The DOI matches its Crossref record.
Mixed integer programming for multi-vehicle path planning
Abstract
This paper presents a new approach to fuel-optimal path planning of multiple vehicles using a combination of linear and integer programming. The basic problem formulation is to have the vehicles move from an initial dynamic state to a final state without colliding with each other, while at the same time avoiding other stationary and moving obstacles. It is shown that this problem can be rewritten as a linear program with mixed integer/linear constraints that account for the collision avoidance. A key benefit of this approach is that the path optimization can be readily solved using the CPLEX optimization software with an AMPL/Matlab interface. An example is worked out to show that the framework of mixed integer/linear programming is well suited for path planning and collision avoidance problems. Implementation issues are also considered. In particular, we compare receding horizon strategies with fixed arrival time approaches.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Wireless communications with unmanned aerial vehicles: opportunities and challenges
Zeng, Y., Zhang, R., & Lim, T. J. (2016) · IEEE Communications Magazine · doi:10.1109/mcom.2016.7470933 · Cited by 4,048
CHOMP: Gradient optimization techniques for efficient motion planning
Ratliff, N., Zucker, M., Bagnell, J. A., & Srinivasa, S. (2009) · 2009 IEEE International Conference on Robotics and Automation · doi:10.1109/robot.2009.5152817 · Cited by 992
Cellular-Enabled UAV Communication: A Connectivity-Constrained Trajectory Optimization Perspective
Zhang, S., Zeng, Y., & Zhang, R. (2019) · IEEE Transactions on Communications · doi:10.1109/tcomm.2018.2880468 · Cited by 426
Malyuta, D., Reynolds, T. P., Szmuk, M., Lew, T., Bonalli, R., Pavone, M., & Açıkmeşe, B. (2022) · IEEE Control Systems · doi:10.1109/mcs.2022.3187542 · Cited by 259
Luis, C. E., & Schoellig, A. P. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2018.2890572 · Cited by 160
Metadata
- Authors
- Schouwenaars, T., De Moor, B., Feron, E., & How, J.
- Venue
- 2001 European Control Conference (ECC)
- Publisher
- IEEE
- Published
- 2001-09
- Pages
- 2603-2608
- OpenAlex
- W1601512022
- Cited by
- 566
- References
- 0
- FWCI
- 17.17
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Mixed integer programming for multi-vehicle path planning. https://app.cochat.ai/papers/10.23919/ecc.2001.7076321
- The paper
- Schouwenaars, T., De Moor, B., Feron, E., & How, J. (2001). Mixed integer programming for multi-vehicle path planning. 2001 European Control Conference (ECC). https://doi.org/10.23919/ecc.2001.7076321
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
