Presented in IROS 2023 Workshop "ROBOTIC PERCEPTION AND MAPPING: FRONTIER VISION & LEARNING TECHNIQUES".
experiments
: Contains the implementations for experiments.risam
: Contains the implementation of the algorithm.
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Version Summary (tested and confirmed with the following dependency versions)
- GTSAM: Tag=4.2a8, exact hash=9902ccc0a4f62123e91f057babe3612a95c15c20
- KimeraRPGO: exact hash=8c5e163ba38345ff583d87403ad53bf966c0221b
- dcsam: exact hash=b7f62295eec201fb00ee6d1d828fa551ac1f4bd7
- GCC: 11.4.0
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These should be checked out when the git submodules are initialized, but are included here for completeness
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GTSAM
- Download GTSAM version 4.2a8 ! 4.2a9 not working!
- Setup compile time options required by KimeraRPGO
- Build and optionally install GTSAM (Scripts assume GTSAM python is installed in the active python environment)
-
Clone riSAM and Submodules
git clone --recursive https://github.com/SNU-DLLAB/AGNC-PGO.git
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Build GTSAM
- Configure cmake with following options:
cmake .. -DGTSAM_POSE3_EXPMAP=ON -DGTSAM_ROT3_EXPMAP=ON -DGTSAM_USE_SYSTEM_EIGEN=ON
- Configure cmake with following options:
-
Link GTSAM
- If you
install
GTSAM this should be automatic - If you are working with a local build of GTSAM set
GTSAM_DIR
andGTSAM_INCLUDE_DIR
to the appropriate directories.
- If you
-
Build AGNC-PGO with riSAM
cd AGNC-PGO
mkdir build
cd build
cmake ..
make
The original code is from "Robot Perception Lab - Carnegie Mellon University". link: https://github.com/rpl-cmu/risam