In the process of grasping objects by robot, the uncertainty of the object pose has greater impact on the stability of grasping. In this article, an adaptive grasping strategy is proposed to solve the problem of pose uncertainty in the grasping process. The strategy is based on the finger state function to switch control method, so as to realize the contact with the object by the fingers, and the application of grasp force to ensure the pre-grasp stability of the object; then, the object pose error is estimated through the contact between finger and object, and the pose error of the object is compensated according to the different error ranges to reduce the influence of the pose error on the grasp stability. Finally, the grasping experiments by humanoid robot are carried out to verify the performance of the adaptive grasping method proposed in this article.

Elastic elements are commonly adopted to realize underactuation in the design of human-friendly prosthetic hands. The stiffness of these elastic elements, which is a key factor affecting the grasp performance of the underactuated finger, has not well addressed when considering both the stability and adaptability. In this study, an adaptive anthropomorphic finger that adopted a novel nine-bar mechanism is proposed. This nine-bar mechanism is integrated through a coupled four-bar mechanism and an adaptive seven-bar mechanism. The developed finger based on the nine-bar mechanism is able to improve the grasp stability in the global workspace under an extremely small spring stiffness. A quantitative analysis of the grasp stability was carried out. Comparative experiments on the grasps using the finger with/without adaptability were also performed. The results validated that our finger has a good stability when grasping the objects of different sizes.

The force and/or motion transmissibility and the analyticity of inverse kinematics for a thumb mechanism depend on thumb configuration. This paper presents a general framework for the thumb configuration and performance evaluation in the design of dexterous robotic hand. The thumb configuration is described by the functional analysis of human thumb, and the thumb of robotic hand is generalized into 15 configurations. A performance evaluation method is proposed based on kinetostatic and dynamic dexterity as well as workspace. The kinetostatic dexterity is based on a Jacobian matrix condition number (JMCN). A dynamic dexterity measure is presented via acceleration analysis, which keeps a clear geometric meaning. The proposed method is applied to evaluate the performance of three examples, which cover thumb configurations of most existing dexterous hands. Performance evaluation results demonstrate the effectiveness of the proposed method. Using these results and the proposed performance evaluation method, meaningful design principles are presented to guide the design of the thumb configuration.

Purpose: This paper aims to present the design and experiment of a modular multisensory prosthetic hand for applications. Design and experiment of a modular multisensory hand for prosthetic applications. Design/methodology/approach: This paper reveals more details focusing on the appearance, mechanism design, electrical design and control of the prosthetic hand considering anthropomorphism, dexterity, sensing and controllability. The finger is internally integrated with the actuator, the transmission mechanism, the sensors and the controller as a modular unit. Integrated with multiple sensors, the prosthetic hand can not only perceive the position, the contact force and the temperature of the environment like a human hand but also provide the foundation for the practical control. Findings: The experiments show that the prosthetic hand can accurately control the contact force to achieve stable grasps based on the sensors feedback and a simple and effective force-tracking impedance control algorithm. In addition, the experiments based on the cosmesis validate not only the cosmesis functionality but also the control performance for a prosthesis–cosmesis system. Practical implications: Because of the small size, low weight, high integration, modularity and controllability, the prosthetic hand is easily applied to upper-limb amputees. Meanwhile, the finger as a modular unit is easy to be fixed, maintained and applied to a partial upper-limb amputee. Originality/value: Each modular finger of the prosthetic hand integrated with the actuator, the transmission mechanism, the sensors and the controller as a whole can independently control the position and the force. The cosmetic glove design can provide pretty appearance without compromising the control performance.

Purpose: The purpose of this study is to present a novel hybrid closed-loop control method together with its performance validation for the dexterous prosthetic hand. Design/methodology/approach: The hybrid closed-loop control is composed of a high-level closed-loop control with the user in the closed loop and a low-level closed-loop control for the direct robot motion control. The authors construct the high-level control loop by using electromyography (EMG)-based human motion intent decoding and electrical stimulation (ES)-based sensory feedback. The human motion intent is decoded by a finite state machine, which can achieve both the patterned motion control and the proportional force control. The sensory feedback is in the form of transcutaneous electrical nerve stimulation (TENS) with spatial-frequency modulation. To suppress the TENS interfering noise, the authors propose biphasic TENS to concentrate the stimulation current and the variable step-size least mean square adaptive filter to cancel the noise. Eight subjects participated in the validation experiments, including pattern selection and egg grasping tasks, to investigate the feasibility of the hybrid closed-loop control in clinical use. Findings: The proposed noise cancellation method largely reduces the ES noise artifacts in the EMG electrodes by 18.5 dB on average. Compared with the open-loop control, the proposed hybrid closed-loop control method significantly improves both the pattern selection efficiency and the egg grasping success rate, both in blind operating scenarios (improved by 1.86 s, p < 0.001, and 63.7 per cent, p < 0.001) or in common operating scenarios (improved by 0.49 s, p = 0.008, and 41.3 per cent, p < 0.001). Practical implications: The proposed hybrid closed-loop control method can be implemented on a prosthetic hand to improve the operation efficiency and accuracy for fragile objects such as eggs. Originality/value: The primary contribution is the proposal of the hybrid closed-loop control, the spatial-frequency modulation method for the sensory feedback and the noise cancellation method for the integrating of the myoelectric control and the ES-based sensory feedback.