RouthSearch: Inferring PID Parameter Specification for Flight Control Program by Coordinate Search Article Swipe
Siao Wang
,
Zhen Dong
,
Hui Li
,
Liwei Shen
,
Xin Peng
,
Dongdong She
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1145/3728904
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1145/3728904
Flight control programs are widely used in unmanned aerial vehicles (UAVs) to manage and maintain UAVs’ flying behaviors dynamically. These flight control programs include a PID control module that takes three user-configurable PID parameters: Proportional (P), Integral (I), and Derivative (D). Users can also adjust these PID parameters during flight to suit the needs of various flight tasks. However, flight control programs do not have sufficient safety checks on the user-provided PID parameters, leading to a severe vulnerability of UAV—input validation bug. It happens when the user misconfigures PID parameters and causes the UAV to enter a dangerous state, such as deviation from the expected path, loss of control, or even crash. Prior works use random testing approaches like fuzzing to identify invalid PID parameters from user input. However, they are not effective in the three-dimensional search space of PID parameters. Meanwhile, each dynamic execution of the UAV test is very expensive, further affecting the performance of random testing. In this work, we address the problem of PID parameter misconfiguration by combining the Routh-Hurwitz stability criterion with coordinate search, introducing a method called RouthSearch. Instead of identifying misconfigured PID parameters in an ad-hoc fashion, RouthSearch principledly determines valid ranges for three-dimensional PID parameters. We first leverage the Routh-Hurwitz Criterion to identify a theoretical PID parameter boundary. We then refine the boundary using an efficient coordinate search. The valid range of three-dimensional PID parameters determined by RouthSearch can filter out misconfigured PID parameters from users during flight and further help to discover logical bugs in popular flight control programs. We evaluated RouthSearch across eight flight modes in two popular flight control programs, PX4 and ArduPilot. The results show that RouthSearch can determine the valid ranges of the three-dimensional PID parameters with an accuracy of 92. 0% when compared to the ground truth. In terms of the total number of misconfigured PID parameters, RouthSearch discovers 3,853 sets of PID misconfigurations within 48 hours, while the STOA work PGFuzz only discovers 449 sets of PID misconfigurations, significantly outperforming prior works by 8.58 times. Additionally, our method helps to detect three bugs in ArduPilot and PX4.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1145/3728904
- OA Status
- hybrid
- References
- 36
- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4411522840Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1145/3728904Digital Object Identifier
- Title
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RouthSearch: Inferring PID Parameter Specification for Flight Control Program by Coordinate SearchWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-06-22Full publication date if available
- Authors
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Siao Wang, Zhen Dong, Hui Li, Liwei Shen, Xin Peng, Dongdong SheList of authors in order
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-
https://doi.org/10.1145/3728904Publisher landing page
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-
YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
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https://doi.org/10.1145/3728904Direct OA link when available
- Concepts
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PID controller, Computer science, Control theory (sociology), Leverage (statistics), Simulation, Control (management), Control engineering, Engineering, Artificial intelligence, Temperature controlTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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36Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| publication_date | 2025-06-22 |
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| referenced_works_count | 36 |
| abstract_inverted_index.a | 24, 75, 96, 180, 211 |
| abstract_inverted_index.0% | 294 |
| abstract_inverted_index.48 | 319 |
| abstract_inverted_index.In | 159, 301 |
| abstract_inverted_index.It | 82 |
| abstract_inverted_index.We | 203, 216, 258 |
| abstract_inverted_index.an | 191, 222, 290 |
| abstract_inverted_index.as | 100 |
| abstract_inverted_index.by | 170, 234, 337 |
| abstract_inverted_index.do | 62 |
| abstract_inverted_index.in | 6, 133, 190, 253, 265, 348 |
| abstract_inverted_index.is | 149 |
| abstract_inverted_index.of | 54, 78, 107, 138, 145, 156, 166, 185, 229, 284, 292, 303, 307, 315, 330 |
| abstract_inverted_index.on | 68 |
| abstract_inverted_index.or | 109 |
| abstract_inverted_index.to | 11, 50, 74, 94, 120, 209, 249, 297, 344 |
| abstract_inverted_index.we | 162 |
| abstract_inverted_index.449 | 328 |
| abstract_inverted_index.92. | 293 |
| abstract_inverted_index.PID | 25, 32, 46, 71, 88, 123, 139, 167, 188, 201, 213, 231, 240, 287, 309, 316, 331 |
| abstract_inverted_index.PX4 | 271 |
| abstract_inverted_index.The | 226, 274 |
| abstract_inverted_index.UAV | 93, 147 |
| abstract_inverted_index.and | 13, 38, 90, 246, 272, 350 |
| abstract_inverted_index.are | 3, 130 |
| abstract_inverted_index.can | 42, 236, 279 |
| abstract_inverted_index.for | 199 |
| abstract_inverted_index.not | 63, 131 |
| abstract_inverted_index.our | 341 |
| abstract_inverted_index.out | 238 |
| abstract_inverted_index.the | 52, 69, 85, 92, 103, 134, 146, 154, 164, 172, 206, 219, 281, 285, 298, 304, 322 |
| abstract_inverted_index.two | 266 |
| abstract_inverted_index.use | 114 |
| abstract_inverted_index.(D). | 40 |
| abstract_inverted_index.(I), | 37 |
| abstract_inverted_index.(P), | 35 |
| abstract_inverted_index.8.58 | 338 |
| abstract_inverted_index.PX4. | 351 |
| abstract_inverted_index.STOA | 323 |
| abstract_inverted_index.also | 43 |
| abstract_inverted_index.bug. | 81 |
| abstract_inverted_index.bugs | 252, 347 |
| abstract_inverted_index.each | 142 |
| abstract_inverted_index.even | 110 |
| abstract_inverted_index.from | 102, 125, 242 |
| abstract_inverted_index.have | 64 |
| abstract_inverted_index.help | 248 |
| abstract_inverted_index.like | 118 |
| abstract_inverted_index.loss | 106 |
| abstract_inverted_index.only | 326 |
| abstract_inverted_index.sets | 314, 329 |
| abstract_inverted_index.show | 276 |
| abstract_inverted_index.such | 99 |
| abstract_inverted_index.suit | 51 |
| abstract_inverted_index.test | 148 |
| abstract_inverted_index.that | 28, 277 |
| abstract_inverted_index.then | 217 |
| abstract_inverted_index.they | 129 |
| abstract_inverted_index.this | 160 |
| abstract_inverted_index.used | 5 |
| abstract_inverted_index.user | 86, 126 |
| abstract_inverted_index.very | 150 |
| abstract_inverted_index.when | 84, 295 |
| abstract_inverted_index.with | 176, 289 |
| abstract_inverted_index.work | 324 |
| abstract_inverted_index.3,853 | 313 |
| abstract_inverted_index.Prior | 112 |
| abstract_inverted_index.These | 19 |
| abstract_inverted_index.Users | 41 |
| abstract_inverted_index.eight | 262 |
| abstract_inverted_index.enter | 95 |
| abstract_inverted_index.first | 204 |
| abstract_inverted_index.helps | 343 |
| abstract_inverted_index.modes | 264 |
| abstract_inverted_index.needs | 53 |
| abstract_inverted_index.path, | 105 |
| abstract_inverted_index.prior | 335 |
| abstract_inverted_index.range | 228 |
| abstract_inverted_index.space | 137 |
| abstract_inverted_index.takes | 29 |
| abstract_inverted_index.terms | 302 |
| abstract_inverted_index.these | 45 |
| abstract_inverted_index.three | 30, 346 |
| abstract_inverted_index.total | 305 |
| abstract_inverted_index.users | 243 |
| abstract_inverted_index.using | 221 |
| abstract_inverted_index.valid | 197, 227, 282 |
| abstract_inverted_index.while | 321 |
| abstract_inverted_index.work, | 161 |
| abstract_inverted_index.works | 113, 336 |
| abstract_inverted_index.(UAVs) | 10 |
| abstract_inverted_index.Flight | 0 |
| abstract_inverted_index.PGFuzz | 325 |
| abstract_inverted_index.across | 261 |
| abstract_inverted_index.ad-hoc | 192 |
| abstract_inverted_index.adjust | 44 |
| abstract_inverted_index.aerial | 8 |
| abstract_inverted_index.called | 182 |
| abstract_inverted_index.causes | 91 |
| abstract_inverted_index.checks | 67 |
| abstract_inverted_index.crash. | 111 |
| abstract_inverted_index.detect | 345 |
| abstract_inverted_index.during | 48, 244 |
| abstract_inverted_index.filter | 237 |
| abstract_inverted_index.flight | 20, 49, 56, 59, 245, 255, 263, 268 |
| abstract_inverted_index.flying | 16 |
| abstract_inverted_index.ground | 299 |
| abstract_inverted_index.hours, | 320 |
| abstract_inverted_index.input. | 127 |
| abstract_inverted_index.manage | 12 |
| abstract_inverted_index.method | 181, 342 |
| abstract_inverted_index.module | 27 |
| abstract_inverted_index.number | 306 |
| abstract_inverted_index.random | 115, 157 |
| abstract_inverted_index.ranges | 198, 283 |
| abstract_inverted_index.refine | 218 |
| abstract_inverted_index.safety | 66 |
| abstract_inverted_index.search | 136 |
| abstract_inverted_index.severe | 76 |
| abstract_inverted_index.state, | 98 |
| abstract_inverted_index.tasks. | 57 |
| abstract_inverted_index.times. | 339 |
| abstract_inverted_index.truth. | 300 |
| abstract_inverted_index.widely | 4 |
| abstract_inverted_index.within | 318 |
| abstract_inverted_index.Instead | 184 |
| abstract_inverted_index.UAVs’ | 15 |
| abstract_inverted_index.address | 163 |
| abstract_inverted_index.control | 1, 21, 26, 60, 256, 269 |
| abstract_inverted_index.dynamic | 143 |
| abstract_inverted_index.further | 152, 247 |
| abstract_inverted_index.fuzzing | 119 |
| abstract_inverted_index.happens | 83 |
| abstract_inverted_index.include | 23 |
| abstract_inverted_index.invalid | 122 |
| abstract_inverted_index.leading | 73 |
| abstract_inverted_index.logical | 251 |
| abstract_inverted_index.popular | 254, 267 |
| abstract_inverted_index.problem | 165 |
| abstract_inverted_index.results | 275 |
| abstract_inverted_index.search, | 178 |
| abstract_inverted_index.search. | 225 |
| abstract_inverted_index.testing | 116 |
| abstract_inverted_index.various | 55 |
| abstract_inverted_index.However, | 58, 128 |
| abstract_inverted_index.Integral | 36 |
| abstract_inverted_index.accuracy | 291 |
| abstract_inverted_index.boundary | 220 |
| abstract_inverted_index.compared | 296 |
| abstract_inverted_index.control, | 108 |
| abstract_inverted_index.discover | 250 |
| abstract_inverted_index.expected | 104 |
| abstract_inverted_index.fashion, | 193 |
| abstract_inverted_index.identify | 121, 210 |
| abstract_inverted_index.leverage | 205 |
| abstract_inverted_index.maintain | 14 |
| abstract_inverted_index.programs | 2, 22, 61 |
| abstract_inverted_index.testing. | 158 |
| abstract_inverted_index.unmanned | 7 |
| abstract_inverted_index.vehicles | 9 |
| abstract_inverted_index.ArduPilot | 349 |
| abstract_inverted_index.Criterion | 208 |
| abstract_inverted_index.affecting | 153 |
| abstract_inverted_index.behaviors | 17 |
| abstract_inverted_index.boundary. | 215 |
| abstract_inverted_index.combining | 171 |
| abstract_inverted_index.criterion | 175 |
| abstract_inverted_index.dangerous | 97 |
| abstract_inverted_index.determine | 280 |
| abstract_inverted_index.deviation | 101 |
| abstract_inverted_index.discovers | 312, 327 |
| abstract_inverted_index.effective | 132 |
| abstract_inverted_index.efficient | 223 |
| abstract_inverted_index.evaluated | 259 |
| abstract_inverted_index.execution | 144 |
| abstract_inverted_index.parameter | 168, 214 |
| abstract_inverted_index.programs, | 270 |
| abstract_inverted_index.programs. | 257 |
| abstract_inverted_index.stability | 174 |
| abstract_inverted_index.ArduPilot. | 273 |
| abstract_inverted_index.Derivative | 39 |
| abstract_inverted_index.Meanwhile, | 141 |
| abstract_inverted_index.approaches | 117 |
| abstract_inverted_index.coordinate | 177, 224 |
| abstract_inverted_index.determined | 233 |
| abstract_inverted_index.determines | 196 |
| abstract_inverted_index.expensive, | 151 |
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| abstract_inverted_index.sufficient | 65 |
| abstract_inverted_index.validation | 80 |
| abstract_inverted_index.RouthSearch | 194, 235, 260, 278, 311 |
| abstract_inverted_index.UAV—input | 79 |
| abstract_inverted_index.identifying | 186 |
| abstract_inverted_index.introducing | 179 |
| abstract_inverted_index.parameters, | 72, 310 |
| abstract_inverted_index.parameters. | 140, 202 |
| abstract_inverted_index.parameters: | 33 |
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| abstract_inverted_index.theoretical | 212 |
| abstract_inverted_index.Proportional | 34 |
| abstract_inverted_index.RouthSearch. | 183 |
| abstract_inverted_index.dynamically. | 18 |
| abstract_inverted_index.principledly | 195 |
| abstract_inverted_index.Additionally, | 340 |
| abstract_inverted_index.Routh-Hurwitz | 173, 207 |
| abstract_inverted_index.misconfigured | 187, 239, 308 |
| abstract_inverted_index.misconfigures | 87 |
| abstract_inverted_index.outperforming | 334 |
| abstract_inverted_index.significantly | 333 |
| abstract_inverted_index.user-provided | 70 |
| abstract_inverted_index.vulnerability | 77 |
| abstract_inverted_index.misconfiguration | 169 |
| abstract_inverted_index.misconfigurations | 317 |
| abstract_inverted_index.three-dimensional | 135, 200, 230, 286 |
| abstract_inverted_index.user-configurable | 31 |
| abstract_inverted_index.misconfigurations, | 332 |
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| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.24994552 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |