Arm-Stroke Descriptor Variability during 200-m Front Crawl Swimming

The present study aimed to explore the variability of the arm-stroke temporal descriptors between and within laps during middle-distance swimming event using IMMUs. Eight male swimmers performed a 200-m maximum front-crawl in which the inter-lap and intra-lap variability of velocity, stroke rate, stroke-phases duration and arm-coordination index were measured through five units of IMMU. An algorithm computes the 3D coordinates of the wrist by means the IMMU orientation and the kinematic chain of upper arm biomechanical model, and it recognizes the start events of the four arm-stroke phases. Velocity and stroke rate had a mean value of 1.47 ± 0.10 m·s−1 and 32.94 ± 4.84 cycles·min−1, respectively, and a significant decrease along the 200-m (p < 0.001; η2 = 0.80 and 0.47). The end of each lap showed significantly lower stroke rate compared to the start and the middle segment (p < 0.05; η2 = 0.55). No other significant inter-lap and intra-lap differences were detected. The two main findings are: (i) IMMUs technology can be an effective solution to continuously monitor the temporal descriptors during the swimming trial; (ii) swimmers are able to keep stable their temporal technique descriptors in a middle-distance event, despite the decrease of velocity and stroke rate.

Applications of Light-Weight Wearable Devices to Online Programming of Industrial Dual-Arm Robots

Dexterous manipulation of dual-arm robots in unstructured environments is very useful. Programming a dual-arm industrial robot to efficiently complete dexterous tasks, however, is especially challenging due to the complexity of its inverse kinematics, motion planning, dual-arm coordination with self-collision avoidance, and so on. This paper presents a systematic solution to accurately manipulate a dual-arm industrial robot on-site via light-weight wearable devices. In the developed system, the human operator directly drives the robot through the human arms motions tracked by the combination of inertial measurement units and handheld joystick controllers. A proper motion retargeting method with self-collision avoidance is used to enable the user to manipulate the robot directly through intuitive arm motions within a comfortable range and ensure the task manipulation with safety in unstructured environments. The developed system has been tested with various tasks, such as the manipulation of objects of different shapes, dexterous turn-over, and dual-arm coordination. Compared with the existing telerobotic systems, the developed system with simultaneous 14 degree-of-freedom teleoperation directly driven by light-weight wearable devices is able to handle more dexterous and accurate manipulation tasks with the capability of fast deployment and self-collision awareness. Such a solution could pave the way for online dual-arm robot programming on efficient manipulation skills transfer in the future.

Playing a Musical Saw With a Humanoid Robot: Investigation for Industrial Automation

The objective of this study was to automate the dual-arm coordination of a humanoid robot when using a musical saw as a percussion instrument to produce a target sound. We examined the striking motion of the robot using its elastic stiffness, the change in vibration caused by the striking tool resulting from the robot arm-applied force on the saw, and dual arm cooperative motion based on striking sound feedback. To accomplish this, the frequency characteristics of the musical saw and the location of sound generation were determined. Based on the characteristics of the striking task and using an acoustic recognition system, we then developed an impact sound feedback system that could provide performance control of the two humanoid robot arms. The results indicate that humanoid robot can play the musical saw by controlling the curvature freely to achieve target sounds.

A Multi-Priority Control of Asymmetric Coordination for Redundant Dual-Arm Robot

The paper develops a multi-priority control method of asymmetric coordination for a redundant dual-arm robot. A novel dual-arm coordination impedance is introduced to the multi-priority control, and then the performance of the object tracking and the redundant joints is improved by the regulation of the relative Cartesian errors between two arms. The control of asymmetric coordination is divided into the main task and the secondary task. The control of the main task can regulate the two end-effectors’ errors and the relative errors by building the model of spatial parallel spring and damping (SPSDM), which establishes the dual-arm coordination impedance relation in Cartesian space. The control of the secondary task optimizes the performance of the redundant joint impedance and joint limit avoidance in null space. Finally, a typical asymmetric coordination experiment of peg-in-hole is carried out to verify the validity and feasibility of the proposed method. The results indicate that the proposed dual-arm coordination impedance can regulate the relative tracking errors between two objects directly, and in the context of the external impact force applied to the two end-effectors, the peg-in-hole dual-arm task can be achieved successfully.