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This paper presents the development of a real-time path-planning optimization approach to controlling the motion of space-based robots. The algorithm is capable of designing a trajectory for a robot to navigate within complex surroundings that include numerous obstacles (generalized shapes) and constraints (geometric and performance limitations). The methodology employs a unique transformation that effectively changes a complex optimization problem into one with a positive definite cost function that enables high convergence rates for complex geometries, enabling its application to real-time operations. This strategy was implemented on the Synchronized Position Hold Engage Reorient Experimental Satellite (SPHERES) test-bed on the International Space Station (ISS), and iterative experimental testing was conducted onboard the ISS during Expedition 17 by the first author.

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