Configuration Space, SLAM and Object Recognition

Running head: CONFIGURATION SPACE, SLAM, AND OBJECT RECOGNITION
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Defining Configuration Space, SLAM and Object recognition
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CONFIGURATION SPACE, SLAM AND OBJECT RECOGNITION 2
Configuration Space (Cs) in robotics is the space of probable positions a robot could
attain. Also, identified as state space, it can be described as the set of possible transformations
applicable to a robot. Clearly understanding the configuration space assists in solving numerous
motion planning challenges that seem different in terms of kinematics and geometry. Most
concepts involving Cs are borrowed directly from mathematics, especially from topology
(Taylor, 2019). For a robot to attain the right position within its state space, its parameters,
which are the generalized coordinates defining the configuration of a system, need to satisfy
mathematical constraints. Classical mechanics literature considers the configuration of a system
to be the positions held by all components and are subject to kinematical constraints. A
significant concept under configuration space is obstacles. Motion Planning algorithms strive to
find a path with minimum collision constraints in the Cs for the robot during its transformations.
In certain instances, the configurations defining the parameters of the robotic movements could
result in the robot colliding with obstacles or lead to certain links of the robot to collide with
each other. The manifold of robot transformations where the collision constraints are present is
identified as the obstacle region. (Lavalle, 2006) The remaining space without any collision
constraint is the precise path that the robot should follow to attain its configuration goal from
start to finish.
A robotic arm is an example where configuration space is applied. A robotic arm is made
up of a number of rigid linkages. The configuration space comprises of the position of each
linkage, subject to the constraints of how linkages attach together, and, its range of motion
beyond its obstacle region.
Simultaneous localization and mapping (SLAM) is the process of developing a map using
a robot or unmanned vehicle navigating an environment while using the map it creates. The