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Provided you have a high update rate LIDAR (or your robot travels relatively steady and slowly) you can try hector_mapping. As can be seen in the video on the linked page, that can work pretty well while using no odometry at all. So far I had pretty positive feedback by numerous people using it on robots without odometry. The "localization only" mode isn't implemented right now, but having localization through SLAM is probably better than not having localization at all :)

Alternatively you could also try to fake odometry for AMCL either by using the laser_scan_matcher, by using imu data and maybe also desired velocity commands. The latter essentially means generating odometry by converting your cmd_vel commands to fake measured data. This might or might not improve AMCL performance, depending on how closely your robot can follow the motions commmands you provide.

Provided you have a high update rate LIDAR (or your robot travels relatively steady and slowly) you can try hector_mapping. As can be seen in the video on the linked page, that can work pretty well while using no odometry at all. So far I had pretty positive feedback by numerous people using it on robots without odometry. The "localization only" mode isn't implemented right now, but having localization through SLAM is probably better than not having localization at all :)

Alternatively you could also try to fake odometry for AMCL either by using the laser_scan_matcher, by using imu data and maybe also desired velocity commands. The latter essentially means generating odometry by converting your cmd_vel commands to fake measured data. This might or might not improve AMCL performance, depending on how closely your robot can follow the motions commmands motion commands you provide.