use crate::{ astar::{Astar, PathResult}, terrain::Block, vol::{BaseVol, ReadVol}, }; use common_base::span; use hashbrown::hash_map::DefaultHashBuilder; #[cfg(rrt_pathfinding)] use hashbrown::HashMap; #[cfg(rrt_pathfinding)] use kiddo::{distance::squared_euclidean, KdTree}; // For RRT paths (disabled for now) #[cfg(rrt_pathfinding)] use rand::distributions::Uniform; use rand::{thread_rng, Rng}; #[cfg(rrt_pathfinding)] use std::f32::consts::PI; use std::iter::FromIterator; use vek::*; // Path #[derive(Clone, Debug)] pub struct Path { nodes: Vec, } impl Default for Path { fn default() -> Self { Self { nodes: Vec::default(), } } } impl FromIterator for Path { fn from_iter>(iter: I) -> Self { Self { nodes: iter.into_iter().collect(), } } } impl IntoIterator for Path { type IntoIter = std::vec::IntoIter; type Item = T; fn into_iter(self) -> Self::IntoIter { self.nodes.into_iter() } } impl Path { pub fn is_empty(&self) -> bool { self.nodes.is_empty() } pub fn len(&self) -> usize { self.nodes.len() } pub fn iter(&self) -> impl Iterator { self.nodes.iter() } pub fn start(&self) -> Option<&T> { self.nodes.first() } pub fn end(&self) -> Option<&T> { self.nodes.last() } pub fn nodes(&self) -> &[T] { &self.nodes } } // Route: A path that can be progressed along #[derive(Default, Clone, Debug)] pub struct Route { path: Path>, next_idx: usize, } impl From>> for Route { fn from(path: Path>) -> Self { Self { path, next_idx: 0 } } } pub struct TraversalConfig { /// The distance to a node at which node is considered visited. pub node_tolerance: f32, /// The slowdown factor when following corners. /// 0.0 = no slowdown on corners, 1.0 = total slowdown on corners. pub slow_factor: f32, /// Whether the agent is currently on the ground. pub on_ground: bool, /// Whether the agent is currently in water. pub in_liquid: bool, /// The distance to the target below which it is considered reached. pub min_tgt_dist: f32, /// Whether the agent can climb. pub can_climb: bool, /// Whether the agent can fly. pub can_fly: bool, } const DIAGONALS: [Vec2; 8] = [ Vec2::new(1, 0), Vec2::new(1, 1), Vec2::new(0, 1), Vec2::new(-1, 1), Vec2::new(-1, 0), Vec2::new(-1, -1), Vec2::new(0, -1), Vec2::new(1, -1), ]; impl Route { pub fn path(&self) -> &Path> { &self.path } pub fn next(&self, i: usize) -> Option> { self.path.nodes.get(self.next_idx + i).copied() } pub fn is_finished(&self) -> bool { self.next(0).is_none() } pub fn traverse( &mut self, vol: &V, pos: Vec3, vel: Vec3, traversal_cfg: &TraversalConfig, ) -> Option<(Vec3, f32)> where V: BaseVol + ReadVol, { let (next0, next1, next_tgt, be_precise) = loop { // If we've reached the end of the path, stop self.next(0)?; let next0 = self .next(0) .unwrap_or_else(|| pos.map(|e| e.floor() as i32)); let next1 = self.next(1).unwrap_or(next0); // Stop using obstructed paths if !walkable(vol, next1) { return None; } let be_precise = DIAGONALS.iter().any(|pos| { (-1..2).all(|z| { vol.get(next0 + Vec3::new(pos.x, pos.y, z)) .map(|b| !b.is_solid()) .unwrap_or(false) }) }); // Map position of node to middle of block let next_tgt = next0.map(|e| e as f32) + Vec3::new(0.5, 0.5, 0.0); let closest_tgt = next_tgt.map2(pos, |tgt, pos| pos.clamped(tgt.floor(), tgt.ceil())); // Determine whether we're close enough to the next to to consider it completed let dist_sqrd = pos.xy().distance_squared(closest_tgt.xy()); if dist_sqrd < traversal_cfg.node_tolerance.powi(2) * if be_precise { 0.25 } else { 1.0 } && (((pos.z - closest_tgt.z > 1.2 || (pos.z - closest_tgt.z > -0.2 && traversal_cfg.on_ground)) && (pos.z - closest_tgt.z < 1.2 || (pos.z - closest_tgt.z < 2.9 && vel.z < -0.05)) && vel.z <= 0.0 // Only consider the node reached if there's nothing solid between us and it && (vol .ray(pos + Vec3::unit_z() * 1.5, closest_tgt + Vec3::unit_z() * 1.5) .until(Block::is_solid) .cast() .0 > pos.distance(closest_tgt) * 0.9 || dist_sqrd < 0.5) && self.next_idx < self.path.len()) || (traversal_cfg.in_liquid && pos.z < closest_tgt.z + 0.8 && pos.z > closest_tgt.z)) { // Node completed, move on to the next one self.next_idx += 1; } else { // The next node hasn't been reached yet, use it as a target break (next0, next1, next_tgt, be_precise); } }; fn gradient(line: LineSegment2) -> f32 { let r = (line.start.y - line.end.y) / (line.start.x - line.end.x); if r.is_nan() { 100000.0 } else { r } } fn intersect(a: LineSegment2, b: LineSegment2) -> Option> { let ma = gradient(a); let mb = gradient(b); let ca = a.start.y - ma * a.start.x; let cb = b.start.y - mb * b.start.x; if (ma - mb).abs() < 0.0001 || (ca - cb).abs() < 0.0001 { None } else { let x = (cb - ca) / (ma - mb); let y = ma * x + ca; Some(Vec2::new(x, y)) } } // We don't always want to aim for the centre of block since this can create // jerky zig-zag movement. This function attempts to find a position // inside a target block's area that aligned nicely with our velocity. // This has a twofold benefit: // // 1. Entities can move at any angle when // running on a flat surface // // 2. We don't have to search diagonals when // pathfinding - cartesian positions are enough since this code will // make the entity move smoothly along them let corners = [ Vec2::new(0, 0), Vec2::new(1, 0), Vec2::new(1, 1), Vec2::new(0, 1), Vec2::new(0, 0), // Repeated start ]; let vel_line = LineSegment2 { start: pos.xy(), end: pos.xy() + vel.xy() * 100.0, }; let align = |block_pos: Vec3, precision: f32| { let lerp_block = |x, precision| Lerp::lerp(x, block_pos.xy().map(|e| e as f32), precision); (0..4) .filter_map(|i| { let edge_line = LineSegment2 { start: lerp_block( (block_pos.xy() + corners[i]).map(|e| e as f32), precision, ), end: lerp_block( (block_pos.xy() + corners[i + 1]).map(|e| e as f32), precision, ), }; intersect(vel_line, edge_line).filter(|intersect| { intersect .clamped( block_pos.xy().map(|e| e as f32), block_pos.xy().map(|e| e as f32 + 1.0), ) .distance_squared(*intersect) < 0.001 }) }) .min_by_key(|intersect: &Vec2| { (intersect.distance_squared(vel_line.end) * 1000.0) as i32 }) .unwrap_or_else(|| { (0..2) .flat_map(|i| (0..2).map(move |j| Vec2::new(i, j))) .map(|rpos| block_pos + rpos) .map(|block_pos| { let block_posf = block_pos.xy().map(|e| e as f32); let proj = vel_line.projected_point(block_posf); let clamped = lerp_block( proj.clamped( block_pos.xy().map(|e| e as f32), block_pos.xy().map(|e| e as f32), ), precision, ); (proj.distance_squared(clamped), clamped) }) .min_by_key(|(d2, _)| (d2 * 1000.0) as i32) .unwrap() .1 }) }; let bez = CubicBezier2 { start: pos.xy(), ctrl0: pos.xy() + vel.xy().try_normalized().unwrap_or_default() * 1.0, ctrl1: align(next0, 1.0), end: align(next1, 1.0), }; // Use a cubic spline of the next few targets to come up with a sensible target // position. We want to use a position that gives smooth movement but is // also accurate enough to avoid the agent getting stuck under ledges or // falling off walls. let next_dir = bez .evaluate_derivative(0.85) .try_normalized() .unwrap_or_default(); let straight_factor = next_dir .dot(vel.xy().try_normalized().unwrap_or(next_dir)) .max(0.0) .powi(2); let bez = CubicBezier2 { start: pos.xy(), ctrl0: pos.xy() + vel.xy().try_normalized().unwrap_or_default() * 1.0, ctrl1: align( next0, (1.0 - if (next0.z as f32 - pos.z).abs() < 0.25 && !be_precise { straight_factor } else { 0.0 }) .max(0.1), ), end: align(next1, 1.0), }; let tgt2d = bez.evaluate(if (next0.z as f32 - pos.z).abs() < 0.25 { 0.25 } else { 0.5 }); let tgt = if be_precise { next_tgt } else { Vec3::from(tgt2d) + Vec3::unit_z() * next_tgt.z }; Some(( tgt - pos, // Control the entity's speed to hopefully stop us falling off walls on sharp // corners. This code is very imperfect: it does its best but it // can still fail for particularly fast entities. straight_factor * traversal_cfg.slow_factor + (1.0 - traversal_cfg.slow_factor), )) .filter(|(bearing, _)| bearing.z < 2.1) } } /// A self-contained system that attempts to chase a moving target, only /// performing pathfinding if necessary #[derive(Default, Clone, Debug)] pub struct Chaser { last_search_tgt: Option>, /// `bool` indicates whether the Route is a complete route to the target route: Option<(Route, bool)>, /// We use this hasher (AAHasher) because: /// (1) we care about DDOS attacks (ruling out FxHash); /// (2) we don't care about determinism across computers (we can use /// AAHash). astar: Option, DefaultHashBuilder>>, } impl Chaser { /// Returns bearing and speed /// Bearing is a Vec3 dictating the direction of movement /// Speed is an f32 between 0.0 and 1.0 pub fn chase( &mut self, vol: &V, pos: Vec3, vel: Vec3, tgt: Vec3, traversal_cfg: TraversalConfig, ) -> Option<(Vec3, f32)> where V: BaseVol + ReadVol, { span!(_guard, "chase", "Chaser::chase"); let pos_to_tgt = pos.distance(tgt); // If we're already close to the target then there's nothing to do let end = self .route .as_ref() .and_then(|(r, _)| r.path.end().copied()) .map(|e| e.map(|e| e as f32 + 0.5)) .unwrap_or(tgt); if ((pos - end) * Vec3::new(1.0, 1.0, 2.0)).magnitude_squared() < traversal_cfg.min_tgt_dist.powi(2) { self.route = None; return None; } let bearing = if let Some((end, complete)) = self .route .as_ref() .and_then(|(r, complete)| Some((r.path().end().copied()?, *complete))) { let end_to_tgt = end.map(|e| e as f32).distance(tgt); // If the target has moved significantly since the path was generated then it's // time to search for a new path. Also, do this randomly from time // to time to avoid any edge cases that cause us to get stuck. In // theory this shouldn't happen, but in practice the world is full // of unpredictable obstacles that are more than willing to mess up // our day. TODO: Come up with a better heuristic for this if (end_to_tgt > pos_to_tgt * 0.3 + 5.0 && complete) || thread_rng().gen::() < 0.001 { None } else { self.route .as_mut() .and_then(|(r, _)| r.traverse(vol, pos, vel, &traversal_cfg)) } } else { // There is no route found yet None }; // If a bearing has already been determined, use that if let Some((bearing, speed)) = bearing { Some((bearing, speed)) } else { // Since no bearing has been determined yet, a new route will be // calculated if the target has moved, pathfinding is not complete, // or there is no route let tgt_dir = (tgt - pos).xy().try_normalized().unwrap_or_default(); // Only search for a path if the target has moved from their last position. We // don't want to be thrashing the pathfinding code for targets that // we're unable to access! if self .last_search_tgt .map(|last_tgt| last_tgt.distance(tgt) > pos_to_tgt * 0.15 + 5.0) .unwrap_or(true) || self.astar.is_some() || self.route.is_none() { self.last_search_tgt = Some(tgt); // NOTE: Enable air paths when air braking has been figured out let (path, complete) = /*if cfg!(rrt_pathfinding) && traversal_cfg.can_fly { find_air_path(vol, pos, tgt, &traversal_cfg) } else */{ find_path(&mut self.astar, vol, pos, tgt, &traversal_cfg) }; self.route = path.map(|path| { let start_index = path .iter() .enumerate() .min_by_key(|(_, node)| { node.xy() .map(|e| e as f32) .distance_squared(pos.xy() + tgt_dir) as i32 }) .map(|(idx, _)| idx); ( Route { path, next_idx: start_index.unwrap_or(0), }, complete, ) }); } // Start traversing the new route if it exists if let Some(bearing) = self .route .as_mut() .and_then(|(r, _)| r.traverse(vol, pos, vel, &traversal_cfg)) { Some(bearing) } else { // At this point no route is available and no bearing // has been determined, so we start sampling terrain. // Check for falling off walls and try moving straight // towards the target if falling is not a danger let walking_towards_edge = (-3..2).all(|z| { vol.get( (pos + Vec3::::from(tgt_dir) * 2.5).map(|e| e as i32) + Vec3::unit_z() * z, ) .map(|b| b.is_air()) .unwrap_or(false) }); // Enable when airbraking/flight is figured out /*if traversal_cfg.can_fly { Some(((tgt - pos) , 1.0)) } else */ if !walking_towards_edge || traversal_cfg.can_fly { Some(((tgt - pos) * Vec3::new(1.0, 1.0, 0.0), 1.0)) } else { // This is unfortunately where an NPC will stare blankly // into space. No route has been found and no temporary // bearing would suffice. Hopefully a route will be found // in the coming ticks. None } } } } } fn walkable(vol: &V, pos: Vec3) -> bool where V: BaseVol + ReadVol, { let below = vol .get(pos - Vec3::unit_z()) .ok() .copied() .unwrap_or_else(Block::empty); let a = vol.get(pos).ok().copied().unwrap_or_else(Block::empty); let b = vol .get(pos + Vec3::unit_z()) .ok() .copied() .unwrap_or_else(Block::empty); let on_ground = below.is_filled(); let in_liquid = a.is_liquid(); (on_ground || in_liquid) && !a.is_solid() && !b.is_solid() } /// Attempt to search for a path to a target, returning the path (if one was /// found) and whether it is complete (reaches the target) fn find_path( astar: &mut Option, DefaultHashBuilder>>, vol: &V, startf: Vec3, endf: Vec3, traversal_cfg: &TraversalConfig, ) -> (Option>>, bool) where V: BaseVol + ReadVol, { let is_walkable = |pos: &Vec3| walkable(vol, *pos); let get_walkable_z = |pos| { let mut z_incr = 0; for _ in 0..32 { let test_pos = pos + Vec3::unit_z() * z_incr; if is_walkable(&test_pos) { return Some(test_pos); } z_incr = -z_incr + if z_incr <= 0 { 1 } else { 0 }; } None }; let (start, end) = match ( get_walkable_z(startf.map(|e| e.floor() as i32)), get_walkable_z(endf.map(|e| e.floor() as i32)), ) { (Some(start), Some(end)) => (start, end), _ => return (None, false), }; let heuristic = |pos: &Vec3| (pos.distance_squared(end) as f32).sqrt(); let neighbors = |pos: &Vec3| { let pos = *pos; const DIRS: [Vec3; 17] = [ Vec3::new(0, 1, 0), // Forward Vec3::new(0, 1, 1), // Forward upward Vec3::new(0, 1, -1), // Forward downward Vec3::new(0, 1, -2), // Forward downwardx2 Vec3::new(1, 0, 0), // Right Vec3::new(1, 0, 1), // Right upward Vec3::new(1, 0, -1), // Right downward Vec3::new(1, 0, -2), // Right downwardx2 Vec3::new(0, -1, 0), // Backwards Vec3::new(0, -1, 1), // Backward Upward Vec3::new(0, -1, -1), // Backward downward Vec3::new(0, -1, -2), // Backward downwardx2 Vec3::new(-1, 0, 0), // Left Vec3::new(-1, 0, 1), // Left upward Vec3::new(-1, 0, -1), // Left downward Vec3::new(-1, 0, -2), // Left downwardx2 Vec3::new(0, 0, -1), // Downwards ]; const JUMPS: [Vec3; 4] = [ Vec3::new(0, 1, 2), // Forward Upwardx2 Vec3::new(1, 0, 2), // Right Upwardx2 Vec3::new(0, -1, 2), // Backward Upwardx2 Vec3::new(-1, 0, 2), // Left Upwardx2 ]; // let walkable = [ // is_walkable(&(pos + Vec3::new(1, 0, 0))), // is_walkable(&(pos + Vec3::new(-1, 0, 0))), // is_walkable(&(pos + Vec3::new(0, 1, 0))), // is_walkable(&(pos + Vec3::new(0, -1, 0))), // ]; // const DIAGONALS: [(Vec3, [usize; 2]); 8] = [ // (Vec3::new(1, 1, 0), [0, 2]), // (Vec3::new(-1, 1, 0), [1, 2]), // (Vec3::new(1, -1, 0), [0, 3]), // (Vec3::new(-1, -1, 0), [1, 3]), // (Vec3::new(1, 1, 1), [0, 2]), // (Vec3::new(-1, 1, 1), [1, 2]), // (Vec3::new(1, -1, 1), [0, 3]), // (Vec3::new(-1, -1, 1), [1, 3]), // ]; DIRS.iter() .chain( Some(JUMPS.iter()) .filter(|_| { vol.get(pos - Vec3::unit_z()) .map(|b| !b.is_liquid()) .unwrap_or(true) || traversal_cfg.can_climb || traversal_cfg.can_fly }) .into_iter() .flatten(), ) .map(move |dir| (pos, dir)) .filter(move |(pos, dir)| { (traversal_cfg.can_fly || is_walkable(pos) && is_walkable(&(*pos + **dir))) && ((dir.z < 1 || vol .get(pos + Vec3::unit_z() * 2) .map(|b| !b.is_solid()) .unwrap_or(true)) && (dir.z < 2 || vol .get(pos + Vec3::unit_z() * 3) .map(|b| !b.is_solid()) .unwrap_or(true)) && (dir.z >= 0 || vol .get(pos + *dir + Vec3::unit_z() * 2) .map(|b| !b.is_solid()) .unwrap_or(true))) }) .map(move |(pos, dir)| pos + dir) // .chain( // DIAGONALS // .iter() // .filter(move |(dir, [a, b])| { // is_walkable(&(pos + *dir)) && walkable[*a] && // walkable[*b] }) // .map(move |(dir, _)| pos + *dir), // ) }; let transition = |a: &Vec3, b: &Vec3| { let crow_line = LineSegment2 { start: startf.xy(), end: endf.xy(), }; // Modify the heuristic a little in order to prefer paths that take us on a // straight line toward our target. This means we get smoother movement. 1.0 + crow_line.distance_to_point(b.xy().map(|e| e as f32)) * 0.025 + (b.z - a.z - 1).max(0) as f32 * 10.0 }; let satisfied = |pos: &Vec3| pos == &end; let mut new_astar = match astar.take() { None => Astar::new(25_000, start, heuristic, DefaultHashBuilder::default()), Some(astar) => astar, }; let path_result = new_astar.poll(100, heuristic, neighbors, transition, satisfied); *astar = Some(new_astar); match path_result { PathResult::Path(path) => { *astar = None; (Some(path), true) }, PathResult::None(path) => { *astar = None; (Some(path), false) }, PathResult::Exhausted(path) => { *astar = None; (Some(path), false) }, PathResult::Pending => (None, false), } } // Enable when airbraking/sensible flight is a thing #[cfg(rrt_pathfinding)] fn find_air_path( vol: &V, startf: Vec3, endf: Vec3, traversal_cfg: &TraversalConfig, ) -> (Option>>, bool) where V: BaseVol + ReadVol, { let radius = traversal_cfg.node_tolerance; let mut connect = false; let total_dist_sqrd = startf.distance_squared(endf); // First check if a straight line path works if vol .ray(startf + Vec3::unit_z(), endf + Vec3::unit_z()) .until(Block::is_opaque) .cast() .0 .powi(2) >= total_dist_sqrd { let mut path = Vec::new(); path.push(endf.map(|e| e.floor() as i32)); connect = true; (Some(path.into_iter().collect()), connect) // Else use RRTs } else { let is_traversable = |start: &Vec3, end: &Vec3| { vol.ray(*start, *end) .until(Block::is_solid) .cast() .0 .powi(2) > (*start).distance_squared(*end) //vol.get(*pos).ok().copied().unwrap_or_else(Block::empty). // is_fluid(); }; informed_rrt_connect(start, end, is_traversable) } } /// Attempts to find a path from a start to the end using an informed /// RRT-Connect algorithm. A point is sampled from a bounding spheroid /// between the start and end. Two separate rapidly exploring random /// trees extend toward the sampled point. Nodes are stored in k-d trees /// for quicker nearest node calculations. Points are sampled until the /// trees connect. A final path is then reconstructed from the nodes. /// This pathfinding algorithm is more appropriate for 3D pathfinding /// with wider gaps, such as flying through a forest than for terrain /// with narrow gaps, such as navigating a maze. /// Returns a path and whether that path is complete or not. #[cfg(rrt_pathfinding)] fn informed_rrt_connect( start: Vec3, end: Vec3, is_valid_edge: impl Fn(&Vec3, &Vec3) -> bool, ) -> (Option>>, bool) { let mut path = Vec::new(); // Each tree has a vector of nodes let mut node_index1: usize = 0; let mut node_index2: usize = 0; let mut nodes1 = Vec::new(); let mut nodes2 = Vec::new(); // The parents hashmap stores nodes and their parent nodes as pairs to // retrace the complete path once the two RRTs connect let mut parents1 = HashMap::new(); let mut parents2 = HashMap::new(); // The path vector stores the path from the appropriate terminal to the // connecting node or vice versa let mut path1 = Vec::new(); let mut path2 = Vec::new(); // K-d trees are used to find the closest nodes rapidly let mut kdtree1 = KdTree::new(); let mut kdtree2 = KdTree::new(); // Add the start as the first node of the first k-d tree kdtree1 .add(&[startf.x, startf.y, startf.z], node_index1) .unwrap_or_default(); nodes1.push(startf); node_index1 += 1; // Add the end as the first node of the second k-d tree kdtree2 .add(&[endf.x, endf.y, endf.z], node_index2) .unwrap_or_default(); nodes2.push(endf); node_index2 += 1; let mut connection1_idx = 0; let mut connection2_idx = 0; let mut connect = false; // Scalar non-dimensional value that is proportional to the size of the // sample spheroid volume. This increases in value until a path is found. let mut search_parameter = 0.01; // Maximum of 7000 iterations for _i in 0..7000 { if connect { break; } // Sample a point on the bounding spheroid let (sampled_point1, sampled_point2) = { let point = point_on_prolate_spheroid(startf, endf, search_parameter); (point, point) }; // Find the nearest nodes to the the sampled point let nearest_index1 = kdtree1 .nearest_one( &[sampled_point1.x, sampled_point1.y, sampled_point1.z], &squared_euclidean, ) .map_or(0, |n| *n.1); let nearest_index2 = kdtree2 .nearest_one( &[sampled_point2.x, sampled_point2.y, sampled_point2.z], &squared_euclidean, ) .map_or(0, |n| *n.1); let nearest1 = nodes1[nearest_index1]; let nearest2 = nodes2[nearest_index2]; // Extend toward the sampled point from the nearest node of each tree let new_point1 = nearest1 + (sampled_point1 - nearest1).normalized().map(|a| a * radius); let new_point2 = nearest2 + (sampled_point2 - nearest2).normalized().map(|a| a * radius); // Ensure the new nodes are valid/traversable if is_valid_edge(&nearest1, &new_point1) { kdtree1 .add(&[new_point1.x, new_point1.y, new_point1.z], node_index1) .unwrap_or_default(); nodes1.push(new_point1); parents1.insert(node_index1, nearest_index1); node_index1 += 1; // Check if the trees connect if let Ok((check, index)) = kdtree2.nearest_one( &[new_point1.x, new_point1.y, new_point1.z], &squared_euclidean, ) { if check < radius { let connection = nodes2[*index]; connection2_idx = *index; nodes1.push(connection); connection1_idx = nodes1.len() - 1; parents1.insert(node_index1, node_index1 - 1); connect = true; } } } // Repeat the validity check for the second tree if is_valid_edge(&nearest2, &new_point2) { kdtree2 .add(&[new_point2.x, new_point2.y, new_point1.z], node_index2) .unwrap_or_default(); nodes2.push(new_point2); parents2.insert(node_index2, nearest_index2); node_index2 += 1; // Again check for a connection if let Ok((check, index)) = kdtree1.nearest_one( &[new_point2.x, new_point2.y, new_point1.z], &squared_euclidean, ) { if check < radius { let connection = nodes1[*index]; connection1_idx = *index; nodes2.push(connection); connection2_idx = nodes2.len() - 1; parents2.insert(node_index2, node_index2 - 1); connect = true; } } } // Increase the search parameter to widen the sample volume search_parameter += 0.02; } if connect { // Construct paths from the connection node to the start and end let mut current_node_index1 = connection1_idx; while current_node_index1 > 0 { current_node_index1 = *parents1.get(¤t_node_index1).unwrap_or(&0); path1.push(nodes1[current_node_index1].map(|e| e.floor() as i32)); } let mut current_node_index2 = connection2_idx; while current_node_index2 > 0 { current_node_index2 = *parents2.get(¤t_node_index2).unwrap_or(&0); path2.push(nodes2[current_node_index2].map(|e| e.floor() as i32)); } // Join the two paths together in the proper order and remove duplicates path1.pop(); path1.reverse(); path.append(&mut path1); path.append(&mut path2); path.dedup(); } else { // If the trees did not connect, construct a path from the start to // the closest node to the end let mut current_node_index1 = kdtree1 .nearest_one(&[endf.x, endf.y, endf.z], &squared_euclidean) .map_or(0, |c| *c.1); // Attempt to pick a node other than the start node for _i in 0..3 { if current_node_index1 == 0 || nodes1[current_node_index1].distance_squared(startf) < 4.0 { if let Some(index) = parents1.values().choose(&mut thread_rng()) { current_node_index1 = *index; } else { break; } } else { break; } } path1.push(nodes1[current_node_index1].map(|e| e.floor() as i32)); // Construct the path while current_node_index1 != 0 && nodes1[current_node_index1].distance_squared(startf) > 4.0 { current_node_index1 = *parents1.get(¤t_node_index1).unwrap_or(&0); path1.push(nodes1[current_node_index1].map(|e| e.floor() as i32)); } path1.reverse(); path.append(&mut path1); } let mut new_path = Vec::new(); let mut node = path[0]; new_path.push(node); let mut node_idx = 0; let num_nodes = path.len(); let end = path[num_nodes - 1]; while node != end { let next_idx = if node_idx + 4 > num_nodes - 1 { num_nodes - 1 } else { node_idx + 4 }; let next_node = path[next_idx]; let start_pos = node.map(|e| e as f32 + 0.5); let end_pos = next_node.map(|e| e as f32 + 0.5); if vol .ray(start_pos, end_pos) .until(Block::is_solid) .cast() .0 .powi(2) > (start_pos).distance_squared(end_pos) { node_idx = next_idx; new_path.push(next_node); } else { node_idx += 1; } node = path[node_idx]; } path = new_path; } /// Returns a random point within a radially symmetrical ellipsoid with given /// foci and a `search parameter` to determine the size of the ellipse beyond /// the foci. Technically the point is within a prolate spheroid translated and /// rotated to the proper place in cartesian space. /// The search_parameter is a float that relates to the length of the string for /// a two dimensional ellipse or the size of the ellipse beyond the foci. In /// this case that analogy still holds as the ellipse is radially symmetrical /// along the axis between the foci. The value of the search parameter must be /// greater than zero. In order to increase the sample area, the /// search_parameter should be increased linearly as the search continues. #[cfg(rrt_pathfinding)] pub fn point_on_prolate_spheroid( focus1: Vec3, focus2: Vec3, search_parameter: f32, ) -> Vec3 { let mut rng = thread_rng(); // Uniform distribution let range = Uniform::from(0.0..1.0); // Midpoint is used as the local origin let midpoint = 0.5 * (focus1 + focus2); // Radius between the start and end of the path let radius: f32 = focus1.distance(focus2); // The linear eccentricity of an ellipse is the distance from the origin to a // focus A prolate spheroid is a half-ellipse rotated for a full revolution // which is why ellipse variables are used frequently in this function let linear_eccentricity: f32 = 0.5 * radius; // For an ellipsoid, three variables determine the shape: a, b, and c. // These are the distance from the center/origin to the surface on the // x, y, and z axes, respectively. // For a prolate spheroid a and b are equal. // c is determined by adding the search parameter to the linear eccentricity. // As the search parameter increases the size of the spheroid increases let c: f32 = linear_eccentricity + search_parameter; // The width is calculated to prioritize increasing width over length of // the ellipsoid let a: f32 = (c.powi(2) - linear_eccentricity.powi(2)).powf(0.5); // The width should be the same in both the x and y directions let b: f32 = a; // The parametric spherical equation for an ellipsoid measuring from the // center point is as follows: // x = a * cos(theta) * cos(lambda) // y = b * cos(theta) * sin(lambda) // z = c * sin(theta) // // where -0.5 * PI <= theta <= 0.5 * PI // and 0.0 <= lambda < 2.0 * PI // // Select these two angles using the uniform distribution defined at the // beginning of the function from 0.0 to 1.0 let rtheta: f32 = PI * range.sample(&mut rng) - 0.5 * PI; let lambda: f32 = 2.0 * PI * range.sample(&mut rng); // Select a point on the surface of the ellipsoid let point = Vec3::new( a * rtheta.cos() * lambda.cos(), b * rtheta.cos() * lambda.sin(), c * rtheta.sin(), ); // NOTE: Theoretically we should sample a point within the spheroid // requiring selecting a point along the radius. In my tests selecting // a point *on the surface* of the spheroid results in sampling that is // "good enough". The following code is commented out to reduce expense. //let surface_point = Vec3::new(a * rtheta.cos() * lambda.cos(), b * // rtheta.cos() * lambda.sin(), c * rtheta.sin()); let magnitude = // surface_point.magnitude(); let direction = surface_point.normalized(); //// Randomly select a point along the vector to the previously selected surface //// point using the uniform distribution //let point = magnitude * range.sample(&mut rng) * direction; // Now that a point has been selected in local space, it must be rotated and // translated into global coordinates // NOTE: Don't rotate about the z axis as the point is already randomly // selected about the z axis //let dx = focus2.x - focus1.x; //let dy = focus2.y - focus1.y; let dz = focus2.z - focus1.z; // Phi and theta are the angles from the x axis in the x-y plane and from // the z axis, respectively. (As found in spherical coordinates) // These angles are used to rotate the random point in the spheroid about // the local origin // // Rotate about z axis by phi //let phi: f32 = if dx.abs() > 0.0 { // (dy / dx).atan() //} else { // 0.5 * PI //}; // This is unnecessary as rtheta is randomly selected between 0.0 and 2.0 * PI // let rot_z_mat = Mat3::new(phi.cos(), -1.0 * phi.sin(), 0.0, phi.sin(), // phi.cos(), 0.0, 0.0, 0.0, 1.0); // Rotate about perpendicular vector in the xy plane by theta let theta: f32 = if radius > 0.0 { (dz / radius).acos() } else { 0.0 }; // Vector from focus1 to focus2 let r_vec = focus2 - focus1; // Perpendicular vector in xy plane let perp_vec = Vec3::new(-1.0 * r_vec.y, r_vec.x, 0.0).normalized(); let l = perp_vec.x; let m = perp_vec.y; let n = perp_vec.z; // Rotation matrix for rotation about a vector let rot_2_mat = Mat3::new( l * l * (1.0 - theta.cos()), m * l * (1.0 - theta.cos()) - n * theta.sin(), n * l * (1.0 - theta.cos()) + m * theta.sin(), l * m * (1.0 - theta.cos()) + n * theta.sin(), m * m * (1.0 - theta.cos()) + theta.cos(), n * m * (1.0 - theta.cos()) - l * theta.sin(), l * n * (1.0 - theta.cos()) - m * theta.sin(), m * n * (1.0 - theta.cos()) + l * theta.sin(), n * n * (1.0 - theta.cos()) + theta.cos(), ); // Get the global coordinates of the point by rotating and adding the origin // rot_z_mat is unneeded due to the random rotation defined by lambda // let global_coords = midpoint + rot_2_mat * (rot_z_mat * point); midpoint + rot_2_mat * point }