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Abstract This study addresses the challenge of motion control in autonomousvehicles through the introduction of a novel profile generation design. Specifically,autonomous vehicles often contend with uncertain factors and physicallimitations within their operational environments, such as abrupt changes inacceleration or intricate parametric motion profiles. To tackle this problem, afiltering technique for motion profile generation is proposed, leveraging ahardware programming language as its foundation. The investigation begins byanalyzing the specific structure of the mobile platform, which includes twoactive side wheels, two passive rear wheels, a high load capacity, and adifferential drive mode. Building upon this theoretical basis, the proposedfiltering technique is introduced to attain smooth motion profiles and optimizetiming. Furthermore, the study suggests the use of FPGA (Field ProgrammableGate Array) acceleration to expedite these computations for swift motionprocessing. To validate the efficacy of the proposed method, both the mobilevehicle and the load are simulated as a one‐axis linear ball‐screw system withan aluminum ruler. The experimental results unequivocally demonstrate theeffectiveness, feasibility, and applicability of the proposed approach across avariety of industrial solutions.