Posture Control Of Robot Research Articles

Fiber optic probe integrated with colloidal nanoparticles with directional diffraction selectivity for magnetic field vector detection

A fiber optic probe integrated with colloidal nanoparticles with directional diffraction selectivity is proposed for wide-bandwidth magnetic field vector detection. The probe is constructed with the multimode fiber in which the end-surface is integrated with the Fe3O4@C colloidal nanoparticles by a silicone tube. The colloidal nanoparticles form a three-dimensional photonic crystal structure by magnetic field for diffraction selectivity. The lattice constant and diffraction angle are adjusted by the intensity and direction of the magnetic field, respectively. Obtaining the directional diffraction light through the magnetic field-induced photonic band gap shift with the wavelength blue shift and reflectivity change is confirmed by theory and experiment. The results show that the maximum sensitivity reaches up to 19.7 nm/mT in response range from 13 mT to 200 mT. For vector detection, the peak wavelength shift from 740 nm to 485 nm and reflectance shift from 71% to 7% covering the 0–45° region is verified. In addition, the proposed method could decouple intensity and direction of the magnetic field completely. The fiber optic probe integrated with colloidal nanoparticles has wide detection range and high sensitivity with rapid response. It will open up new horizons for inspiring design and application of magnetic field vector detection in robot posture control and motion perception.

Smart Pneumatic Artificial Muscle Using a Bend Sensor like a Human Muscle with a Muscle Spindle.

Shortage of labor and increased work of young people are causing problems in terms of care and welfare of a growing proportion of elderly people. This is a looming social problem because people of advanced ages are increasing. Necessary in the fields of care and welfare, pneumatic artificial muscles in actuators of robots are being examined. Pneumatic artificial muscles have a high output per unit of weight, and they are soft, similarly to human muscles. However, in previous research of robots using pneumatic artificial muscles, rigid sensors were often installed at joints and other locations due to the robots' structures. Therefore, we developed a smart actuator that integrates a bending sensor that functions as a human muscle spindle; it can be externally attached to the pneumatic artificial muscle. This paper reports a smart artificial muscle actuator that can sense contraction, which can be applied to developed self-monitoring and robot posture control.

AI-Based Posture Control Algorithm for a 7-DOF Robot Manipulator

With the rapid development of artificial intelligence (AI) technology and an increasing demand for redundant robotic systems, robot control systems are becoming increasingly complex. Although forward kinematics (FK) and inverse kinematics (IK) equations have been used as basic and perfect solutions for robot posture control, both equations have a significant drawback. When a robotic system is highly nonlinear, it is difficult or impossible to derive both the equations. In this paper, we propose a new method that can replace both the FK and IK equations of a seven-degrees-of-freedom (7-DOF) robot manipulator. This method is based on reinforcement learning (RL) and artificial neural networks (ANN) for supervised learning (SL). RL was used to acquire training datasets consisting of six posture data in Cartesian space and seven motor angle data in joint space. The ANN is used to make the discrete training data continuous, which implies that the trained ANN infers any new data. Qualitative and quantitative evaluations of the proposed method were performed through computer simulation. The results show that the proposed method is sufficient to control the robot manipulator as efficiently as the IK equation.

Attitude stability control system of mobile robot mechanism based on nanosensor

Aiming at the poor stability of attitude control of mobile robot mechanism, a kind of attitude stability control system of mobile robot mechanism based on nanodisplacement sensor is designed. In the hardware part, a hydraulic drive is used to control the action posture of the mobile robot, a nanodisplacement sensor is used to collect the walking data of the robot, and serial communication of the upper computer is used to convert the data into electrical signals to realise the robot posture control. In the software part, the mathematical coordinate system of robot walking is constructed, and the rotating posture of the robot is controlled by the Euler angle. The experimental results show that the control performance of the designed system is stable and the control precision is high, which can realise the attitude stabilisation control of the mobile robot.

Stress Isolation Suspension for Silicon-on-Insulator 3-Axis Accelerometer Designed by Topology Optimization Method

Accurate multi-axis inertial sensing is required for self-positioning estimation in automatic driving and robot posture control. In particular, a small bias drift is an important requirement for these applications. The bias drift is primarily caused by the external stress from the package. To reduce the bias drift in micro electro-mechanical systems (MEMS) sensors, a stress isolation suspension (SIS) structure inside the sensor chip is considered promising for miniaturization and cost reduction. To easily design an effective SIS, we propose a new design procedure based on the topology optimization method (TOM). The number of elements for the TOM in MEMS devices is often large owing to narrow lines and gaps such as release holes and comb-shaped electrodes, which increasing the computational cost of a TOM using an iterative algorithm. Before the TOM iterative calculation, we first identify the dominant external force mode affecting the bias drift using a single finite element analysis (FEA) with precise detailed geometry. Based on this, the TOM model is simplified. This combination of FEA and TOM allows a bias-reducing topology-optimized SIS (T-SIS) structure to be designed with reduced computational cost. For validation, we applied the T-SIS design procedure to a capacitive accelerometer for z-axis bias drift reduction and compared its performance to accelerometers without T-SIS. The experimental results indicate that the T-SIS reduces the z-axis bias drift from ±811 mG to ±9.9 mG (temperature range: −30 °C to +70 °C), which is 1/80 of the bias drift of the sensor without T-SIS.

Research on the Posture Control Method of Hexapod Robot for Rugged Terrain

This paper proposes a hexapod robot posture control method for rugged terrain to solve the problem of difficulty in realizing the posture control of a foot robot in rough terrain. The walking gait and original position of a six-legged robot is planned, and the Layer Identification of Tracking (LIT) strategy is developed to enable the robot to distinguish mild rugged terrain and severe rugged terrains automatically. The virtual suspension dynamic model is established. In mild rugged terrain, the posture maintenance strategy is adopted to keep the stability of the torso. In severe rugged terrain, the posture adjustment strategy is adopted to ensure the leg workspace and make it more widely adapt to the changing terrain, and a gravity center position adjustment method based on foot force distribution is designed to use foot force as feedback to control the position and attitude. The experiment of posture control in rough terrain and climbing experiment in the ladder terrain shows that the hexapod robot has good posture maintenance and posture adjustment effects when traversing complex terrain through the posture maintenance strategy and the posture adjustment strategy. Combined with the terrain identification method based on LIT, the hexapod robot can successfully climb the ladder terrain through the identification of the changing ladder terrain, and the movement of the posture adjustment process is stable.

Fractal characteristic analysis of surge impact over shallow underwater vehicle

In the near water surface, the posture control of the underwater vehicle is very important. The underwater vehicle is forced to rotate due to external forces. So, we focus on the surge and the wake flow of thrusters as possible causes of the external forces. Based on fractal dimension concept of fractal theory, the method of short-time fractal dimension is presented to analyse fractal characteristics, focusing on the impact of underwater robot by surge. Respectively, two kinds of surge are introduced: a) surge impacts underwater vehicle from one side; b) surge impacts underwater vehicle from the head. They are analysed every 4s, 2s, 1s and 0.5s. Simulation results show that taking advantage of short-time fractal dimension in underwater vehicle can be dynamically adjusted fuzzy control parameters to improve the posture control of robot under surge.

Modeling and simulation of an artificial muscle and its application to biomimetic robot posture control

The shape memory effect exhibited by Nitinol wire can be utilized to construct an artificial muscle. The muscle is activated by an electric current, which produces heat and initiates a phase transformation. The Nitinol artificial muscle stress–strain–power relationship was determined by experiments, and a mathematical model was developed. The artificial muscle model was utilized for the posture control of a biomimetic underwater robot. The optimal activation patterns for height, pitch, and roll postures were determined. Simulation results for the height postures are in agreement with the experiments. The separation between the center of gravity and the centroid of the robot has a stabilizing effect on pitch and roll postures.