Abstract
This chapter first provides a formulation of the geometric path planning problem in Sect. 7.2 and then introduces sampling-based planning in Sect. 7.3. Sampling-based planners are general techniques applicable to a wide set of problems and have been successful in dealing with hard planning instances. For specific, often simpler, planning instances, alternative approaches exist and are presented in Sect. 7.4. These approaches provide theoretical guarantees and for simple planning instances they outperform sampling-based planners. Section 7.5 considers problems that involve differential constraints, while Sect. 7.6 overviews several other extensions of the basic problem formulation and proposed solutions. Finally, Sect. 7.8 addresses some important and more advanced topics related to motion planning.
| Original language | English (US) |
|---|---|
| Title of host publication | Springer Handbook of Robotics |
| Publisher | Springer International Publishing |
| Pages | 139-161 |
| Number of pages | 23 |
| ISBN (Electronic) | 9783319325521 |
| ISBN (Print) | 9783319325507 |
| DOIs | |
| State | Published - Jan 1 2016 |
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Keywords
- Belief space
- Cell decomposition
- Differential constraint
- Motion planning
- Planning algorithm
ASJC Scopus subject areas
- Computer Science(all)
- Engineering(all)
Cite this
Motion planning. / Kavraki, Lydia E.; Lavalle, Steven M.
Springer Handbook of Robotics. Springer International Publishing, 2016. p. 139-161.Research output: Chapter in Book/Report/Conference proceeding › Chapter
}
TY - CHAP
T1 - Motion planning
AU - Kavraki, Lydia E.
AU - Lavalle, Steven M
PY - 2016/1/1
Y1 - 2016/1/1
N2 - This chapter first provides a formulation of the geometric path planning problem in Sect. 7.2 and then introduces sampling-based planning in Sect. 7.3. Sampling-based planners are general techniques applicable to a wide set of problems and have been successful in dealing with hard planning instances. For specific, often simpler, planning instances, alternative approaches exist and are presented in Sect. 7.4. These approaches provide theoretical guarantees and for simple planning instances they outperform sampling-based planners. Section 7.5 considers problems that involve differential constraints, while Sect. 7.6 overviews several other extensions of the basic problem formulation and proposed solutions. Finally, Sect. 7.8 addresses some important and more advanced topics related to motion planning.
AB - This chapter first provides a formulation of the geometric path planning problem in Sect. 7.2 and then introduces sampling-based planning in Sect. 7.3. Sampling-based planners are general techniques applicable to a wide set of problems and have been successful in dealing with hard planning instances. For specific, often simpler, planning instances, alternative approaches exist and are presented in Sect. 7.4. These approaches provide theoretical guarantees and for simple planning instances they outperform sampling-based planners. Section 7.5 considers problems that involve differential constraints, while Sect. 7.6 overviews several other extensions of the basic problem formulation and proposed solutions. Finally, Sect. 7.8 addresses some important and more advanced topics related to motion planning.
KW - Belief space
KW - Cell decomposition
KW - Differential constraint
KW - Motion planning
KW - Planning algorithm
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U2 - 10.1007/978-3-319-32552-1_7
DO - 10.1007/978-3-319-32552-1_7
M3 - Chapter
AN - SCOPUS:85069178010
SN - 9783319325507
SP - 139
EP - 161
BT - Springer Handbook of Robotics
PB - Springer International Publishing
ER -