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Yes there is. You need to develop or look for the developed equations of velocities that provides the math that transform from the x y theta velocities to the velocities on each of the motors that you have. The equations are for each configuration and depends also on the separation of the wheels, radius of the wheels and orientation of them and also if ...


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Just check out the bug-algorithms like here


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Something like this? It's pretty close to the dimensions you are searching for 23.5x24.5


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The main problem controlling the wheels speed after the kinematics conversion is that you are only controlling the response of the wheels to the setpoint, not the linear velocity response and the angular velocity response. See diagram below. This way, you will normally have 2 similar PIDs calibrated with the same parameters for controlling the wheels. ...


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I don’t think you need any complex sensing device. You could extend the body of your robot to include a housing which holds an LED, aimed toward the mirror and tilted slightly to the interior of your robot. The extended body would block outside light from interfering with the LED signal. You could place a photodiode in your robot to give a binary signal ...


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Your Question is in generall so the answers will be, too. What is your application? It is in Indoor or Outdoor? Do you have a specific SLAM in you mind to use? However, in general, I propose you do not limit your self to monocular cameras. If you are in an indoor environment I propose you RGBD cameras and in an outdoor environment, stereo cameras would be a ...


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In general, there are two options available. The first one is called model predictive control which means to simulate future states of the system and search in the game tree for a pleasant node. The second strategy is “direct control”, which can be realized as a pid controller. The idea is to implement if-then-statements without predicting the future. To ...


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You made a simple mistake while calculating the derivative.The equation is: $\vec{OP}= OP_s \vec {i_s} + P_sP \vec {j_s}$ The derivative should be $\partial \vec{OP}/ \partial t =\partial({OP_s}\vec {i_s})/\partial t + \partial (P_sP \vec {j_s})/\partial t = \partial({OP_s}\vec {i_s})/\partial t $ but it's given that $d\vec{OP_s} / dt = \partial ({OP_s}\...


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The strategy you outlined is up to the task only if the high-level path planning will be undertaking every once in a while the required corrections to compensate for the unavoidable mismatches between the commanded velocities delivered to the system and the actual feedback that might be represented as current locations along a designed path within the map. ...


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