Haibo Gao

Bio: Haibo Gao is an academic researcher from Harbin Institute of Technology. The author has contributed to research in topics: Terramechanics & Hexapod. The author has an hindex of 23, co-authored 212 publications receiving 2190 citations.

A Novel Trapezoid-Type Stick–Slip Piezoelectric Linear Actuator Using Right Circular Flexure Hinge Mechanism

Abstract: A trapezoid-type stick–slip piezoelectric linear actuator using a right circular flexure hinge mechanism was proposed, designed, fabricated, and tested with the aim of accomplishing linear driving based on stick–slip motion. The angle adjustment of the trapezoid beam was used for generating lateral motion on the driving foot of the flexure hinge mechanism. A method of tuning the lateral motion of the flexure hinge mechanism was discussed. Based on the finite-element method, a proper angle of the trapezoid beam was obtained. The analysis results proved that asymmetrical flexure hinge mechanism can increase static friction force in slow extension stage and decrease kinetic friction force in quick contraction stage by lateral motion of the driving foot. A prototype was fabricated and its experimental system was established. The mechanical output experiments showed that the prototype achieved maximum output velocity and load of 5.96 mm/s and 3 N at a voltage of 100 V $p-p$ and a frequency of 500 Hz, respectively.

Foot-terrain interaction mechanics for legged robots: Modeling and experimental validation

Abstract: Contact mechanics plays an important role in the design, performance analysis, simulation, and control of legged robots. The Hunt-Crossley model and the Coulomb friction model are often used as black-box models with limited consideration of the properties of the terrain and the feet. This paper analyzes the foot-terrain interaction based on the knowledge of terramechanics and reveals the relationship between the parameters of the conventional models and the terramechanics models. The proposed models are derived in three categories: deformable foot on hard terrain, hard foot on deformable terrain, and deformable foot on deformable terrain. A novel model of tangential forces as the function of displacement is proposed on the basis of an in-depth understanding of the terrain properties. Methods for identifying the model parameters are also developed. Extensive foot-soil interaction experiments have been carried out, and the experimental results validate the high fidelity of the derived models.

Trilateral Teleoperation of Adaptive Fuzzy Force/Motion Control for Nonlinear Teleoperators With Communication Random Delays

Abstract: In this paper, an adaptive fuzzy control scheme is proposed for hybrid motion/force of trilateral teleoperation systems with a dual-master-single-slave configuration under stochastic time-varying delays in communication channels. Different from previous works on bilateral teleoperation systems, this paper addresses dual-master trilateral control of a single holonomic-constrained robotic manipulator, where the communication delays are modeled as multiple Markov chains, and the motion/force controls are investigated under consideration of unsymmetric stochastic time-varying delays and system dynamical uncertainties. Using partial feedback linearization, the whole trilateral teleoperation system, which consists of both master and slave manipulator dynamics, is transformed into three subsystems. By integrating Markov jump systems to handle random delays, adaptive fuzzy control strategies are developed for the nonlinear teleoperators with modeling uncertainties and external disturbances by using the approximation property of the fuzzy logic systems (FLSs). It is proven that the trilateral teleoperation system is stochastically stable in mean square under specific linear matrix inequality (LMI) conditions, and all the signals of the resulting closed-loop system are uniformly bounded. The proposed scheme is validated by extensive simulations.

Adaptive Neural Network-Based Tracking Control for Full-State Constrained Wheeled Mobile Robotic System

Abstract: In this paper, an adaptive neural network (NN)-based tracking control algorithm is proposed for the wheeled mobile robotic (WMR) system with full state constraints. It is the first time to design an adaptive NN-based control algorithm for the dynamic WMR system with full state constraints. The constraints come from the limitations of the wheels’ forward speed and steering angular velocity, which depends on the motors’ driving performance. By employing adaptive NNs and a barrier Lyapunov function with error variables, then, the unknown functions in the systems are estimated, and the constraints are not violated. Based on the assumptions and lemmas given in this paper and the references, while the design and the system parameters chose properly, our proposed scheme can guarantee the uniform ultimate boundedness for all signals in the WMR system, and the tracking error converge to a bounded compact set to zero. The numerical experiment of a WMR system is presented to illustrate the good performance of the proposed control algorithm.

Linear And Nonlinear Programming

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Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning

Abstract: This paper investigates adaptive fuzzy neural network (NN) control using impedance learning for a constrained robot, subject to unknown system dynamics, the effect of state constraints, and the uncertain compliant environment with which the robot comes into contact. A fuzzy NN learning algorithm is developed to identify the uncertain plant model. The prominent feature of the fuzzy NN is that there is no need to get the prior knowledge about the uncertainty and a sufficient amount of observed data. Also, impedance learning is introduced to tackle the interaction between the robot and its environment, so that the robot follows a desired destination generated by impedance learning. A barrier Lyapunov function is used to address the effect of state constraints. With the proposed control, the stability of the closed-loop system is achieved via Lyapunov’s stability theory, and the tracking performance is guaranteed under the condition of state constraints and uncertainty. Some simulation studies are carried out to illustrate the effectiveness of the proposed scheme.

Fuzzy Adaptive Output Feedback Control of MIMO Nonlinear Systems With Partial Tracking Errors Constrained

Abstract: In this paper, a partial tracking error constrained fuzzy output-feedback dynamic surface control (DSC) scheme is proposed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems. The considered MIMO nonlinear systems contain unknown functions and without the requirement of their states being available for the controller design. With the help of fuzzy logic systems identifying the MIMO unknown nonlinear systems, a fuzzy adaptive observer is established to estimate the unmeasured states. By transforming the tracking errors into new virtual error variables and based on the DSC backstepping recursive design technique, a new adaptive fuzzy output-feedback control method is developed. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are bounded and the partial state tracking errors are confined all times within the prescribed bounds. The simulation results and comparisons with the previous control approaches confirm the effectiveness and utility of the proposed scheme.

Adaptive Locomition of a Multilegged Robot over Rough Terrain

Abstract: Although the off-road mobility characteristics of wheeled or tracked vehicles are generally recognized as being inferior to those of man and cursorial animals, the complexity of the joint-coordination control problem has thus far frustrated attempts to achieve improved vehicular terrain adaptability through the application of legged locomotion concepts. Nevertheless, the evident superiority of biological systems in this regard has motivated a number of theoretical studies over the past decade which have now reached a state of maturity sufficient to permit the construction of experimental computer-controlled adaptive walking machines. At least two such vehicles are known to have recently demonstrated legged locomotion over smooth hard-surfaced terrain. This paper is concerned with an extension of the present theory of limb coordination for such machines to the case in which the terrain includes regions not suitable for weight-bearing and which must consequently be avoided by the control computer in deciding when and where to successively place the feet of the vehicle. The paper includes a complete problem formalization, a heuristic algorithm for solution of the problem thus posed, and a preliminary evaluation of the proposed algorithm in terms of a computer simulation study.