB++;
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velSum += item.rb.velocity;
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}
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avgVel = velSum / numOfRB;
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return avgVel;
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}
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/// <summary>
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/// Normalized value of the difference in actual speed vs goal walking speed.
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/// </summary>
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public float GetMatchingVelocityReward(Vector3 velocityGoal, Vector3 actualVelocity)
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{
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//distance between our actual velocity and goal velocity
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var velDeltaMagnitude = Mathf.Clamp(Vector3.Distance(actualVelocity, velocityGoal), 0, TargetWalkingSpeed);
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//return the value on a declining sigmoid shaped curve that decays from 1 to 0
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//This reward will approach 1 if it matches perfectly and approach zero as it deviates
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return Mathf.Pow(1 - Mathf.Pow(velDeltaMagnitude / TargetWalkingSpeed, 2), 2);
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}
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/// <summary>
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/// Agent touched the target
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/// </summary>
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public void TouchedTarget()
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{
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AddReward(1f);
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}
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}
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