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Recent studies have witnessed a significant progress in developing legged robots with rapid and stable locomotion speeds and adaptability to complex roads, but their high energy consumption limited their development and applications. This paper analyzes the energy efficiency of a bionic electric-drive panda robot serving as an emotional companion for robot-enhanced therapy. Unlike other quadruped robots, our bionic robot focuses on emotional interaction rather than capability of dexterous locomotion and operations. This results in the need to change working period. Then we proposed four strategies to reduce energy consumption. The energy efficiency optimization strategy described in this paper is suitable for quadruped robots focusing on none-highly dynamic motions, and can be treated as locomotion optimization strategy based on energy efficiency optimization for quadruped robots to some extent.

Trajectory tracking control is one of the core techniques that impacts the auto-driving performance of a mobile robot. Whereas, there lacks enough work on reference trajectory generation and controller design for practical usage. This paper considers mobile robots with unicycle vehicle model on which most of automatic guided vehicles (AGVs) in real world are built. A new trajectory planning algorithm is developed, and is applied along with a control law considering constraints of the unicycle model and limited motor capabilities. The proposed algorithm is easy to be implemented on real world AGVs, and it yields a fast, accurate and robust trajectory tracking performance. The effectiveness of the algorithm is validated by simulation tests.

In this paper, we propose a novel design of gaits for space manipulators so as to minimize the dynamic disturbance on a space station. Without modifying their joint configuration, we first propose the use of our previous developed gripping methodology. It combines the concepts of wheels motion in parallel grippers to reduce the swing motions in conventional gaits. For the proposed gaits, three major aspects are considered including 1) linear motion; 2) turning; and 3) exterior transition. Based on the conventional modeling approach for fixed base space manipulators, we extend the method to formulate the dynamic coupling during wheels motion. It is to visualize the manipulator as a prismatic joint with its gripping base moving with wheels motion. Also, we develop an experimental platform for verification. For disturbance analysis, various simulations have been conducted. Results have validated that the proposed gaits generate the lowest disturbance on a space station.

Space robots are in huge demand due to the rapid growth of their service targets, i.e., spacecraft. There are generally large flexible components on spacecraft, such as antenna reflectors and solar paddles. Due to the vibratility of their structure, it is challenging for a space robot with flexible appendages (the base is then called flexible-base) to capture and repair the large flexible spacecraft. After capturing, the two spacecraft with flexible appendages are connected by a space manipulator, and a compounded system is formed. In this paper, we developed a dynamic model and a closed-loop simulation system, to provide a means to verify path planning and control algorithms. Initially, the dynamic characteristics of different capturing stages (preimpact and post-impact) were analyzed. The topologies of a flexible-base space robot and the compounded system were described based on incidence and channel matrices. Secondly, the recursive dynamics was formulated and resolved by an effective numerical method. The modeling was verified by Adams’ model. Thirdly, we implemented a dynamics calculation block in Matlab/Simulink environment using the S-function package for the C program, and developed a closed-loop simulation system, which was composed of the Planning and Controller, the Multibody Dynamic, and the 3D Display modules. Finally, based on the simulation system, two typical missions—target berthing and on-orbital manipulation of the target along a circle, were simulated and evaluated. Dynamics analysis results presented some useful rules for the path planning and control to suppress the vibration of the flexible structure.

Treebot is the first tree-climbing robot that is capable of climbing from a tree trunk to a branch. The robot employs several design principles adapted from arboreal animals, including claw gripping and inchworm locomotion, with a certain artificial optimization to achieve high maneuverability on irregular-shaped trees. Treebot is composed of a pair of tree grippers that permits Treebot to attach to a wide variety of trees with a wide range of gripping curvature, and a novel continuum maneuvering structure that provides high maneuverability and adaptability. In the robot actuation, only five actuators are necessary. Although Treebot weighs only 600 gr, it has a payload capability of 1.75 kg, which is nearly three times its own weight. This paper describes the design process and specifically addresses the robot locomotion and optimization of gripping force. Experimental results demonstrate the robot's ability to climb trees with high maneuverability. © 2012 Wiley Periodicals, Inc. © 2012 Wiley Periodicals, Inc.

Space robotic systems are expected to play an increasingly important role in future space activities. Nevertheless, dynamics modeling and motion planning of a space robot are much more complex than those of a fixed-base robot, due to the dynamic coupling between the manipulator and its base. On the other hand, in order to assure the success of on-orbital missions, many experiments are required to verify the key algorithms on the ground before the space robot is launched. In this paper, the main research achievements on dynamics modeling, path planning, and ground verification are reviewed, and future studies are recommended. Firstly, we summarize the essential modeling concepts, and deduce the kinematics and dynamics equations of a space robot. Secondly, the main motion planning approaches are discussed. Then, different ground verification systems, including the air-bearing table, neutral buoyancy, airplane flying, free-falling motion, suspension system, and hybrid system, are introduced. Finally, the future research trends are forecasted.

Space robotic systems are expected to play an increasingly important role in the future on-orbit service. The applications include repairing, refueling or de-orbiting of a satellite, or removal of the space debris. The dynamical performances of space robotic system result from the multi-physics interactions between mechanical, electrical, electronic, control, etc. In this paper, we developed a unified multi-domain modelling and simulation system. The system is composed of the following modules: the path planner, joint controllers, motor and its driver, gearing mechanism of the space manipulators, the Guidance, Navigation, and Control (GNC) system, the actuators of the base, and the orbital environment, orbital dynamic and the multi-body dynamic of the whole system, etc. Based on this system, the operation during different stages, including far range rendezvous, close range rendezvous (is usually divided into two sub-phases: closing and final approach) and target capturing can be studied from the view of multi-physics domains. The key algorithms, such as pose (position and attitude) measurement, GNC of the base, path planning and control of the space manipulator, and so on, can be validated using the system. As examples, the capturing processes of a moving target under free-floating and attitude-controlled modes are simulated and the simulation results are given.

SUMMARYSpace robotic systems are expected to play an increasingly important role in the future. Unlike on the earth, space operations require the ability to work in the unstructured environment. Some autonomous behaviors are necessary to perform complex and difficult tasks in space. This level of autonomy relies not only on vision, force, torque, and tactile sensors, but also the advanced planning and decision capabilities. In this paper, the authors study the autonomous target capturing from the issues of theory and experiments. Firstly, we deduce the kinematic and dynamic equations of space robotic system. Secondly, the visual measurement model of hand–eye camera is created, and the image processing algorithms to extract the target features are introduced. Thirdly, we propose an autonomous trajectory planning method, directly using the 2D image features. The method predicts the target motion, plans the end-effector's velocities and solves the inverse kinematic equations using practical approach to avoid the dynamic singularities. At last, numeric simulation and experiment results are given. The ground experiment system is set up based on the concept of dynamic simulation and kinematic equivalence. With the system, the experiments of autonomous capturing a target by a free-floating space robot, composed of a 6-DOF manipulator and a satellite as its base, are conducted, and the results validate the proposed algorithm.

Space robots are playing an increasingly important role in on-orbital servicing, including repairing, refueling, or de-orbiting the satellite. The target must be captured and berthed before the servicing task starts. However, the attitude of the base may lean much and needs re-orientating after capturing. In this paper, a method is proposed to berth the target, and re-orientate the base at the same time, using manipulator motion only. Firstly, the system state is formed of the attitude quaternion and joint variables, and the joint paths are parameterized by sinusoidal functions. Then, the trajectory planning is transformed to an optimization problem. The cost function, defined according to the accuracy requirements of system variables, is the function of the parameters to be determined. Finally, we solve the parameters using the particle swarm optimization algorithm. Two typical cases of the spacecraft with a 6-DOF manipulator are dynamically simulated, one is that the variation of base attitude is limited; the other is that both the base attitude and the joint rates are constrained. The simulation results verify the presented method.

With the significant development of robotic technologies, the applications of robots have been extended broadly from their traditional industry role to military, medical field, and even daily services. Robotics has gradually become a very large industry with tremendous influence on the sustainable development of the world.

To provide a high starting torque and to work under a high rpm range are the design requirements for the integrated startgenerators (ISG) used for intelligent vehicles with hybrid powertrains. However, meeting with both of these two requirements usually involves with sophisticated motor and controller design and high manufacturing cost. Hence, a transmission with variable reduction ratio is desired to be configured between the ISG and the engine. In an earlier paper, a Controller-Free Ratio-Variable gearbox design concept has been introduced, which can auto change gear ratios in a purely mechanical way and avoid from using any controller or actuators. This paper represents the work on implementation, testing and evaluation of the gearbox. The performance of the gearbox proof to be functional though the test result.

We have developed a single wheel, gyroscopically stabilized robot. This is a novel concept for a mobile robot that provides dynamic stability for rapid locomotion. The robot is a sharp-edged wheel actuated by a spinning flywheel for steering and a drive motor for propulsion. The spinning flywheel acts as a gyroscope to stabilize the robot and it can be steered by tilting. This robot is nonholonomic in nature, underactuated and inherently unstable in the lateral direction. In this paper, we first develop a three-dimensional (3-D) nonlinear dynamic model and investigate the dynamic characteristics of the robot. We conduct simulations and real-time experiments to verify the model. Both simulations and experiments show that the flywheel has a significant stabilizing effect on the robot. Then, we can decouple the longitudinal and lateral motions of the robot by linearization. We propose a linear state feedback to stabilize the robot at different lean angles, so as to control the steering velocity of the robot indirectly, because the robot steers only by leaning itself to a predefined angle. For the task of path following, we design a controller for tracking any desired straight line without falling. In the controller, we first design the linear and steering velocities for driving the robot along the desired straight line by controlling the path curvature. We then apply the linear state feedback to stabilize the robot at the predefined lean angle such that the resulting steering velocity of the robot converges to the given steering velocity. This work is a significant step toward fully autonomous control of such a dynamically stable but statically unstable system.

Finite-time control of the robot system is studied through both state feedback and dynamic output feedback control. The effectiveness of the proposed approach is illustrated by both theoretical analysis and computer simulation. In addition to offering an alternative approach for improving the design of the robot regulator, this research also extends the study of the finite-time control problem from second-order systems to a large class of higher order nonlinear systems.

A single wheel, gyroscopically stabilized robot was developed to provide a dynamic stability for rapid locomotion. It is a sharp-edged wheel actuated by a spinning flywheel for steering and a drive motor for propulsion. The spinning flywheel acts as a gyroscope to stabilize the robot and it can be tilted to achieve steering. Its nature is nonholonomic, underactuated and inherently unstable in the lateral direction. In this paper, we discuss the problem of controlling the tilt-up motion of such a dynamically stable but statically unstable robot. We first present a dynamic model which is verified through simulations and experiments. Then, we develop a model-based controller for tilt-up motion, assuming that the robot is rolling without slipping. Taking advantage of human skill in teleoperating the robot, we develop a human-based controller for tilt-up motion, in which we train a human control strategy model to abstract the operator’s skill in controlling the tilt-up motion. The controller was successfully implemented, such that the robot can recover from fall automatically. This work is a significant step towards a fully automatic control of such a dynamically stable but statically unstable robot.

In this paper, a novel precise pick and place device (PPD) is proposed for robotic manipulators. It is capable of accurately picking the work pieces and placing them when they are deviated from their initial taught picking positions. In addition, a new muti-line identification algorithm is also developed, which is very effective, especially when the obtained data is limited but needs precise identification. Moreover, the design and implementation of PPD are developed, including hardware design, control algorithm, muti-line fitting approach, offsets calculation and compensation of inverse kinematics, etc. The advantages of PPD are low cost, effective algorithm with high accuracy, when compare with vision or other traditional approaches. Numerous pick and place experiments have been conducted and the results are satisfied.

In this article we present a hybrid systems approach for fault tolerant control of robot manipulators. Our method is based on a combination of fault detection and isolation, control reconfiguration, and control algorithms. The contribution of this work is the construction of a hybrid automaton for control reconfiguration, whose discrete states indicate the number of failed joints, and whose dynamic states are the positions of the joints. With thie proposed method, it is possible to make the manipulator’s end-effector reach any Cartesian configuration inside its workspace irrespective of the number of joint failures. This is a significant property for manipulators operating in environments where actuator repair is too costly or impossible, such as in space or deep-sea. Experimental results with a 3-link planar manipulator illustrate the proposed method.

This paper considers the stabilization problem of uncertain dynamic nonholonomic systems. New robust and adaptive robust control laws are presented with an aim to stabilize the system to the origin with a simple design procedure and no extensive online computations. The designed controllers have been implemented in a nonholonomic wheeled mobile robot, and the application are discussed. Simulation study demonstrates the effectiveness of the proposed method.

The underactuated free floating robot in space is nonlinear systems where velocity and acceleration constraints are both nonintegrable, therefore it is a secondorder nonholonomic system. Some of the existing nonholonomic control methods will not be directly applicable to such systems as it is extremely difficult, if not impossible, to find the control Lie brackets. In this paper, by investigating the system dynamics in depth, a simple velocity-based method is proposed to control the unactuated joints and a multi-step composite strategy to implement orientation tracking tasks. The proposed algorithm is of significance in controlling of space robots when some joints fail to function, or they are intentionally set to be passive for energy efficiency and safety purposes.

This paper presents a novel concept of mobility that provides dynamic stability and rapid locomotion. The concept, called Gyrover, is a single-wheel, gyroscopically stabilized robot that can be considered as a single wheel actuated by a spinning flywheel attached to a two-link manipulator at the wheel bearing and drive motor. The spinning flywheel acts as a gyroscope to stabilize the robot, and it can be tilted to achieve steering. This configuration conveys significant advantages over multiwheel, statically stable vehicles, including good dynamic stability and insensitivity to attitude disturbances, high maneuverability, low rolling resistance, ability to recover from falls, and amphibious capability. In this paper, the authors present the robot concept, three prototypes of the design, and system implementation. The authors study the robot’s nonholonomic constraints and the stabilizing effect of the flywheel on the system through simulation and experiments.

This article discusses the problem of controlling robot manipulators with passive joints, when the number of passive joints is larger than the number of active joints. Assuming that brakes and position sensors are available at each passive joint, we investigate the following issues: (1) what is a sufficient condition for controllability of the passive joints via dynamic coupling with the active joints and how can we quantify the controllability at a given configuration; (2) what is the optimal control and locking sequence of the passive joints; and (3) how can we control both passive and active joints to an equilibrium point in joint space. We propose an optimal control method and demonstrate its validity with both simulation and experimental results. The work presented here is significant because it provides a better understanding and a guideline for utilizing manipulators with passive joints for energy efficiency and fault-tolerant design in applications such as space robotics, hyperredundant robots, and sport mechanics. © 1998 John Wiley & Sons, Inc. 15: 115–129, 1998

In this paper, we discuss the problem of how a free-floating space manipulator can be mapped to a conventional, fixed-base manipulator which preserves both its dynamic and kinematic properties. This manipulator is called Dynamically Equivalent Manipulator (DEM). The DEM concept not only allows us to model a free-floating space manipulator system with simple, well-understood methods, but also to build a conventional manipulator system to experimentally study the dynamic performance and task execution of a space manipulator system, without having to resort to complicated experimental set-ups to simulate the space environment. This paper presents the theoretical development of the DEM concept, demonstrates the dynamic and kinematic equivalence, and presents simulation results to illustrate the equivalence under open-loop and closed-loop control strategies.

In this article, we describe and develop methodologies for modeling and transferring human control strategy. This research has potential application in a variety of areas such as the intelligent vehicle highway system, human-machine interfacing, real-time training, space telerobotics, and agile manufacturing. We specifically address the following issues: (1) how to efficiently model human control strategy through learning cascade neural networks, (2) how to select state inputs in order to generate reliable models, (3) how to validate the computed models through an independent, hidden Markov model-based procedure, and (4) how to effectively transfer human control strategy. We have implemented this approach experimentally in the real-time control of a human driving simulator, and are working to transfer these methodologies for the control of an autonomous vehicle and a mobile robot. In providing a framework for abstracting computational models of human skill, we expect to facilitate analysis of human control, the development of human-like intelligent machines, improved human-robot coordination, and the transfer of skill from one human to another.

The authors have developed a unique, single-wheel robot that exploits gyroscopic forces for steering and stability. Experiments with two working models show promise for the concept for high-speed, rough-terrain and amphibious applications.

This paper presents the optimization for rail-type climbing robot in space application, especially for the rail and mobile base subsystems. Firstly, the rail-type climbing robot is modeled and the evaluation performance indexs are identified. Then five main parameters are modeled and analyzed to find out the contribution function separately. Finally, the system optimization function is built. The output results offer a guideline for space researcher when doing rail-type climbing robot design.

Underactuated manipulators are robot manipulators composed of both active and passive joints in serial chain mechanisms. The study of underactuation is significant for the control of a variety of rigid-body systems, such as free-floating robots in space and gymnasts, whose structure include passive joints. For mechanisms with large degrees of freedom, such as hyper-redundant snake-like robots and multi-legged machines, the underactuated structure allows a more compact design, weight decrease, and energy saving. Furthermore, when one or more joints of a standard manipulator fail, it becomes an underactuated mechanism; a control technique for such system will increase the reliability and fault-tolerance of current and future robots. The goal of this study is to present a robust control method for the control of underactuated manipulators subject to modeling errors and disturbances. Because an accurate modelling of the underactuated system is more critical for control issues than it is for standard manipulators, this method is significant in practice. Variable structure controllers are proposed in both joint space and Cartesian space, and a comprehensive simulation study is presented to address issues such as computation, robustness, and feasibility of the methods. Experimental results demonstrate the actual applicability of the proposed methods in a real two-degrees-of-freedom underactuated manipulator. As it will be shown, the proposed variable structure controller provides robustness againstboth disturbances and parametric uncertainties, a characteristic not present on previously proposed PID-based schemes.

In recent years, researchers have been dedicated to the study of underactuated manipulators, which have more joints than control actuators. In previous work, researchers always assumed that there was enough dynamic coupling between the active and the passive joints of the manipulator for it to be possible to control the position of the passive joints via the dynamic coupling. In this work, the authors aim to develop an index to measure the dynamic coupling, so as to address when control of the under-actuated system is possible, and how the motion and robot configuration can be designed. We discuss extensively the nature of the dynamic coupling and of the proposed coupling index, and their applications in the analysis and design of underactuated systems, through a detailed mathematical analysis and several illustrative examples. © 1995 John Wiley & Sons, Inc.

In this paper, we propose a robust control scheme for a free-floating space robot system where a robot arm is mounted on a free-floating base—a satellite, spacecraft or space station. The base is not controlled by external moments or forces. We model the system as an extended robot, including a pseudo-arm representing the base motion produced by six hypothetical passive joints, and a real robot arm. This model allows us to categorize the free-floating space robot system as a specific type of under-actuated system with mixed passive and active joints. We then discuss some fundamental properties of such a system. By means of an input-output linearization technique, we demonstrate that the internal dynamics of the system are nonlinear parametric and therefore, the control of the system using conventional robot control schemes is not feasible. To overcome the difficulty in controlling the internal dynamics subject to parameter uncertainty, and to avoid the measurement of the base acceleration, we develop a ro...

This paper presents a novel climbing robot called Clothbot which has high maneuverability on flexible clothes. It has a novel gripper consisting of two parallel wheels that can grip continuously and stably on various kinds of clothes. Clothbot also has an omni-directional tail of two DOFs so that it can change its center of gravity to control the moving direction on complex and undeterminate clothes. Consequently, Clothbot is able to access most positions of the clothes by moving straight and turning around with only four motors. It is compact, small and light-weighted but has a load capacity six times its own weight. A series of experiments validate its high performance on flexible clothes.

We have developed a light-weight space manipulator, Self-Mobile Space Manipulator (SM'), in the Robotics Institute at Carnegie Mellon University. SM' is a 7-degreeof-freedom (DOF), 1/3-scale, laboratory version of a robot designed to walk on the trusswork and other exterior surfaces of Space Station Freedom, and to perform manipulation tasks that are required for inspection, maintenance, and construction. Combining the mobility and manip ulation functions in one body as a mobile manipulator, SM2 is capable of routine tasks such as inspection, parts transportation, object lighting, and simple assembly procedures. The system will provide assistance to astronauts and greatly reduce the need for astronaut extra-vehicular activity (EVA). This paper discusses the robot hardware development, gravity compensation system, control structure and teleoperation functions of the SM2 system, and demonstrates its capabilities of locomotion and manipulation in space applications.

In this article we discuss the problem of dynamic coupling and control of a space robot with a free-flying base, which could be a spacecraft, space station, or satellite. We formulate the dynamics of the system systematically and demonstrate nonlinearity of parameterization of the dynamics structure. We study the dynamic coupling of the robot and base system, and propose a concept, i.e., coupling factor, to illustrate the motion and force dependencies. Based on the coupling factor, we define a measure to characterize the degree of the dynamic coupling. The measure can be considered as a performance index in planning robot motion, or in evaluating robot trajectory for minimizing base motion, or in optimizing the robot configuration design and selecting the robot base location. Based on the dynamics analysis, we propose control schemes for position regulation and trajectory tracking problems. The regulation controller is simple to implement and will be useful in regular material transporting tasks. The tracking controller uses a dynamic model and provides more accurate and faster motion, and will be feasible for tracking moving objects or structural inspection tasks. A simulation study is shown at the end of the article. © 1994 John Wiley & Sons, Inc.

In this paper, we discuss the problem of the switching surface for a multivariable variable structure system. We first propose a new switching surface by which robustness of the controlled system to disturbances is provided. Based on the switching surface, we develop control input to drive the system to track the desired trajectory. This control input does not produce the chattering that normally occurs when a conventional control input is used. We apply the proposed method to a multivariable linear system and discuss the simulation results to show the computational procedure and its effectiveness. >

The self-mobile space manipulator, (SM)/sup 2/, is a simple, 5-DOF, 1/3 scale, laboratory version of a robot designed to walk on the trusswork and other exterior surfaces of Space Station Freedom. It will be capable of routine tasks such as inspection, parts transportation and simple maintenance procedures. The authors have designed and built the robot and gravity compensation system to permit simulated zero-gravity experiments. The authors have developed the control system for the (SM)/sup 2/ including control hardware architecture and operating system, control station with various interfaces, hierarchical control structure, multi-phase control strategy for step motion, and various low-level controllers. The system provides operator friendly, real-time monitoring, robust control for 3-D locomotion movements of the flexible robot. A hierarchical structure allows the control to be executed in various levels autonomously or by teleoperation, and a multiphase control strategy facilitates the control in different tasks. Based on the dynamic model developed, a linear-structured joint-level controller and model-based control scheme with acceleration feedback is being implemented to provide a stable and fast motion. The configuration-independent control scheme allows the control parameters to adapt to changes in system dynamics due to the robot configuration variation. With a variety of low-level controllers which the authors developed, the system has demonstrated robustness to the uncertainties in modeling and in payload. >

In this paper, an novel tree gripping mechanism has been proposed for miniature tree-climbing robots. It is capable of attaching on a wide variety of trees with a wide range of gripping curvature. In addition, it is lightweight and simple in control. The gripper is simple in control as it is actuated by one actuator only. In addition, the omni-directional gripping ability also simplifies the use of the gripper as there is no extra actuator needed for orientation control. The special mechanism and optimized settings make the gripper able to attach on different sizes of tree tightly. The mechanism also allows zero energy consumption in static gripping. Numerous on-tree experiments of the proposed mechanism have been conducted and the results are satisfied.

In this paper, we study the stability region for a set of intelligent controllers developed by learning human expert control skills using support vector machines (SVMs). Based on the discrete-time system Lyapunov theory, a Chebychev points based estimation approach is proposed to evaluate the stability region, a key property of this set of SVM-based human learning controllers. One of such learning controllers has been implemented in vertical balance control of a dynamically stable, statically unstable single wheel mobile robot - Gyrover. The experimental results validate the proposed scheme for estimation of the stability region.

State of Charge (SoC) estimation is one of the most significant and difficult techniques to promote the commercialization of electric vehicles (EVs). Suffering from various interference in vehicle driving environment and model uncertainties due to the strong time-variant property and inconsistency of batteries, the existing typical SoC estimators such as coulomb counting and extended Kalman filter cannot perform their theoretically optimal efficacy in practical applications. Aiming at enhancing the robustness of SoC estimation and improving accuracy under the real driving conditions with noises and uncertainties, this paper proposes a framework consisting of (1) an adaptive-κ nonlinear diffusion filter to reduce the noise in current measurement, (2) a self-learning strategy to estimate and remove the zero-drift, (3) a coulomb counting algorithm to realize open-loop SoC estimation, (4) an H ∞ filter to implement closed-loop robust estimation, and (5) a data fusion unite to achieve the final estimation by integrating the advantages of the two SoC estimators. The availability and efficacy of each component have been demonstrated based on comparative studiesin simulation with the conventional approaches respectively, under the testing conditions of noises with various signal-noise-ratios, varying zero-drifts, and different model errors. The overall framework has also been verified to rationally and efficiently combine these components and achieve robust estimation results in the presence of kinds of noises and uncertainties.

Battery fast charging is a crucial issue in both research and application to realize and promote the mass commercialization of electric vehicles, especially pure electric vehicles. However, due to the strong nonlinear properties of batteries, the charging process should take into consideration various factors such as state of charge (SoC), temperature, and charging current, so as to assure the safety, reduce charging time, and enhance charging efficiency. In this paper, we propose a fast charging strategy under the model predictive control framework. Two models are employed to predict SoC and temperature under a sequence of future charging currents. SoC predictor is based on RC equivalent circuit and temperature predictor is based on thermal conduction and convection. The prediction of battery future states allows optimization of the control sequence, with the objectives to follow a predetermined SoC trajectory and to minimize battery temperature rising. Genetic algorithm are introduced to solve the constrained multi-objective optimization problem. The results using Advisor platform demonstrate the availability and efficacy of the proposed framework and prove that it has the ability to reduce charging time and heat generation simultaneously.

To manage the drivestrain and power flow of hybrid electric vehicle (HEV) and achieve balanced performances on fuel economy, emissions, grade ability and acceleration ability, it is necessary to develop a control system with suitable parameters by solving a multi-objective optimization problem. Based on the proof of the relationship between dominating number and diversity in objective-space, a dominating number based multi-objective genetic algorithm is proposed to enhance the diversity of Pareto-front and has been applied to optimize parameters of electric assist control strategy for parallel HEV under standard test procedure provided in Advisor. Simulations under four drive cycles demonstrate availability and efficacy of the proposed algorithm.

The dynamical performances of space robotic system result from the multi-physics interactions between mechanical, electrical, electronic, control, et al. In this paper, we developed a unified multi-domain modeling and simulation platform. The platform is composed of the following modules: the mechanism of the multi-body system; the path planner, the joint axis (including electrical motor and its drive circuit) of the space manipulator; the GNC (guidance, navigation and control) system, and the actuators used for the attitude and orbit control. Based on this platform, the operation during different stages, including far range rendezvous, close range rendezvous (is usually divided into two sub-phases: closing and final approach) and target capturing can be studied from the view of multi-physics domains. The key algorithms, such as pose measurement, GNC of the base, path planning and control of the space manipulator, and so on, can be validated using the system. As an example, the capturing process of a moving target is simulated and the simulation results are given.

State-of-charge (SOC) estimation is the most difficult problem in battery management system, which is one of the key component of electric vehicle and hybrid electric vehicle. Suffered from the non-zero mean noises in practice, the conventional current integral and Kalman filter estimation methods can not achieve the required accuracy, even causing nonconvergent results. According to the SOC truth value obtained by Open-circuit-voltage Vs. SOC curve at each vehicle start time, we deduce a mathematic formula to calculate the mean values of system noises and then a self-learning strategy is proposed to improve the current integral and Kalman filter methods in colored noise environment. The simulation experiment based on a typical battery model verifies the availability and efficiency of proposed strategy.

In this paper, an omni-directional steer-by-wire interface for four wheel independent steering vehicle is presented. The proposed steering interface is an extension of a traditional steering interface that provides three steering inputs. By combination of which, driver can control the vehicle in traditional way or omni-directionally without any mode switching operation. The reservation of the conventional steering behavior makes driver easy to adapt the novel steering interface. The force feedback controller is designed to synchronize the extended steering interface and the orientations of wheels so as to improve vehicle handling. Hardware-in-the-loop simulations are conducted to verify the hardware prototype and examine the proposed algorithms.

Recently, development of mini-sized humanoid robots with a certain level of intelligence becomes a popular research topic. Because of its small size and light weight, those humanoid robots become more portable and attractive. However, extra difficulties are introduced in hardware selection, mechanical design, motion planning, etc. In this paper, we propose the development of a transformable mini-humanoid robot, TMBot including works in mechanical design and motion planning. It is half the size of traditional servo humanoids. To make it to be more portable, it is designed with a function of box transformation. Based on the box like structure, a user can easily put the robot into a bag. It will transform back to the human-like status whenever the user wants to play with it. For the motion planning algorithm, the concept of inverse kinematics is introduced. In the algorithm, 3-D inverse kinematics of the robot is first figured out which is then utilized in gait generation. To ensure the motion stability, a balance control algorithm is developed. It is a geometric method with the application of 3-D inverse kinematics to adjust the tilting of the robot while walking. Experimental results have proved the success of TMBot in terms of portability, gait generation, and tilting correction using the idea of 3-D inverse kinematics based balance control algorithm.

This paper proposed a behavior-based steering controller for four wheel independent steering vehicle. The proposed controller acts as virtual linkages among each wheel to minimize wheel slip resulted by the misalignment of the orientations of wheels effectively. As there is no trajectory planning needed in the control algorithm, the proposed controller is especially suitable for non-autonomous vehicle which the driving path cannot be pre-determined. Numerical simulations to examine the performance of the proposed controller are implemented. Results show the effectiveness and robustness of the proposed behavior-based controller.

Many robotic applications require the direct contact of the end-effector with the environment. Passive compliance attached to the robot wrist, hand, or finger is desirable to produce smooth transitions between the free motion and contact, as well as to allow self-correction in order to accommodate geometric uncertainties in assembly and manufacturing. However, the use of passive compliance degenerates the positioning capability of the manipulator when the robot moves in free space. When the robot makes contact on workpiece, active adjustment of stiffness for various tasks in different directions is needed. We proposed to use passive compliance that is instrumented so that the system provides the necessary flexibility and also sensing to actively control the contact forces or to compensate the positioning error during motion and contact. In this article, the dynamic control of the manipulator with a compliant wrist is addressed. The measured deformation information of the instrumented compliant wrist is utilized in the feedback loop to increase the stiffness of the overall system in position control and to decrease the stiffness in force control. The dynamics model for both unconstrained and constrained cases is established. Applying nonlinear feedback control techniques, the dynamics of the manipulator-wrist system is linearized and decoupled, which allows the controller design to be carried out by using the linear system theory.

State-of-charge (SOC) estimation is the most difficult problem in battery management system, which is one of the key component of electric vehicle and hybrid electric vehicle. Suffered from the non-zero mean noise and uncertain model parameters in practice, the conventional current integral and Kalman filter estimation methods can not achieve the required accuracy, even causing nonconvergent results. The essential difficulties to apply current integral and Kalman filter to solve SOC estimation problem in colored noise and time-variant battery system are analyzed. Hinfin filter, an estimator designed to handle the estimation problem in noised and uncertain situation, is then applied to calculate SOC online. The simulation experiment based on a typical battery model verifies the availability and efficiency of the proposed method.

We have been developing a single wheel, gyroscopically stabilized robot, initially at Carnegie Mellon University. It is a basically single wheel which connected to a spinning flywheel through a two-link manipulator at the wheel bearing. The nature of the system is nonholonomic, nonlinear and underactuated. In this paper, we first develop a dynamic model and decouple the model with respect to the control inputs. We then study the effect of the flywheel dynamics on stabilizing the single wheel robot through simulation and experimental study. Based on understanding of the robot dynamics, we design a linear state feedback controller for the lean angle of the robot. Finally, we discuss the possibility of transferring operator’s manual control directly via learning the mapping between data acquired from the manual control interface and the sensor data from the robot on-board sensors. The experimental results supported the method. The work is significant for understanding the highly coupled dynamics system, and is valuable for developing the automatic control for such a dynamically stabilized robot.

In this paper, an adaptive dynamic programming (ADP) based strategy for real-time energy control of parallel hybrid electric vehicles is presented. The aim is to develop a fuel-optimal control which is not relying on the priori knowledge of the future driving conditions (global optimal control), but only upon the current system operation. Adaptive dynamic programming is an on-line tuning method, which controls the system while simultaneously learning its characteristics in real time. A suboptimal energy control is then obtained with a proper definition of a cost function to be minimized at each time instant. The instantaneous cost function includes the fuel economy, emissions and the deviation of battery soc. Our approach guarantees an optimization of vehicle performance and an adaptation to driving conditions. Simulation results over standard driving cycles are presented to demonstrate the effectiveness of the proposed stochastic approach. It was found that the obtained ADP control algorithm outperforms a traditional rule-based control strategy.