Maximizing the Coverage of Roadmap Graph for Optimal Motion Planning

<div>Example of sampled sensing nodes and a node in 3D configuration space. (a) Sensing nodes sampled on <span class="nowrap"><svg height="14.694621pt" id="M110" style="vertical-align:-5.406286pt" version="1.1" viewbox="-0.049816 -9.288335 61.457234 14.694621" width="61.457234pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M471 379C471 433 467 511 427 578C379 658 305 712 208 712C154 712 98 699 70 684C70 668 95 634 111 634C141 651 180 665 234 665C306 665 350 627 372 575C391 530 393 480 393 442V415C371 436 344 448 313 448C280 448 227 437 176 411C100 372 23 279 23 148C23 67 64 -12 180 -12C293 -12 360 46 407 129C450 205 471 310 471 379ZM382 335C382 142 289 50 238 35C226 31 213 28 200 28C139 28 110 91 110 164C110 310 191 382 223 395C245 404 259 409 280 409C305 409 332 404 359 388C379 376 382 362 382 335Z"></path></g><g transform="matrix(.013,0,0,-0.013,6.446,0)"><path d="M401 353C473 367 557 406 557 502C557 551 535 592 498 616C460 640 410 650 333 650H41V615C112 608 121 602 121 516V134C121 49 112 42 35 35V0H289C372 0 449 14 500 43C556 74 593 126 593 193C593 288 517 335 401 349V353ZM253 363V553C253 574 255 589 262 596C268 602 284 609 307 609C361 609 415 575 415 484C415 401 372 363 276 363H253ZM253 323H273C386 323 445 276 445 182C445 84 382 43 326 42C273 41 253 62 253 136V323Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,14.758,3.132)"><path d="M397 380C406 395 404 411 396 425S369 451 350 451C302 451 239 372 192 294H189L199 338C214 407 207 451 180 451C152 451 83 405 30 345L48 318C87 354 117 372 125 372S135 362 127 324L55 -5L61 -12C87 -5 117 3 139 5C154 87 168 162 179 207C198 250 240 310 260 332C281 355 297 366 307 366C321 366 333 360 347 346C351 342 360 342 369 348C379 355 389 366 397 380Z"></path></g><g transform="matrix(.0065,0,0,-0.0065,18.247,5.233)"><path d="M468 631C455 633 437 638 419 647C391 661 351 667 319 667C183 667 100 591 100 483C100 398 175 333 225 302L265 277C326 239 362 203 362 151C362 67 303 27 241 27C114 27 78 136 63 213L25 211C29 123 31 67 29 49C56 23 130 -17 219 -17C348 -17 452 61 452 174C452 266 399 306 320 361L287 384C230 424 184 457 184 513C184 561 221 623 299 623C383 623 416 561 429 478L465 486C463 519 462 592 468 631Z"></path></g><g transform="matrix(.013,0,0,-0.013,26.758,0)"><path d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 610 70 450 70 271V270C70 89 136 -72 282 -170L300 -147Z"></path></g><g transform="matrix(.013,0,0,-0.013,31.273,0)"><path d="M393 379C402 394 400 411 393 422C384 437 365 448 348 448C301 448 237 372 186 285H182L193 335C210 408 205 448 178 448C150 448 80 402 29 344L45 321C80 355 114 373 122 373C128 373 130 365 124 330C106 228 76 98 50 -5L57 -12C82 -5 112 3 132 6L172 203C196 256 234 304 254 329C275 355 293 367 306 367C318 367 330 360 342 348C347 343 355 343 365 350S386 367 393 379Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,36.193,3.132)"><path d="M357 391C357 416 325 451 270 451C241 451 179 431 146 400C109 365 97 334 97 307C97 248 143 213 196 180C250 146 261 123 261 101C261 75 237 40 190 40C153 40 110 72 86 109C81 116 68 119 55 112C37 102 24 87 24 66C24 30 85 -12 137 -12C229 -12 331 62 331 140C331 189 304 218 236 260C197 284 164 309 164 346C164 381 194 400 220 400C259 400 282 380 304 350C310 342 321 339 330 344C347 353 357 372 357 391Z"></path></g><g transform="matrix(.013,0,0,-0.013,43.803,0)"><path d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z"></path></g><g transform="matrix(.013,0,0,-0.013,55.094,0)"><path d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z"></path></g></svg>).</span> (b) A node and its sensing nodes.</div>

Complexity

Maximizing the Coverage of Roadmap Graph for Optimal Motion Planning

Figure 4