Poisson-Disc

Based on Jason Davies’ implementation of Bridson’s algorithm. See the related explanation and Mike Bostock's block. Icon comes from here.

<!DOCTYPE html>
<meta charset="utf-8">

<body>
<script src="//d3js.org/d3.v4.min.js"></script>
<script>
// based on https://bl.ocks.org/mbostock/19168c663618b7f07158
var margin = {top: 20, right: 10, bottom: 20, left: 10},
    width = 900 - margin.left - margin.right,
    height = 600 - margin.top - margin.bottom,
    r = 13,
    radious = 14;

var sample = poissonDiscSampler(width, height, radious);

var svg = d3.select("body").append("svg")
    .attr("width", width + margin.left + margin.right)
    .attr("height", height + margin.top + margin.bottom);

d3.timer(function() {
  for (var i = 0; i < 100; ++i) {
    var s = sample();
    if (!s) return true;
    svg.append("image")
    .attr('xlink:href', 'icon.png')
      .attr("x", s[0])
      .attr("y", s[1])
      .attr('height', '0')
      .attr('width', '0')
      .transition()
      .attr('height', r)
      .attr('width', r)

}
});

// Based on https://www.jasondavies.com/poisson-disc/
function poissonDiscSampler(width, height, radius) {
  var k = 30, // maximum number of samples before rejection
      radius2 = radius * radius,
      R = 3 * radius2,
      cellSize = radius * Math.SQRT1_2,
      gridWidth = Math.ceil(width / cellSize),
      gridHeight = Math.ceil(height / cellSize),
      grid = new Array(gridWidth * gridHeight),
      queue = [],
      queueSize = 0,
      sampleSize = 0;

return function() {
    if (!sampleSize) return sample(Math.random() * width, Math.random() * height);

// Pick a random existing sample and remove it from the queue.
    while (queueSize) {
      var i = Math.random() * queueSize | 0,
          s = queue[i];

// Make a new candidate between [radius, 2 * radius] from the existing sample.
      for (var j = 0; j < k; ++j) {
        var a = 2 * Math.PI * Math.random(),
            r = Math.sqrt(Math.random() * R + radius2),
            x = s[0] + r * Math.cos(a),
            y = s[1] + r * Math.sin(a);

// Reject candidates that are outside the allowed extent,
        // or closer than 2 * radius to any existing sample.
        if (0 <= x && x < width && 0 <= y && y < height && far(x, y)) return sample(x, y);
      }

queue[i] = queue[--queueSize];
      queue.length = queueSize;
    }
  };

function far(x, y) {
    var i = x / cellSize | 0,
        j = y / cellSize | 0,
        i0 = Math.max(i - 2, 0),
        j0 = Math.max(j - 2, 0),
        i1 = Math.min(i + 3, gridWidth),
        j1 = Math.min(j + 3, gridHeight);

for (j = j0; j < j1; ++j) {
      var o = j * gridWidth;
      for (i = i0; i < i1; ++i) {
        if (s = grid[o + i]) {
          var s,
              dx = s[0] - x,
              dy = s[1] - y;
          if (dx * dx + dy * dy < radius2) return false;
        }
      }
    }

return true;
  }

function sample(x, y) {
    var s = [x, y];
    queue.push(s);
    grid[gridWidth * (y / cellSize | 0) + (x / cellSize | 0)] = s;
    ++sampleSize;
    ++queueSize;
    return s;
  }
}

</script>

https://d3js.org/d3.v4.min.js