给定两点云,其中一点云是静态的,而另一点云是移动障碍。我们要移动空间中的移动点云障碍物,并记下它是否与静止点云在那个位置相交。在PCL中是否有可用的函数来自动完成此操作,还是我们必须编写自己的函数才能做到这一点?
发布于 2015-06-09 19:29:16
柔性碰撞库( fcl )库可以实现快速的碰撞检测。
以下是受支持的不同对象形状:
我假设你的点云是从物体表面抽取的样本,这些物体占据了三维空间中的体积。所以,你必须把你的点云转换成一个网格或者一个占用率八叉树。
发布于 2019-09-30 07:51:44
只是为了扩展@fferri关于如何使用fcl
(灵活冲突库)检查碰撞的答案。
1.从点云创建fcl::CollisionObject
。
这里我使用八叉树作为点云的概率表示。
std::shared_ptr<fcl::CollisionObject> createCollisionObject(const pcl::PointCloud<pcl::PointXYZ>::Ptr pointcloud_ptr, const octomap::point3d& sensor_origin_wrt_world)
{
// octomap octree settings
const double resolution = 0.01;
const double prob_hit = 0.9;
const double prob_miss = 0.1;
const double clamping_thres_min = 0.12;
const double clamping_thres_max = 0.98;
std::shared_ptr<octomap::OcTree> octomap_octree = std::make_shared<octomap::OcTree>(resolution);
octomap_octree->setProbHit(prob_hit);
octomap_octree->setProbMiss(prob_miss);
octomap_octree->setClampingThresMin(clamping_thres_min);
octomap_octree->setClampingThresMax(clamping_thres_max);
octomap::KeySet free_cells;
octomap::KeySet occupied_cells;
#if defined(_OPENMP)
#pragma omp parallel
#endif
{
#if defined(_OPENMP)
auto thread_id = omp_get_thread_num();
auto thread_num = omp_get_num_threads();
#else
int thread_id = 0;
int thread_num = 1;
#endif
int start_idx = static_cast<int>(pointcloud_ptr->size() / thread_num) * thread_id;
int end_idx = static_cast<int>(pointcloud_ptr->size() / thread_num) * (thread_id + 1);
if (thread_id == thread_num - 1)
{
end_idx = pointcloud_ptr->size();
}
octomap::KeySet local_free_cells;
octomap::KeySet local_occupied_cells;
for (auto i = start_idx; i < end_idx; i++)
{
octomap::point3d point((*pointcloud_ptr)[i].x, (*pointcloud_ptr)[i].y, (*pointcloud_ptr)[i].z);
octomap::KeyRay key_ray;
if (octomap_octree->computeRayKeys(sensor_origin_3d, point, key_ray))
{
local_free_cells.insert(key_ray.begin(), key_ray.end());
}
octomap::OcTreeKey tree_key;
if (octomap_octree->coordToKeyChecked(point, tree_key))
{
local_occupied_cells.insert(tree_key);
}
}
#if defined(_OPENMP)
#pragma omp critical
#endif
{
free_cells.insert(local_free_cells.begin(), local_free_cells.end());
occupied_cells.insert(local_occupied_cells.begin(), local_occupied_cells.end());
}
}
// free cells only if not occupied in this cloud
for (auto it = free_cells.begin(); it != free_cells.end(); ++it)
{
if (occupied_cells.find(*it) == occupied_cells.end())
{
octomap_octree->updateNode(*it, false);
}
}
// occupied cells
for (auto it = occupied_cells.begin(); it != occupied_cells.end(); ++it)
{
octomap_octree->updateNode(*it, true);
}
auto fcl_octree = std::make_shared<fcl::OcTree>(octomap_octree);
std::shared_ptr<fcl::CollisionGeometry> fcl_geometry = fcl_octree;
return std::make_shared<fcl::CollisionObject>(fcl_geometry);
}
正如@fferri在评论中所说,您还可以使用pcl
中的三角剖分函数从点云创建网格。但是,您应该知道GJK/EPA算法不能支持凹对象。因此,正确地说,在使用CGAL进行碰撞检测之前,您可能需要通过凸分解(例如可以使用fcl
)处理网格。
2.运动障碍物与静止点云之间的连续碰撞检测。
不幸的是,目前在fcl
中实现的CCD接口没有完全支持八叉树/点云(甚至是天真的CCD解决程序)。但您可以通过下列任何一种方法来解决这个问题:
https://stackoverflow.com/questions/30741008
复制相似问题