A Performance Review of Collision-Free Path Planning Algorithms
Abstract
:1. Introduction
2. CFPP
2.1. Environment Type
2.2. Environmental Representation
2.3. Searching Algorithms
2.3.1. Classical Algorithm
2.3.2. Heuristic Based Algorithm
2.4. Experimental Type
3. Experiments Plan
3.1. Algorithms
3.2. Envionments
3.3. Metaheuristic Parameter
4. Computational Results
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Word | Notation | Word | Notation |
---|---|---|---|
Environment type | Env.T. | Network | N. |
Environment representation | Env.R. | Coordinate system | Co.S. |
Searching algorithm | S.Alg. | Boundary representation | B.R. |
Experimental Type | Exp.T. | Cell tree | C.T. |
Obstacle type | O.T. | Polygonal approximation | Po.A. |
Point type | P.T. | Evolutionary programming | E.P. |
Workspace representation | W.R. | K nearest neighbor | K near. |
Obstacle representation | Ob.R. | Simulation | S. |
Experiment | Exp. | Probabilistic roadmap | PRM |
Workspace representation algorithm | W.R.Alg. | Rapidly-exploring Random Tree | RRT |
Certain | C. | Voronoi Diagram | V.D. |
Uncertain | Uc. | Visibility Graph | Vgraph |
Static | S. | Normal distribution transform | NDT |
Dynamic | D. | Circle approximation | Ci.A |
Ref. | Author & Year | Env.T. | Env.R | S.Alg. | Exp.T. | W.R.Alg. | |||
---|---|---|---|---|---|---|---|---|---|
P.T. | O.T | W.R. | Ob.R | Exp. | Robot | ||||
[29] | Kavraki et al., 1996 | C. | S. | N. | Grid | Heuristic | S. | Articulated robots | PRM |
[19] | Kavraki et al., 1998 | C. | - | - | B.R. | - | S. | 6 DOF | PRM |
[49] | Hsu et al., 1997 | C. | S. | N. | - | Heuristic | S. | 6 DOF | PRM |
[39] | Wilmarth et al., 1999 | C. | S. | N. | B.R. | - | S. | - | MAPRM |
[31] | Kuffner & LaValle, 2000 | C. | S. | N. | - | Heuristic | S. | 7 DOF | RRT |
[23] | Thrun et al., 2001 | Uc. | S. | N. | B.R., C.T. | MCL algorithm | S. | RWI B18 robot | Sampling based |
[35] | Sánchez & Latombe, 2002 | C. | D. | N. | Po.A. | Heuristic | S. | Multi robot | PRM |
[36] | Sanchez & Latombe, 2002 | Uc. | D. | N. | Po.A. | Heuristic | S. | - | PRM |
[37] | Sánchez & Latombe, 2003 | C. | D. | N. | - | Heuristic | S. | 6 robots | PRM |
[26] | LaValle et al., 2004 | - | - | N. | - | - | S. | - | Sampling based review |
[40] | Saha et al., 2005 | C. | S. | N. | - | F* | S. | - | PRM |
[43] | Hsu et al., 2006 | Uc. | S. | N. | - | Heuristic | S. | - | PRM |
[41] | Saha et al., 2006 | - | S. | N. | - | Heuristic | S. | - | PRM |
[50] | Alterovitz et al., 2007 | Uc. | S. | N. | B.R. | Heuristic | S. | - | Sampling based |
[30] | Hsu et al., 2002 | Uc. | D. | N. | B.R. | Heuristic | Real | - | PRM |
[34] | Kuwata et al., 2009 | Uc. | D. | N., Co.S. | Grid | Heuristic | S. | Vehicle | RRT |
[27] | Englot & Hover, 2011 | C. | S. | N. | - | ACO | S. | - | Sampling based |
[44] | Karaman & Frazzoli, 2011 | C. | S. | N. | B.R. | Heuristic | S. | - | Sampling based |
[33] | Malone et al., 2014 | - | D. | N. | Grid | Dijkstra | S. | - | PRM |
[24] | Janson et al., 2018 | Uc. | S. | N. | B.R. | MCMP | S. | - | Sampling based |
[51] | Contreras-Cruz et al., 2015 | Uc. | S. | N. | - | EP, Dijkstra | Real | Xidoo-Bot | PRM |
[42] | Dantam et al., 2016 | - | S. | N. | - | Heuristic | Real | - | RRT |
[38] | Solovey et al., 2016 | - | S. | N. | - | K Near., M* | S. | High DOF Multi robot | RRT |
[32] | Kim et al., 2016 | - | S. | N. | - | K Near. | S. | - | RRT |
[45] | Marble & Bekris, 2017 | C. | S. | N. | - | K Near. | S. | - | PRM |
[28] | Ichter et al., 2018 | - | D. | N. | - | Heuristic | S. | Multi robots | Sampling based |
Ref. | Author & Year | Env.T. | Env.R | S.Alg. | Exp.T. | W.R.Alg. | |||
---|---|---|---|---|---|---|---|---|---|
P.T. | O.T. | W.R. | Ob.R | Exp | Robot | ||||
[54] | Bhattacharya & Gavrilova, 2007 | - | D. | N. | B.R. | Dijkstra | S. | - | V.D. |
[55] | Ho & Liu, 2009 | - | S. | N. | B.R. | Dijkstra | S. | Car-like robot | V.D. |
[56] | Janson et al., 2018 | - | - | N. | B.R. | Dijkstra | S. | - | PRM |
[57] | Wang et al., 2011 | C. | S. | N. | B.R. | Dijkstra | S. | - | Grid |
[20] | Alexopoulos & Griffin, 1992 | C. | S. | N. | B.R. | A* | S. | A mobile robot | Vgraph |
[64] | Fu & Liu, 1990 | C. | S. | N. | Po.A. | A* | S. | - | Vgraph |
[58] | Herman, 1986 | C. | S. | N. | C.T. | A* | S. | - | C.T. |
[2] | Lozano-Pérez & Wesley, 1979 | C. | S. | N. | B.R. | A* | S. | - | Vgraph |
[60] | Berg et al., 2006 | Uc. | D. | N. | B.R. | D* | S. | - | Roadmap |
[59] | Bohlin & Kavraki, 2000 | C. | S. | N. | B.R. | A* | S. | 6 DOF robot | PRM |
[62] | Deng et al., 2012 | Uc. | D. | N. | - | Dijkstra | S. | - | - |
[63] | Duchoň et al., 2014 | - | - | N. | Grid | A* | S. | - | SLAM based grid |
[61] | Noto & Sato, 2002 | - | - | N. | - | Dijkstra | S. | - | Grid |
Ref. | Author & Year | Env.T. | Env.R | S.Alg. | Exp.T. | W.R.Alg. | |||
---|---|---|---|---|---|---|---|---|---|
P.T. | O.T. | W.R. | Ob.R. | Exp. | Robot | ||||
[65] | Stoyanov et al., 2010 | C. | - | N. | - | Wavefront | S. | - | NDT |
[66] | AL-Taharwa et al., 2008 | C. | S. | N. | Grid | GA | S. | - | Grid |
[67] | Cai & Peng, 2002 | C. | S. | N. | B.R. | GA | S. | Two robots | Obstacle edge |
[68] | Yang & Yoo, 2018 | - | D. | N. | Grid | GA, ACO | S. | UAV | Grid Layer |
[69] | Hu & Yang, 2004 | C. | D. | N. | Grid | GA | S. | - | Grid |
[73] | MahmoudZadeh et al., 2018 | Uc. | D. | Co.S. | B.R. | EA | S. | AUV | - |
[71] | Elshamli et al., 2004 | - | D. | N. | B.R. | GA | S. | - | - |
[70] | Jiang et al., 2018 | C. | S. | Co.S. | B.R. | GA | S. | - | Mechanical arm |
[72] | Zhao et al., 1994 | C. | S. | Co.S. | B.R. | GA | S. | Mobile Manipulator | - |
[78] | Tu & Yang, 2004 | C. | D. | N. | Grid | GA | S. | - | Grid |
[75] | Lamini et al., 2018 | C. | S. | N. | Grid | GA | S. | - | Grid |
[74] | Lee et al., 2018 | C. | S. | N. | Grid | GA | S. | - | Grid |
[77] | Sedighi et al., 2004 | C. | S. | N. | Grid | GA | S. | - | Grid |
[76] | Tuncer & Yildirim, 2012 | C. | D. | N. | Grid | GA | S. | - | Grid |
[79] | Nazarahari et al., 2019 | C. | S. | Co.S. | B.R. | GA, Wavefront | S. | Multi-robot | Potential field |
Ref. | Author & Year | Env.T. | Env.R | S.Alg. | Exp.T. | W.R.Alg. | |||
---|---|---|---|---|---|---|---|---|---|
P.T. | O.T. | W.R. | Ob.R. | Exp. | Robot | ||||
[80] | Janabi-Sharifi & Vinke, 1993 | C. | S. | Co.S. | B.R. | SA | S. | Disk robot | Potential field |
[82] | Park et al., 2001 | - | S. | Co.S. | B.R. | SA | Both | Mobile robot | Potential field |
[84] | Park & Lee, 2002 | - | S. | Co.S. | B.R. | SA | Both | Mobile robot | Potential field |
[81] | Zhu et al., 2006 | C. | S. | Co.S. | B.R. | SA | S. | - | Potential field |
[90] | Carriker et al., 1990 | C. | S. | Co.S. | B.R. | SA | S. | Mobile Manipulator | - |
[89] | Kroumov & Yu, 2009 | C. | S. | Co.S. | B.R. | SA, NN | S. | - | Potential field |
[86] | Martínez-Alfaro & Gómez-García, 1998 | C. | S. | Co.S. | B.R. | SA, Fuzzy | S. | - | - |
[85] | Miao & Tian, 2008 | C. | D. | N. | B.R. | SA | S. | - | Obstacle edge |
[88] | Miao & Tian, 2013 | C. | D. | N. | B.R. | SA | S. | - | Obstacle edge |
[87] | Tavares et al., 2011 | C. | S. | Co.S. | B.R. | SA | S. | - | - |
[91] | Amer et al., 2019 | C. | D. | N. | - | SA | S. | Vehicles | Road |
Ref. | Author & Year | Env.T. | Env.R | Exp.T. | W.R.Alg. | |||
---|---|---|---|---|---|---|---|---|
P.T. | O.T. | W.R. | Ob.R. | Exp. | Robot | |||
[99] | Chen & Li, 2006 | C. | S. | Co.S. | Ci.A. | S. | Car-like robot | - |
[93] | Foo et al., 2007 | - | S. | Co.S. | B.R. | S. | UAV | - |
[95] | Fu et al., 2011 | - | S. | Co.S. | B.R. | S. | UAV | - |
[96] | Gong et al., 2011 | C. | S. | Co.S. | B.R. | S. | - | - |
[97] | Saska et al., 2006 | C. | S. | Co.S. | B.R. | S. | Robotic soccer | - |
[92] | Song et al., 2019 | C. | S. | Co.S. | Grid | S. | - | Grid |
[46] | Tharwat et al., 2019 | C. | S. | Co.S. | B.R. | S. | - | - |
[94] | Zhang et al., 2013 | Uc. | S. | Co.S. | B.R. | S. | - | - |
[98] | Zhang et al., 2013 | C. | S. | Co.S. | B.R. | S. | UAV | - |
[104] | Kang et al., 2008 | C. | S. | N. | B.R. | S. | - | Obstacle edge |
[100] | Masehian & Sedighizadeh, 2010 | C. | S. | Co.S. | B.R. | S. | - | - |
[102] | Phung et al., 2017 | C. | S. | N. | - | S. | UAV | Vision-based inspection |
[103] | Shiltagh & Jalal, 2013 | C. | S. | N. | Grid | S. | - | Grid |
[101] | Wang et al., 2015 | C. | D. | N. | Grid | S. | - | Grid |
[105] | Alejo et al., 2013 | - | - | Co.S. | - | S. | Multi-UAV | - |
[106] | Thabit & Mohades, 2019 | C. | S. | N. | Grid | S. | Multi-UAV | Grid |
Ref. | Author & Year | Env.T. | Env.R | Exp.T. | W.R.Alg. | |||
---|---|---|---|---|---|---|---|---|
P.T. | O.T. | W.R. | Ob.R. | Exp. | Robot | |||
[112] | Akka & Khaber, 2018 | C. | S. | N. | Gird | S. | - | Grid |
[115] | Brand et al., 2010 | C. | S. | N. | Grid | S. | - | Grid |
[114] | Chia et al., 2010 | C. | S. | N. | Grid | S. | - | Grid |
[109] | Garcia et al., 2009 | C. | D. | N. | Grid | S. | - | Grid |
[108] | Jiao et al., 2018 | C. | S. | N. | Grid | S. | Wheelchairs | Grid |
[107] | Xing et al., 2011 | C. | D. | N. | Grid | S. | - | Grid |
[118] | Xiong et al., 2019 | C. | S. | N. | Grid | Both | AMV | V.D. |
[117] | Cong & Ponnambalam, 2009 | C. | S. | N. | Grid | S. | - | Grid |
[110] | Yen & Cheng, 2018 | C. | S. | N. | Grid | S. | (Multi-task) | Grid |
[111] | Hsiao et al., 2004 | - | - | N. | - | S. | - | Random Generated |
[113] | Yu et al., 2019 | C. | S. | N. | B.R. | S. | AUV (Multi-task) | Cube, Dense |
[116] | Zhang et al., 2010 | C. | S. | N. | Grid | S. | UAV | Point |
[120] | Fan et al., 2003 | C. | S. | Co.S. | B.R. | S. | - | - |
[119] | Wang et al., 2019 | C. | S. | N. | Grid | S. | Ground robot | Cube |
[121] | Ma et al., 2019 | C. | S. | N. | Grid | S. | AUV | Cube |
Searching Algorithm | Parameter | Characteristic |
---|---|---|
GA | Population Number | Integer |
Stop Criteria | Integer | |
Mutate Rate | Double (0~1) | |
Crossover Rate | Double (0~1) | |
Random Rate | Double (0~1) | |
SA | Stop Criteria | Integer |
Temperature | Double | |
Reduce Rate | Double (0~1) | |
Stop Temperature | Double | |
ACO | Ant Number | Integer |
Stop Criteria | Integer | |
Pheromone Rate | Double (0~1) | |
Evaporate Rate | Double (0~1) | |
PSO | Particle Number | Integer |
Stop Criteria | Integer | |
Inertia Max Rate | Double (0~1) | |
Inertia Min Rate | Double (0~1) |
Searching Algorithm | Parameter | Value |
---|---|---|
GA | Mutate Rate | 0.97 |
Crossover Rate | 0.59 | |
Random Rate | 0.15 | |
SA | Temperature | 2625.31 |
Reduction Rate | 0.61 | |
Stopping Temperature | 0.52 | |
ACO | Pheromone Rate | 0.44 |
Evaporate Rate | 0.96 | |
PSO | Inertia Max Rate | 0.94 |
Inertia Min Rate | 0.36 |
Problem Name | Searching Algorithm | Best OFV | Mean OFV | Processing Time (ms) | Average Processing Time (ms) | OFV Variance | Time Variance |
---|---|---|---|---|---|---|---|
10_1o | GA | 14.817 | 14.820 | 0.0 | 14.661 | 0.001 | 28.056 |
SA | 14.817 | 15.745 | 0.0 | 0.420 | 1.726 | 6.370 | |
ACO | 14.817 | 14.817 | 0.0 | 7.567 | 0 | 61.731 | |
PSO | 14.817 | 14.817 | 0.0 | 10.043 | 0 | 60.053 | |
10_4ch | GA | 27.136 | 29.893 | 281 | 355.175 | 1.807 | 14129.98 |
SA | 27.648 | 29.889 | 0.0 | 8.135 | 1.819 | 62.096 | |
ACO | 28.307 | 31.933 | 328 | 315.228 | 1.752 | 4752.647 | |
PSO | 27.648 | 29.889 | 47 | 45.607 | 0.566 | 37.096 | |
10_4n | GA | 16.243 | 17.337 | 47 | 53.248 | 0.048 | 139.240 |
SA | 16.243 | 17.663 | 0.0 | 0.860 | 0.103 | 12.733 | |
ACO | 16.243 | 17.355 | 31 | 17.06 | 0.034 | 25.762 | |
PSO | 16.243 | 17.169 | 15 | 15.726 | 0.095 | 18.089 | |
10_7n | GA | 14.065 | 14.305 | 62 | 90.302 | 0.025 | 833.630 |
SA | 14.065 | 14.566 | 0.0 | 2.990 | 0.100 | 38.428 | |
ACO | 14.055 | 14.351 | 47 | 41.365 | 0.040 | 202.931 | |
PSO | 14.065 | 14.278 | 15 | 21.607 | 0.015 | 61.548 | |
10_11s | GA | 14.485 | 16.810 | 125 | 180.398 | 0.426 | 3084.414 |
SA | 14.485 | 17.652 | 15 | 7.544 | 0.871 | 62.567 | |
ACO | 14.485 | 17.044 | 93 | 78.178 | 0.298 | 650.778 | |
PSO | 14.485 | 17.119 | 47 | 52.074 | 0.296 | 63.746 | |
10_1n | GA | 14.777 | 14.844 | 0.0 | 17.058 | 0.020 | 79.302 |
SA | 14.777 | 15.505 | 0.0 | 0.265 | 0.176 | 4.069 | |
ACO | 14.777 | 14.777 | 0.0 | 14.406 | 0.000 | 31.709 | |
PSO | 14.777 | 14.777 | 0.0 | 7.556 | 0 | 62.998 |
Problem Name | Searching Algorithm | Best OFV | Mean OFV | Processing Time (ms) | Average Processing Time (ms) | OFV Variance | Time Variance |
---|---|---|---|---|---|---|---|
10_1o | Dijkstra | 14.817 | 14.817 | 0.0 | 1.038 | 0 | 15.036 |
A* | 14.817 | 14.817 | 0.0 | 0.831 | 0 | 12.363 | |
Wavefront | 17.414 | 17.414 | 0.0 | 0.189 | 0 | 2.946 | |
10_4ch | Dijkstra | 27.136 | 27.136 | 0.0 | 0.779 | 0 | 11.554 |
A* | 27.136 | 27.136 | 0.0 | 0.771 | 0 | 12.039 | |
Wavefront | 219.782 | 219.782 | 15 | 15.932 | 0 | 4.964 | |
10_4n | Dijkstra | 16.243 | 16.243 | 0.0 | 0.815 | 0 | 12.133 |
A* | 16.243 | 16.243 | 0.0 | 0.621 | 0 | 9.275 | |
Wavefront | 20.485 | 20.485 | 0.0 | 1.883 | 0 | 26.053 | |
10_7n | Dijkstra | 14.055 | 14.055 | 0.0 | 0.744 | 0 | 11.001 |
A* | 14.055 | 14.055 | 0.0 | 0.625 | 0 | 9.394 | |
Wavefront | 17.314 | 17.314 | 0.0 | 0.031 | 0 | 0.481 | |
10_11s | Dijkstra | 14.485 | 14.485 | 0.0 | 1.123 | 0 | 16.288 |
A* | 14.485 | 14.485 | 0.0 | 0.763 | 0 | 11.322 | |
Wavefront | 14.485 | 14.485 | 0.0 | 0.015 | 0 | 0.225 | |
10_1n | Dijkstra | 14.777 | 14.777 | 0.0 | 1.448 | 0 | 20.492 |
A* | 14.777 | 14.777 | 0.0 | 1.198 | 0 | 17.296 | |
Wavefront | 72.083 | 72.083 | 0.0 | 0.300 | 0 | 4.655 |
Problem Name | Searching Algorithm | Best OFV | Mean OFV | Processing Time (ms) | Average Processing Time (ms) | OFV Variance | Time Variance |
---|---|---|---|---|---|---|---|
20_1o | GA | 29.509 | 29.642 | 31 | 69.416 | 0.039 | 958.536 |
SA | 29.509 | 29.867 | 0.0 | 0.464 | 0.040 | 6.976 | |
ACO | 29.509 | 29.509 | 140 | 186.123 | 0 | 238.633 | |
PSO | 29.509 | 29.509 | 0.0 | 8.251 | 0 | 65.400 | |
20_4o | GA | 17.470 | 17.749 | 94 | 190.572 | 0.087 | 6469.725 |
SA | 17.470 | 18.497 | 0.0 | 2.137 | 3.040 | 28.829 | |
ACO | 17.470 | 17.557 | 156 | 234.829 | 0.041 | 3034.65 | |
PSO | 17.470 | 17.495 | 15 | 36.399 | 0.013 | 62.066 |
Problem Name | Searching Algorithm | Best OFV | Mean OFV | Processing Time (ms) | Average Processing Time (ms) | OFV Variance | Time Variance |
---|---|---|---|---|---|---|---|
20_1o | Dijkstra | 29.509 | 29.509 | 31 | 45.066 | 0 | 43.279 |
A* | 29.509 | 29.509 | 15 | 33.730 | 0 | 38.918 | |
Wavefront | 30.971 | 30.971 | 0.0 | 0.328 | 0 | 5.025 | |
20_4o | Dijkstra | 17.470 | 17.470 | 15 | 23.931 | 0 | 61.980 |
A* | 17.470 | 17.470 | 0.0 | 8.360 | 0 | 62.405 | |
Wavefront | 17.828 | 17.828 | 0.0 | 0.315 | 0 | 4.871 |
Problem Name | Searching Algorithm | Best OFV | Mean OFV | Processing Time (ms) | Average Processing Time (ms) | OFV Variance | Time Variance |
---|---|---|---|---|---|---|---|
40_1o | GA | 62.512 | 62.622 | 125 | 156.54 | 0.037 | 2315.346 |
SA | 62.512 | 66.927 | 0.0 | 0.374 | 21.240 | 5.700 | |
ACO | 62.512 | 62.512 | 515 | 546.614 | 0 | 108.868 | |
PSO | 62.512 | 62.512 | 0.0 | 9.711 | 0 | 57.515 | |
40_1n | GA | 62.201 | 62.420 | 93 | 188.511 | 0.067 | 5195.051 |
SA | 62.201 | 63.481 | 0.0 | 0.327 | 1.619 | 4.995 | |
ACO | 62.201 | 62.208 | 750 | 864.01 | 0.003 | 5275.087 | |
PSO | 62.201 | 62.201 | 0.0 | 13.239 | 0.000 | 34.564 | |
40_11s | GA | 61.160 | 65.949 | 3359 | 2819.886 | 7.753 | 966961.7 |
SA | 60.677 | 68.213 | 63 | 23.476 | 15.223 | 116.924 | |
ACO | 61.172 | 67.476 | 1250 | 1562.399 | 6.878 | 251384.9 | |
PSO | 61.159 | 65.818 | 94 | 114.755 | 5.893 | 193.761 |
Problem Name | Searching Algorithm | Best OFV | Mean OFV | Processing Time (ms) | Average Processing Time (ms) | OFV Variance | Time Variance |
---|---|---|---|---|---|---|---|
40_1o | Dijkstra | 62.512 | 62.512 | 328 | 352.055 | 0 | 68.236 |
A* | 62.512 | 62.512 | 124 | 133.200 | 0 | 62.801 | |
Wavefront | 73.899 | 73.899 | 0.0 | 1.486 | 0 | 21.079 | |
40_1n | Dijkstra | 62.201 | 62.201 | 609 | 625.265 | 0 | 47.522 |
A* | 62.201 | 62.201 | 390 | 407.943 | 0 | 39.447 | |
Wavefront | 2727.895 | 2727.895 | 15 | 23.186 | 0 | 91.761 | |
40_11s | Dijkstra | 58.835 | 58.835 | 234 | 247.047 | 0 | 181.048 |
A* | 58.835 | 58.835 | 78 | 89.608 | 0 | 80.601 | |
Wavefront | 64.527 | 64.527 | 0.0 | 1.276 | 0 | 18.266 |
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Shin, H.; Chae, J. A Performance Review of Collision-Free Path Planning Algorithms. Electronics 2020, 9, 316. https://doi.org/10.3390/electronics9020316
Shin H, Chae J. A Performance Review of Collision-Free Path Planning Algorithms. Electronics. 2020; 9(2):316. https://doi.org/10.3390/electronics9020316
Chicago/Turabian StyleShin, Hyunwoo, and Junjae Chae. 2020. "A Performance Review of Collision-Free Path Planning Algorithms" Electronics 9, no. 2: 316. https://doi.org/10.3390/electronics9020316
APA StyleShin, H., & Chae, J. (2020). A Performance Review of Collision-Free Path Planning Algorithms. Electronics, 9(2), 316. https://doi.org/10.3390/electronics9020316