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Environment.hpp
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Environment.hpp
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//----------------------------//
// This file is part of RaiSim//
// Copyright 2020, RaiSim Tech//
//----------------------------//
#pragma once
#include <deque>
#include <stdlib.h>
#include <math.h>
#include <cstdint>
#include <set>
#include <vector>
#include <string>
#include <random>
#include "../../RaisimGymEnv.hpp"
#include <fenv.h>
#include <stdexcept>
template <typename T>
inline void scaling(T &n, const T &max_src, const T &max_dst)
{
n = n / max_src * max_dst;
}
inline void quatToEuler(const raisim::Vec<4> &quat, Eigen::Vector3d &eulerVec)
{
double qw = quat[0], qx = quat[1], qy = quat[2], qz = quat[3];
// roll (x-axis rotation)
double sinr_cosp = 2 * (qw * qx + qy * qz);
double cosr_cosp = 1 - 2 * (qx * qx + qy * qy);
eulerVec[0] = std::atan2(sinr_cosp, cosr_cosp);
// pitch (y-axis rotation)
double sinp = 2 * (qw * qy - qz * qx);
if (std::abs(sinp) >= 1)
eulerVec[1] = std::copysign(M_PI / 2, sinp); // use 90 degrees if out of range
else
eulerVec[1] = std::asin(sinp);
// yaw (z-axis rotation)
double siny_cosp = 2 * (qw * qz + qx * qy);
double cosy_cosp = 1 - 2 * (qy * qy + qz * qz);
eulerVec[2] = std::atan2(siny_cosp, cosy_cosp);
}
namespace raisim
{
class ENVIRONMENT : public RaisimGymEnv
{
public:
explicit ENVIRONMENT(const std::string &resourceDir, const Yaml::Node &cfg, bool visualizable, int env_id) : RaisimGymEnv(resourceDir, cfg), visualizable_(visualizable)
{
setSeed(env_id);
for (int i = 0; i < 10; i++)
clean_randomizer = Eigen::VectorXd::Random(1)[0];
/// add objects
READ_YAML(bool, isTest, cfg["test"])
READ_YAML(bool, isEval, cfg["eval"])
READ_YAML(bool, roughTerrain, cfg["roughTerrain"])
READ_YAML(bool, privinfo, cfg["privinfo"])
READ_YAML(bool, includeGRF, cfg["includeGRF"])
READ_YAML(int, baseDim, cfg["baseDim"])
READ_YAML(int, geomDim, cfg["geomDim"])
READ_YAML(bool, randomize_friction, cfg["randomize_friction"])
READ_YAML(bool, randomize_mass, cfg["randomize_mass"])
READ_YAML(bool, randomize_motor_strength, cfg["randomize_motor_strength"])
READ_YAML(bool, randomize_gains, cfg["randomize_gains"])
READ_YAML(bool, use_priv_vel, cfg["use_priv_vel"])
READ_YAML(bool, use_slope_dots, cfg["use_slope_dots"])
/// Target Speed
READ_YAML(bool, cts_target_speed, cfg["cts_target_speed"])
READ_YAML(double, target_end_speed, cfg["target_end_speed"])
READ_YAML(double, pid_coeff, cfg["pid_coeff"])
READ_YAML(double, slope_th, cfg["slope_threshold"])
READ_YAML(double, target_start_speed, cfg["target_start_speed"])
READ_YAML(double, target_speed_period, cfg["target_speed_period"])
READ_YAML(bool, observe_base_speed, cfg["observe_base_speed"])
READ_YAML(double, bodyLinearVel_avg_weight, cfg["bodyLinearVel_avg_weight"])
READ_YAML(bool, speedTest, cfg["speedTest"])
READ_YAML(bool, target_speed_curriculum, cfg["target_speed_curriculum"])
/// Reward coefficients
READ_YAML(double, forwardVelRewardCoeff_, cfg["forwardVelRewardCoeff"])
READ_YAML(double, lateralVelRewardCoeff_, cfg["lateralVelRewardCoeff"])
READ_YAML(double, angularVelRewardCoeff_, cfg["angularVelRewardCoeff"])
READ_YAML(double, torqueRewardCoeff_, cfg["torqueRewardCoeff"])
READ_YAML(double, deltaTorqueRewardCoeff_, cfg["deltaTorqueRewardCoeff"])
READ_YAML(double, actionRewardCoeff_, cfg["actionRewardCoeff"])
READ_YAML(double, sidewaysRewardCoeff_, cfg["sidewaysRewardCoeff"])
READ_YAML(double, jointSpeedRewardCoeff_, cfg["jointSpeedRewardCoeff"])
READ_YAML(double, cost_coeff, cfg["cost_coeff"])
READ_YAML(double, cost_decay_fac, cfg["cost_decay_fac"])
READ_YAML(double, deltaContactRewardCoeff_, cfg["deltaContactRewardCoeff"])
READ_YAML(double, deltaReleaseRewardCoeff_, cfg["deltaReleaseRewardCoeff"])
READ_YAML(double, contactRewardCoeff_, cfg["contactRewardCoeff"])
READ_YAML(double, footSlipRewardCoeff_, cfg["footSlipRewardCoeff"])
READ_YAML(double, footClearenceRewardCoeff_, cfg["footClearenceRewardCoeff"])
READ_YAML(double, contactChangeRewardCoeff_, cfg["contactChangeRewardCoeff"])
READ_YAML(double, contactDistRewardCoeff_, cfg["contactDistRewardCoeff"])
READ_YAML(double, upwardRewardCoeff_, cfg["upwardRewardCoeff"])
READ_YAML(double, workRewardCoeff_, cfg["workRewardCoeff"])
READ_YAML(double, yAccRewardCoeff_, cfg["yAccRewardCoeff"])
READ_YAML(double, dynNoise_, cfg["dynNoise"])
READ_YAML(double, max_speed, cfg["max_speed"])
READ_YAML(double, lat_speed, cfg["lat_speed"])
READ_YAML(double, ang_speed, cfg["ang_speed"])
READ_YAML(double, terrain_freq, cfg["terrainFreq"])
READ_YAML(double, alive_bonus, cfg["aliveBonus"])
a1_ = world_->addArticulatedSystem(resourceDir_ + "/a1/urdf/a1.urdf");
a1_->setName("a1");
a1_->setControlMode(raisim::ControlMode::PD_PLUS_FEEDFORWARD_TORQUE);
/// indices of links that should not make contact with ground
footIndices_.insert(a1_->getBodyIdx("FR_calf"));
footIndices_.insert(a1_->getBodyIdx("FL_calf"));
footIndices_.insert(a1_->getBodyIdx("RR_calf"));
footIndices_.insert(a1_->getBodyIdx("RL_calf"));
base_idx = a1_->getBodyIdx("base");
// head_idx = a1_->getFrameIdxByName("head_joint");
footVec_.push_back(a1_->getBodyIdx("FR_calf"));
footVec_.push_back(a1_->getBodyIdx("FL_calf"));
footVec_.push_back(a1_->getBodyIdx("RR_calf"));
footVec_.push_back(a1_->getBodyIdx("RL_calf"));
footFrame_.push_back(a1_->getFrameIdxByName("FR_foot_fixed"));
footFrame_.push_back(a1_->getFrameIdxByName("FL_foot_fixed"));
footFrame_.push_back(a1_->getFrameIdxByName("RR_foot_fixed"));
footFrame_.push_back(a1_->getFrameIdxByName("RL_foot_fixed"));
nFoot = footVec_.size();
/// get robot data
gcDim_ = a1_->getGeneralizedCoordinateDim();
gvDim_ = a1_->getDOF();
nJoints_ = gvDim_ - 6;
base_mass_list = a1_->getMass();
/// initialize containers
gc_.setZero(gcDim_);
gc_init_.setZero(gcDim_);
gv_.setZero(gvDim_);
gv_init_.setZero(gvDim_);
pTarget_.setZero(gcDim_);
vTarget_.setZero(gvDim_);
pTarget12_.setZero(nJoints_);
mass_noise_vector.setZero(base_mass_list.size());
jt_mean_pos.setZero(nJoints_);
jt_mean_pos << 0.05, 0.8, -1.4, -0.05, 0.8, -1.4, 0.05, 0.8, -1.4, -0.05, 0.8, -1.4;
// randomize terrains
randomize_terrain();
/// set pd gains
// std::cout << "Pid coeffs " << pid_coeff << std::endl;
pgain = pid_coeff + Eigen::VectorXd::Random(1)[0] * 5.;
dgain = 0.6 + Eigen::VectorXd::Random(1)[0] * 0.2;
Eigen::VectorXd jointPgain(gvDim_), jointDgain(gvDim_);
jointPgain.setZero();
jointPgain.tail(nJoints_).setConstant(pgain);
jointDgain.setZero();
jointDgain.tail(nJoints_).setConstant(dgain);
a1_->setPdGains(jointPgain, jointDgain);
a1_->setGeneralizedForce(Eigen::VectorXd::Zero(gvDim_));
num_g1 = (int)g1_position.size();
// prior policy input
obDim_ = 42 + (int)privinfo * (20 + 3 * (int)use_priv_vel + nFoot * (int)use_slope_dots + 1 + 2*(num_g1 -1));
// trained policy input
obDim_ += baseDim + (int)privinfo * (20 + 3 * (int)use_priv_vel + nFoot * (int)use_slope_dots + 1 + 2*(num_g1-1));
actionDim_ = nJoints_;
actionMean_.setZero(actionDim_);
actionStd_.setZero(actionDim_), invActionStd_.setZero(actionDim_);
obDouble_.setZero(obDim_);
ob_delay.setZero(obDim_);
/// action & observation scaling
actionMean_ = gc_init_.tail(nJoints_);
double act_std_val = 0.4;
actionStd_.setConstant(act_std_val);
invActionStd_.setConstant(1. / act_std_val);
/// visualize if it is the first environment
if (visualizable_)
{
server_ = std::make_unique<raisim::RaisimServer>(world_.get());
server_->launchServer();
server_->focusOn(a1_);
if (isTest && use_slope_dots)
{ // TODO
for (int visual_i = 0; visual_i < (nFoot + 2*(num_g1 -1)); visual_i++)
{
visual_scan_dots.push_back(server_->addVisualSphere("viz_sphere_" + std::to_string(visual_i),
0.1, 1, 0, 0, 1));
}
}
}
// to store history
last_torque.resize(a1_->getGeneralizedForce().size());
last_torque = VecDyn(a1_->getGeneralizedForce());
last_contact.setZero(nFoot);
grf_bin_obs.setZero(nFoot);
last_swing.setZero(nFoot);
last_foot_state.setZero(nFoot);
}
void init() final {}
void kill_server()
{
server_->killServer();
}
void randomize_terrain()
{
// this function is only called to initialize terrains.
// it is not called later in the training
add_random_terrain();
gc_init_ << 0, 0, 0.6, 1.0, 0.0, 0.0, 0.0, jt_mean_pos;
}
void add_steps()
{
isSlope = true;
sampleCmds = true;
useRef = false;
isDown = false;
double sample_list[4] = {0.2, 0.3, 0.4, 0.5};
double stepSize = sample_list[std::rand() % 4];
double stepHeight = 0.15 + 0.05 * Eigen::VectorXd::Random(1)[0];
double pixelSize_ = 0.05;
raisim::TerrainProperties terrainProp_;
terrainProp_.xSize = 15.0;
terrainProp_.ySize = 15.0;
terrainProp_.xSamples = terrainProp_.xSize / pixelSize_;
terrainProp_.ySamples = terrainProp_.ySize / pixelSize_;
std::vector<double> heights_;
heights_.resize(terrainProp_.xSamples * terrainProp_.ySamples);
int xNum = terrainProp_.xSize / stepSize;
int yNum = terrainProp_.ySize / stepSize;
int gridWidth_ = stepSize / pixelSize_;
Eigen::Map<Eigen::Matrix<double, -1, -1>> mapMat(heights_.data(),
terrainProp_.xSamples,
terrainProp_.ySamples);
mapMat.setZero();
/// steps
for (size_t i = 0; i < xNum; i++)
{
for (size_t j = 0; j < yNum; j++)
{
double h = 0.5 * (1.0 + Eigen::VectorXd::Random(1)[0]) * stepHeight;
mapMat.block(gridWidth_ * j, gridWidth_ * i, gridWidth_, gridWidth_).setConstant(h);
}
}
mapMat.block(gridWidth_ * (xNum / 2 - 1), gridWidth_ * (yNum / 2 - 1), 2.0 / pixelSize_, 2.0 / pixelSize_).setConstant(0);
hm_ = world_->addHeightMap(terrainProp_.xSamples,
terrainProp_.ySamples,
terrainProp_.xSize,
terrainProp_.ySize, 0.0, 0.0, heights_, "terrain");
}
void add_slope()
{
isSlope = true;
sampleCmds = false;
useRef = false;
double stepHeight = 0.015 * Eigen::VectorXd::Random(1)[0];
double fractal_coeff;
if (stepHeight >= 0)
{
stepHeight += 0.01;
isDown = false;
fractal_coeff = 0.3 + 0.05 * Eigen::VectorXd::Random(1)[0];// 0.25,0.35
fractal_coeff /= 10;
} else {
stepHeight -= 0.01;
isDown = true;
fractal_coeff = 0.425 + 0.075 * Eigen::VectorXd::Random(1)[0];// 0.35,0.5
fractal_coeff /= 10;
stepHeight *= 0.67;
}
slope_info = stepHeight;
double pixelSize_ = 0.05;
raisim::TerrainProperties terrainProp_;
terrainProp_.xSize = 5.;
terrainProp_.ySize = 15.0;
terrainProp_.xSamples = terrainProp_.xSize / pixelSize_;
terrainProp_.ySamples = terrainProp_.ySize / pixelSize_;
std::vector<double> heights_;
heights_.resize(terrainProp_.xSamples * terrainProp_.ySamples);
double ht_i = -(double)terrainProp_.ySamples / 2.0 * stepHeight;
for (int y = 0; y < terrainProp_.ySamples; y++)
{
for (int x = 0; x < terrainProp_.xSamples; x++)
{
size_t idx = y * terrainProp_.xSamples + x;
if (x < 4 || x > terrainProp_.xSamples - 4 || y < 10 || y > terrainProp_.ySamples - 10)
heights_[idx] = ht_i - 1.5;
else
heights_[idx] = ht_i + fractal_coeff * Eigen::VectorXd::Random(1)[0];
}
if (abs(y - (int)terrainProp_.ySamples / 2) > 10)
ht_i += stepHeight;
}
Eigen::Map<Eigen::Matrix<double, -1, -1>> mapMat(heights_.data(),
terrainProp_.xSamples,
terrainProp_.ySamples);
Eigen::Map<Eigen::Matrix<double, -1, 1>> mapVec(heights_.data(),
terrainProp_.xSamples * terrainProp_.ySamples,
1);
Eigen::MatrixXd transMat = mapMat.transpose();
Eigen::Map<Eigen::Matrix<double, -1, 1>> transVec(transMat.data(), terrainProp_.xSamples * terrainProp_.ySamples, 1);
mapVec = transVec;
hm_ = world_->addHeightMap(terrainProp_.ySamples,
terrainProp_.xSamples,
terrainProp_.ySize,
terrainProp_.xSize, +terrainProp_.ySize/2 - 1, 0.0, heights_, "terrain");
}
void add_single_step()
{
isSlope = true;
int max_height_idx = std::max(2, (int)((itr_number - 3000) / 1000));
max_height_idx = std::min(max_height_idx, (int)step_height_list.size());
canonical_step_height = step_height_list[std::rand() % max_height_idx];
double stepHeight = -canonical_step_height;
double stepLength = 1.7; // should be enough to simulate multiple single steps
double pixelSize_ = 0.02;
double gridSize_ = 0.025;
raisim::TerrainProperties terrainProp_;
terrainProp_.xSize = 12.0;
terrainProp_.ySize = 12.0;
terrainProp_.xSamples = terrainProp_.xSize / pixelSize_;
terrainProp_.ySamples = terrainProp_.ySize / pixelSize_;
std::vector<double> heights_;
heights_.resize(terrainProp_.xSamples * terrainProp_.ySamples);
int N = (int)(stepLength / pixelSize_);
int mid0 = 0.5 * terrainProp_.ySamples - (int)(0.5 / pixelSize_);
int mid1 = 0.5 * terrainProp_.ySamples + (int)(0.7 / pixelSize_);
double stepStart = -stepHeight * (mid0 / N);
double max = 0.0;
int cnt = 0;
bool chamfer = false;
for (int y = 0; y < mid0; y++)
{
if (cnt == N)
{
stepStart = max;
cnt = 0;
stepHeight *= -1;
}
if (cnt == 0 && Eigen::VectorXd::Random(1)[0] < 0.5)
chamfer = true;
else
chamfer = false;
for (int x = 0; x < terrainProp_.xSamples; x++)
{
size_t idx = y * terrainProp_.xSamples + x;
max = stepStart + stepHeight;
heights_[idx] = max;
if (chamfer)
heights_[idx] -= gridSize_;
}
cnt++;
}
for (int y = mid0; y < mid1; y++)
{
for (int x = 0; x < terrainProp_.xSamples; x++)
{
size_t idx = y * terrainProp_.xSamples + x;
heights_[idx] = max;
}
}
cnt = N;
for (int y = mid1; y < terrainProp_.ySamples; y++)
{
if (cnt == N)
{
stepStart = max;
cnt = 0;
stepHeight *= -1;
}
if (cnt == 0 && Eigen::VectorXd::Random(1)[0] < 0.5)
chamfer = true;
else
chamfer = false;
for (int x = 0; x < terrainProp_.xSamples; x++)
{
size_t idx = y * terrainProp_.xSamples + x;
max = stepStart + stepHeight;
heights_[idx] = max;
if (chamfer)
heights_[idx] -= gridSize_;
}
cnt++;
}
Eigen::Map<Eigen::Matrix<double, -1, -1>> mapMat(heights_.data(),
terrainProp_.xSamples,
terrainProp_.ySamples);
Eigen::Map<Eigen::Matrix<double, -1, 1>> mapVec(heights_.data(),
terrainProp_.xSamples * terrainProp_.ySamples,
1);
Eigen::MatrixXd transMat = mapMat.transpose();
Eigen::Map<Eigen::Matrix<double, -1, 1>> transVec(transMat.data(), terrainProp_.xSamples * terrainProp_.ySamples, 1);
mapVec = transVec;
hm_ = world_->addHeightMap(terrainProp_.ySamples,
terrainProp_.xSamples,
terrainProp_.ySize,
terrainProp_.xSize, +terrainProp_.xSize / 3 + 1.0, 0.0, heights_, "terrain");
}
void add_stairs()
{
isSlope = true;
sampleCmds = false;
int max_height_idx = std::max(1, (int)((itr_number - start_itr_stairs) / 1000));
max_height_idx = std::min(max_height_idx, (int)step_height_list.size());
canonical_step_height = step_height_list[std::rand() % max_height_idx];
double sign = 1;
useRef = true;
isDown = false;
bool down;
if (isEval)
down = Eigen::VectorXd::Random(1)[0] > 0;
else
down = Eigen::VectorXd::Random(1)[0] > -0.5;
if (down){
sign = -1.;
useRef = false;
isDown = true;
max_height_idx = std::min(max_height_idx, ((int)step_height_list.size()-3));
canonical_step_height = step_height_list[std::rand() % max_height_idx];
}
double stepHeight = sign * canonical_step_height; // 0.03 + sign * 0.05 * Eigen::VectorXd::Random(1)[0];
// now step lenght
double stepLength = step_length_list[std::rand() % max_step_idx];
// fractal first
raisim::TerrainProperties terrainProperties;
terrainProperties.frequency = 20; // 10
double zscale_val = 0.0;
if (isDown)
zscale_val = 0.20;
if (isTest)
zscale_val = 0.0;
terrainProperties.zScale = zscale_val;
terrainProperties.xSize = 12; // maybe 12
terrainProperties.ySize = 12;
terrainProperties.xSamples = 200; // maybe 200
terrainProperties.ySamples = 200;
terrainProperties.fractalOctaves = 2;
terrainProperties.fractalLacunarity = 2.0;
terrainProperties.fractalGain = 0.25;
hm_ = world_->addHeightMap(0.0, 0.0, terrainProperties);
double pixelSize_ = 0.02;
double gridSize_ = 0.025;
raisim::TerrainProperties terrainProp_;
terrainProp_.xSize = 12.0;
terrainProp_.ySize = 12.0;
terrainProp_.xSamples = terrainProp_.xSize / pixelSize_;
terrainProp_.ySamples = terrainProp_.ySize / pixelSize_;
std::vector<double> heights_;
heights_.resize(terrainProp_.xSamples * terrainProp_.ySamples);
int N = (int)(stepLength / pixelSize_);
int mids = (int)(1.2 / pixelSize_);
int mid0 = 0.5 * terrainProp_.xSamples - (int)(1.2 / pixelSize_);
int mid1 = 0.5 * terrainProp_.xSamples + (int)(0.0 / pixelSize_);
double max = 0.2;
double stepStart = max; // stepHeight; // * (mid0 / N);
int cnt = 0;
bool chamfer = false;
// start platform
for (int x = 0; x < mids; x++)
{
for (int y = 0; y < terrainProp_.xSamples; y++)
{
size_t idx = x * terrainProp_.xSamples + y;
heights_[idx] = max;
}
}
for (int x = mids; x < mid0; x++)
{
if (cnt == N)
{
stepStart = max;
cnt = 0;
}
if (cnt == 0 && Eigen::VectorXd::Random(1)[0] < 0)
chamfer = true;
else
chamfer = false;
for (int y = 0; y < terrainProp_.xSamples; y++)
{
size_t idx = x * terrainProp_.xSamples + y;
max = stepStart + stepHeight;
heights_[idx] = max;
if (chamfer)
heights_[idx] -= gridSize_;
}
cnt++;
}
for (int x = mid0; x < mid1; x++)
{
for (int y = 0; y < terrainProp_.xSamples; y++)
{
size_t idx = x * terrainProp_.xSamples + y;
heights_[idx] = max;
}
}
cnt = N;
for (int x = mid1; x < terrainProp_.ySamples; x++)
{
if (cnt == N)
{
stepStart = max;
cnt = 0;
}
if (cnt == 0 && Eigen::VectorXd::Random(1)[0] < 0)
chamfer = true;
else
chamfer = false;
for (int y = 0; y < terrainProp_.xSamples; y++)
{
size_t idx = x * terrainProp_.xSamples + y;
max = stepStart + stepHeight;
heights_[idx] = max;
if (chamfer)
heights_[idx] -= gridSize_;
}
cnt++;
}
Eigen::Map<Eigen::Matrix<double, -1, -1>> mapMat(heights_.data(),
terrainProp_.xSamples,
terrainProp_.ySamples);
Eigen::Map<Eigen::Matrix<double, -1, 1>> mapVec(heights_.data(),
terrainProp_.xSamples * terrainProp_.ySamples,
1);
Eigen::MatrixXd transMat = mapMat.transpose();
Eigen::Map<Eigen::Matrix<double, -1, 1>> transVec(transMat.data(), terrainProp_.xSamples * terrainProp_.ySamples, 1);
mapVec = transVec;
for (size_t i = 0; i < terrainProp_.xSamples; i++)
{
for (size_t j = 0; j < terrainProp_.ySamples; j++)
{
double xidx = i * pixelSize_ - terrainProp_.xSize / 2;
double yidx = j * pixelSize_ - terrainProp_.ySize / 2;
heights_[j * terrainProp_.xSamples + i] += hm_->getHeight(xidx, yidx);
}
}
world_->removeObject(hm_);
hm_ = world_->addHeightMap(terrainProp_.ySamples,
terrainProp_.xSamples,
terrainProp_.ySize,
terrainProp_.xSize, terrainProp_.xSize / 2 - 0.6, 0.0, heights_, "terrain");
}
void randomize_sim_params()
{
if (randomize_friction)
{
double friction_list[6] = {0.5, 0.7, 0.9, 1.2, 1.5, 1.8};
// ground friction
friction = friction_list[std::rand() % 6]; // 1.0 + perturb_coeff * 0.9 * Eigen::VectorXd::Random(1)[0];
world_->setDefaultMaterial(friction, 0.0, 0.0);
}
else
{
friction = 0.8;
world_->setDefaultMaterial(friction, 0.0, 0.0);
}
if (randomize_gains)
{
// Resample Gains
pgain = pid_coeff + Eigen::VectorXd::Random(1)[0] * 5.;
dgain = 0.6 + Eigen::VectorXd::Random(1)[0] * 0.2;
Eigen::VectorXd jointPgain(gvDim_), jointDgain(gvDim_);
jointPgain.setZero();
jointPgain.tail(nJoints_).setConstant(pgain);
jointDgain.setZero();
jointDgain.tail(nJoints_).setConstant(dgain);
a1_->setPdGains(jointPgain, jointDgain);
}
else
{
pgain = pid_coeff;
dgain = 0.6;
Eigen::VectorXd jointPgain(gvDim_), jointDgain(gvDim_);
jointPgain.setZero();
jointPgain.tail(nJoints_).setConstant(pgain);
jointDgain.setZero();
jointDgain.tail(nJoints_).setConstant(dgain);
a1_->setPdGains(jointPgain, jointDgain);
}
if (randomize_mass)
{
// updated mass variation
auto mass_rand = 0.5 * (1. + Eigen::VectorXd::Random(1)[0]);
a1_->getMass()[0] = 6.0 + 2.0 * mass_rand;
Eigen::Vector3d com_vec = Eigen::VectorXd::Random(3);
com_vec(0) = 0.1 * com_vec(0);
com_vec(1) = 0.05 * com_vec(1);
com_vec(2) = 0.0;
a1_->getLinkCOM()[0] = com_vec;
a1_->updateMassInfo();
mass_params << mass_rand, com_vec(0), com_vec(1);
}
else
{
mass_params << 0.5, 0, 0;
}
if (randomize_motor_strength)
{
// resample motor strength
motor_strength = Eigen::VectorXd::Ones(12) - 0.1 * Eigen::VectorXd::Random(12);
}
else
{
motor_strength = Eigen::VectorXd::Ones(12);
}
}
void add_random_terrain()
{
isSlope = false;
sampleCmds = true;
useRef = true;
isDown = false;
raisim::TerrainProperties terrainProperties;
terrainProperties.frequency = 10; // 10
double zscale_val = 0.22; // 0.22
terrainProperties.zScale = zscale_val;
terrainProperties.xSize = 12; // maybe 12
terrainProperties.ySize = 12;
terrainProperties.xSamples = 200; // maybe 200
terrainProperties.ySamples = 200;
terrainProperties.fractalOctaves = 2;
terrainProperties.fractalLacunarity = 2.0;
terrainProperties.fractalGain = 0.25;
hm_ = world_->addHeightMap(Eigen::VectorXd::Random(1)[0] + 4, Eigen::VectorXd::Random(1)[0], terrainProperties); // maybe revisit
tparams[0] = 1;
tparams[1] = 0.;
tparams[2] = 0.;
// tparams[rand_freq] = 1;
}
void sample_goals()
{
double delta_max_speed, delta_ang_speed;
sample_goal_rand_num = Eigen::VectorXd::Random(1)[0];
upwardRewardCoeff_ = 0.0;
if (sample_goal_rand_num > 0.6)
{
delta_max_speed = -0.5 + 0.15 * (Eigen::VectorXd::Random(1)[0] / 2 + 0.5); // 0.
delta_ang_speed = 0.0 * ((std::rand() % 2) * 2 - 1) * (0.6); // 0.
actionRewardCoeff_ = -1.0;
upwardRewardCoeff_ = -3.0;
adaptiveForwardVelRewardCoeff_ = 2.0 * forwardVelRewardCoeff_;
adaptiveAngularVelRewardCoeff_ = 2.0 * angularVelRewardCoeff_;
}
else
{
delta_max_speed = -0.05 + 0.1 * Eigen::VectorXd::Random(1)[0]; // 0.35 ~ 0.55
delta_ang_speed = 0.4 * Eigen::VectorXd::Random(1)[0]; // -0.4 ~ 0.4
actionRewardCoeff_ = 0.;
adaptiveForwardVelRewardCoeff_ = forwardVelRewardCoeff_;
adaptiveAngularVelRewardCoeff_ = angularVelRewardCoeff_;
}
if (not sampleCmds)
{
adaptiveForwardVelRewardCoeff_ = forwardVelRewardCoeff_;
delta_max_speed = -0.05 + 0.05 * Eigen::VectorXd::Random(1)[0]; // 0.4 ~ 0.5
delta_ang_speed = 0.2 * Eigen::VectorXd::Random(1)[0]; // -0.2 ~ 0.2
}
max_speed = 0.5 + delta_max_speed;
ang_speed = 0.0 + delta_ang_speed;
speed_vec.setZero();
speed_vec << delta_max_speed, delta_ang_speed, delta_max_speed, delta_ang_speed;
if (isTest)
{
std::cout << "speed_vec: " << speed_vec[0] + 0.5 << ", " << speed_vec[1] << std::endl;
}
}
void compute_slope_info()
{
if (step_counter % 5 != 0)
return;
slope_dots.setZero(nFoot + 2*(num_g1-1));
if (not isSlope) return; // all zeros when on flat
double yaw = bodyOrientation_[2];
double cosy = std::cos(yaw);
double siny = std::sin(yaw);
double fx, fy, fz, bxi, byi, diff, tz, bxi_back, byi_back, tz_back, position_diff, fz_front;
int latest_position = 0;
std::vector<raisim::Vec<3>> foot_positions;
// Fill up foot position vector
for (int footIdx_i = 0; footIdx_i < nFoot; footIdx_i++)
{
raisim::Vec<3> footPosition;
a1_->getFramePosition(footFrame_[footIdx_i], footPosition);
foot_positions.push_back(footPosition);
}
// First add front points
for (int k = 0; k < num_g1; k++)
{
for (int footIdx_i = 0; footIdx_i < 2; footIdx_i++)
{
fx = foot_positions[footIdx_i][0];
fy = foot_positions[footIdx_i][1];
position_diff = g1_position[k];
bxi = fx + position_diff * cosy;
byi = fy + position_diff * siny;
bxi_back = fx + (position_diff - 0.05) * cosy;
byi_back = fy + (position_diff - 0.05) * siny;
tz = (hm_) ? hm_->getHeight(bxi, byi) : 0;
tz_back = (hm_) ? hm_->getHeight(bxi_back, byi_back) : 0;
diff = tz - tz_back;
if (abs(diff) < slope_th)
{
diff = 0;
}
slope_dots(latest_position) = diff;
if (isTest && visualizable_)
{
if (slope_dots(latest_position) == 0)
visual_scan_dots.at(latest_position)->color = {0, 1, 0, 1};
else
visual_scan_dots.at(latest_position)->color = {1, 0, 0, 1};
visual_scan_dots.at(latest_position)->setPosition(bxi, byi, tz);
}
latest_position++;
}
}
// Now add the slope below the robot
for (int footIdx_i = 2; footIdx_i < nFoot; footIdx_i++)
{
fx = foot_positions[footIdx_i][0];
fy = foot_positions[footIdx_i][1];
fz = (hm_) ? hm_->getHeight(fx, fy) : 0;
fz_front = (hm_) ? hm_->getHeight(foot_positions[footIdx_i-2][0],
foot_positions[footIdx_i-2][1]) : 0;
diff = fz - fz_front;
if (abs(diff) < slope_th)
{
diff = 0;
}
slope_dots(latest_position) = diff;
if (isTest && visualizable_)
{
if (slope_dots(latest_position) == 0)
visual_scan_dots.at(latest_position)->color = {0, 1, 0, 1};
else
visual_scan_dots.at(latest_position)->color = {1, 0, 0, 1};
visual_scan_dots.at(latest_position)->setPosition(fx, fy, fz);
}
latest_position++;
}
}
void reset(bool resample) final
{
if (isTest)
resample = true;
int change_terrain_freq = 100;
if (itr_number > start_itr_stairs)
change_terrain_freq = 50;
if (itr_number % change_terrain_freq == 0 || isTest)
{
if (hm_)
{
world_->removeObject(hm_);
int rand_terrain_select = 0;
if (itr_number > start_itr_stairs || isTest)
{
rand_terrain_select = std::rand() % 100; // 2 + 1; // either step or terrains
}
if (isEval) {
if (rand_terrain_select < 30) add_random_terrain();
else if (rand_terrain_select < 100) add_stairs();
} else {
if (rand_terrain_select < 40) add_random_terrain();
else if (rand_terrain_select < 100) add_stairs();
}
}
}
randomize_sim_params();
avgXYVel.setZero();
avgYawVel = 0;
step_counter = 0;
if (resample)
sample_goals();
gv_init_.setZero(gvDim_);
gv_init_ += 0.1 * Eigen::VectorXd::Random(gvDim_);
double z_ht = (hm_) ? hm_->getHeight(gc_init_[0], gc_init_[1]) : 0;
gc_init_[2] = z_ht + 0.4;
a1_->setState(gc_init_, gv_init_);
obs_history.clear();
act_history.clear();
jterr_history.clear();
// get to rest pos
pTarget_.tail(nJoints_) = Eigen::VectorXd::Zero(12) + actionMean_;
a1_->setPdTarget(pTarget_, vTarget_);
// Reset Slope Dots
slope_dots.setZero(nFoot + 2*(num_g1-1));
for (int i = 0; i < 50; i++)
{
if (server_)
server_->lockVisualizationServerMutex();
world_->integrate();
if (server_)
server_->unlockVisualizationServerMutex();
}
for (int j = 0; j < 50; j++)
act_history.push_back(Eigen::VectorXd::Zero(12));
for (int j = 0; j < 50; j++)
jterr_history.push_back(Eigen::VectorXd::Zero(12));
updateObservation();
updateObservation();
updateObservation();
sample_residual_goal_steps = std::rand() % 50;
sample_residual_env_steps = std::rand() % 10;
}
void curriculumUpdate()
{
cost_coeff = pow(cost_coeff, cost_decay_fac);
itr_number += 1;
}
void setSeed(int seed)
{
std::srand(seed);
for (int i = 0; i < 10; i++)
clean_randomizer = Eigen::VectorXd::Random(1)[0];
}
void applyExternalForceRandomly()
{
if (step_counter >= 200 && step_counter % 100 == 0)
{
Vec<3> extForce = 500 * Eigen::VectorXd::Random(3);
for (int i = 0; i < 2; i++)
{
auto fi = extForce[i];
extForce[i] = fi + (2.0 * (double)(fi > 0) - 1.0) * 400.0;
}
extForce[2] = 0.0;
a1_->setExternalForce(base_idx, extForce);
}
}
double find_max(Eigen::VectorXd &swing_bin, Eigen::VectorXd &grf)
{
double max_val = 0.;
for (int i = 0; i < nFoot; i++)
if (swing_bin[i] == 0 and grf[i] > max_val)
max_val = grf[i];
return max_val;
}
double find_min(Eigen::VectorXd &swing_bin, Eigen::VectorXd &grf)
{
double min_val = 100.0;
for (int i = 0; i < nFoot; i++)
if (swing_bin[i] == 0 and grf[i] < min_val)
min_val = grf[i];
if (min_val == 100.0)
return 0.;
else
return min_val;
}
double compute_forward_reward()
{
double r = 0.;
double forward_r = adaptiveForwardVelRewardCoeff_ * std::min(max_speed, bodyLinearVel_[0]);
// Do not go too fast, but track!
if (isDown && bodyLinearVel_[0] > (max_speed+0.1))
forward_r -= adaptiveForwardVelRewardCoeff_ * (bodyLinearVel_[0] - max_speed);
double angular_r = adaptiveAngularVelRewardCoeff_ * (-std::abs(ang_speed - bodyAngularVel_[2]) + std::abs(ang_speed));
r += forward_r;
r += -abs(bodyLinearVel_[1]);
r += angular_r;
r += (alive_bonus * 1. / (2. - (double)isSlope));
return r;
}
float step(const Eigen::Ref<EigenVec> &action_vec) final
{
step_counter += 1;
if (step_counter % (300 + sample_residual_goal_steps) == 300 + sample_residual_goal_steps - 1)
sample_goals();
if (step_counter % (50 + sample_residual_env_steps) == 50 + sample_residual_env_steps - 1)
randomize_sim_params();
act_history.push_back(action_vec.cast<double>());
auto action = act_history[act_history.size() - 3];
// mean std normalize action
pTarget12_ = action;
pTarget12_ = pTarget12_.cwiseProduct(motor_strength); // adding motor strength perturbation
pTarget12_ = pTarget12_.cwiseProduct(actionStd_);
pTarget12_ += actionMean_;
pTarget_.tail(nJoints_) = pTarget12_;
a1_->setPdTarget(pTarget_, vTarget_);
Eigen::Vector2d loc_xy_prev = gc_.segment(0, 3);
int rand_sim_steps = 0; // std::rand() % 3 - 1;
for (int i = 0; i < int(control_dt_ / simulation_dt_ + 1. * rand_sim_steps + 1e-10); i++)
{
if (server_)
server_->lockVisualizationServerMutex();
world_->integrate();
if (server_)
server_->unlockVisualizationServerMutex();
}