The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
Motion planning with sequential convex optimization and convex collision checking
Open accessAbstract
We present a new optimization-based approach for robotic motion planning among obstacles. Like CHOMP (Covariant Hamiltonian Optimization for Motion Planning), our algorithm can be used to find collision-free trajectories from naïve, straight-line initializations that might be in collision. At the core of our approach are (a) a sequential convex optimization procedure, which penalizes collisions with a hinge loss and increases the penalty coefficients in an outer loop as necessary, and (b) an efficient formulation of the no-collisions constraint that directly considers continuous-time safety Our algorithm is implemented in a software package called TrajOpt. We report results from a series of experiments comparing TrajOpt with CHOMP and randomized planners from OMPL, with regard to planning time and path quality. We consider motion planning for 7 DOF robot arms, 18 DOF full-body robots, statically stable walking motion for the 34 DOF Atlas humanoid robot, and physical experiments with the 18 DOF PR2. We also apply TrajOpt to plan curvature-constrained steerable needle trajectories in the SE(3) configuration space and multiple non-intersecting curved channels within 3D-printed implants for intracavitary brachytherapy. Details, videos, and source code are freely available at: http://rll.berkeley.edu/trajopt/ijrr .
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Cites
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Real-Time Obstacle Avoidance for Manipulators and Mobile Robots
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A Mathematical Introduction to Robotic Manipulation
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“Sampling-based motion planners [21, 25] are very effective and offer probabilistic completeness guarantees.”
BackgroundSampling-based algorithms for optimal motion planning
Karaman, S., & Frazzoli, E. (2011) · The International Journal of Robotics Research · doi:10.1177/0278364911406761 · Cited by 5,275
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LaValle, S. M. (2006) · Cited by 4,177
RRT-connect: An efficient approach to single-query path planning
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Optimization-Based Collision Avoidance
Zhang, X., Liniger, A., & Borrelli, F. (2021) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2019.2949540 · Cited by 444
Integrated Task and Motion Planning
Garrett, C. R., Chitnis, R., Holladay, R., Kim, B., Silver, T., Kaelbling, L. P., & Lozano-Pérez, T. (2021) · Annual Review of Control, Robotics, and Autonomous Systems · doi:10.1146/annurev-control-091420-084139 · Cited by 409
RAPTOR: Robust and Perception-Aware Trajectory Replanning for Quadrotor Fast Flight
Zhou, B., Pan, J., Gao, F., & Shen, S. (2021) · IEEE Transactions on Robotics · doi:10.1109/tro.2021.3071527 · Cited by 308
Self-citationMalyuta, 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
Metadata
- Authors
- Schulman, J., Duan, Y., Ho, J., Lee, A., Awwal, I., Bradlow, H., Pan, J., Patil, S., Goldberg, K., & Abbeel, P.
- Venue
- The International Journal of Robotics Research
- Publisher
- SAGE Publications
- Published
- 2014-06-11
- Volume
- 33
- Issue
- 9
- Pages
- 1251-1270
- ISSN
- 0278-3649 (ISSN-L)
- 1741-3176
- OpenAlex
- W2142224528
- Cited by
- 866
- References
- 58
- FWCI
- 32.05
- Type
- journal article
- Language
- en
- Open access
- green
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- Schulman, J., Duan, Y., Ho, J., Lee, A., Awwal, I., Bradlow, H., Pan, J., Patil, S., Goldberg, K., & Abbeel, P. (2014). Motion planning with sequential convex optimization and convex collision checking. The International Journal of Robotics Research. https://doi.org/10.1177/0278364914528132
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