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It is difficult to answer that, as "good odometry" is quite a subjective measurement. In any system that relies on the use of encoders to estimate the travelled trajectory you are going to have accumulated errors, no matter how good they are. To mitigate that effect you should have a sensor that takes measurement from external features, as a laser range finder or RGB-D as the one you mention. With that kind of sensors, you will be able to correct the drift of your encoders and have "good" navigation and mapping.

It is difficult to answer that, as "good odometry" is quite a subjective measurement. In Besides that, in any system that relies on the use of encoders to estimate the travelled trajectory you are going to have accumulated errors, no matter how good they are. To mitigate that effect you should have a sensor that takes measurement from external features, as a laser range finder or RGB-D as the one you mention. With that kind of sensors, you will be able to correct the drift of your encoders and have "good" navigation and mapping.

It is difficult to answer that, as "good odometry" is quite a subjective measurement. Besides that, in any system that relies on the use of encoders to estimate the travelled trajectory you are going to have accumulated errors, no matter how good they are. To mitigate that effect you should have a sensor that takes measurement from external features, as a laser range finder or RGB-D as the one you mention. With that kind of sensors, you will be able to correct the drift of your encoders and have "good" navigation and mapping.

One test that you can do with your current robot to evaluate that is: robot: turn off your odometry (either by changing the topic name or by hardware) and hardware), then see how it works using only your camera for mapping and navigation. I bet it will work just fine.