Experimental Validation of Pseudospectral-Based Optimal Trajectory Planning for Free-Floating Robots

Abstract

This paper proposes the use of pseudospectral methods to solve the nonlinear trajectory planning problem for freefloating robots. Specifically, three different optimization tools are analyzed. Using each tool, simulations are performed, and it is shown that each solver is capable of finding a deployment trajectory that minimizes the final attitude of a free-floating robot. Each solution is then validated using Pontryagin's minimum principle and Bellman's principle of optimality, as well as by propagating the control torques using a numerical integrator and the dynamics model. Experimental validation is performed at Carleton University's Spacecraft Robotics and Control Laboratory to further investigate the solutions obtained from each tool. Ultimately, it was determined that all solutions resulted in a reduced attitude disturbance at the end of the robotic deployment maneuver.

Riemannian Formulation of Pontryagin’s Maximum Principle for the Optimal Control of Robotic Manipulators

“…This implies that restrictions on these parameters can also be taken into account during the planning stage, so that the controller focuses mainly on the stability and robustness of the trajectory tracking process. Among the optimal control methods, the application of Pontryagin's maximum principle [8][9][10] is certainly one of the most broadly used (some robotics-related examples can be found in [11][12][13][14][15]). It provides an optimality condition that requires to be met at each time during the trajectory.…”

Bounded decoupling control for flexible‐joint robot manipulators with state estimation

“…Flexible‐joint robot manipulator, as a typical representative of non‐linear coupling systems, has complex dynamics relationship between its rigid links and flexible joints, where the joints are commonly driven by elastic mechanisms, such as harmonic reducers or cables [1]. This structure is frequently used in robots in many industrial fields including the aerospace industry [2, 3], where the complicated flexibility effects are exerted on the rigid body of the robot plant with adversely affecting the modelling and control of the manipulators.…”