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In this paper, three acceleration-level joint-driftfree (ALJDF) schemes for kinematic control of redundant manipulators are proposed and analyzed from perspectives of dynamics and kinematics with the corresponding tracking error analyses. Firstly, the existing ALJDF schemes for kinematic control of redundant manipulators are systematized into a generalized acceleration-level joint-drift-free (GALJDF) scheme with a paradox pointing out the theoretical existence of the velocity error related to joint drift. Secondly, to remedy the deficiency of the existing solutions, a novel acceleration-level joint-driftfree (NALJDF) scheme is proposed to decouple Cartesian space error from joint space with the tracking error theoretically eliminated. Thirdly, in consideration of the uncertainty at the dynamics level, a multi-index optimization acceleration-level joint-drift-free (MOALJDF) scheme is presented to reveal the influence of dynamics factors on the redundant manipulator control. Afterwards, theoretical analyses are provided to prove the stability and feasibility of the corresponding dynamic neural network (DNN) with the tracking error deduced. Then, computer simulations, performance comparisons and physical experiments on different redundant manipulators synthesized by the proposed schemes are conducted to demonstrate the high performance and superiority of the NALJDF scheme and the influence of dynamics parameters on robot control. This work is of great significance to enhance the product quality and production efficiency in industrial production.

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