Animals in nature, such as geckos, inchworms, and felines can climb on various surfaces using different mechanisms and serve as references for the study of bio-inspired robots. This paper presents an inchworm-inspired climbing robot that consists of soft body and feet. The soft robot is actuated by shape memory alloy wires and utilizes microspine arrays to attach its feet to rough or soft surfaces. A series of experiments to test the functionality of the feet and torso of the designed robot have verified the theoretical feasibility of the robot. Results have shown that the designed bio-inspired robot can climb on inclined or vertical curved surfaces and flat surfaces. The robot can also adapt to the underwater environment. Thus, this robot has great potential for various applications such as pipeline inspection.

This paper presents a bionic soft robot with chromatic surface micro-structure (CSM), as a new approach for the measurement of body deformation of the soft robots. Firstly, the CSM films are fabricated by diffraction gratings mold using material polydimethylsiloxane (PDMS). Then, the CSM films are attached to the surface of the soft actuators based on shape memory alloy (SMA) wires. By recording and matching the pattern through two cameras, the continuous deformation curvature degrees of SMA soft actuators are attained. Finally, by integrating three actuators mentioned previously, a bio-inspired prototype of three-legged soft robot is manufactured to carry out motions of both freely and grasp obstacles. By recording and matching the pattern of the robot, we demonstrated a non-contact deformation measurement for flexible devices. As a new non-contact measurement method for body deformation of soft robots, it may shed some light on the issues of the soft robots' sensing and controlling in the future.

Conventional patch clamp techniques require complex manual work. Automated patch clamp systems have been recently developed to eliminate the need of manual handling, but these systems can only perform recordings on suspended cells and require cell dissociation for recordings on adherent cells. Here, we develop a systematic approach to apply electrical resistance feedback for automated patch clamp recording on adherent cells. By developing resistance thresholds in the electrical resistance feedback algorithm, the engaging condition of the adherent cell was automatically determined. We analyze the critical parameters that affect the performance of the automated patch clamp recording. By using the new algorithm for automated engaging and formation, the cell-attached and whole-cell recordings on adherent cells were performed in less than 5 min with the yield of over 70%. The system is designed to directly measure the adherent cells and so, cell dissociation (e.g., trypsin treatment and cell scrapers) can be avoided and the cell properties can be maintained. By using the system, the efficiency of performing the automated patch clamp on adherent cells can be improved, which is of great importance in electrophysiological studies of single cells.

Precise manipulation of microparticles has received considerable attention for its great potential applications to clinical medicine. Among the existing manipulation techniques, the method of magnetic force based manipulation exhibits great advantages for its minimally-invasive feature and insensitivity to biological substance, making it ideally suitable to in vivo environment. On the other hand, increasing demand for accurate and high throughput magnetic manipulation highlights the need of incorporating automation technology in the manipulation. In this paper, we propose an automated control approach to manipulating a magnetic microparticle (bead) with a home-designed electromagnetic coil system. A simplified two-order dynamic model for a microparticle suspended in fluidic environment is established first. A closed-loop controller with utilizing visual feedback is then developed based on input-to-state stability and backstepping methodology. The proposed controller guarantees that the microparticle follows the desired trajectory even in presence of environmental uncertainties and disturbances. Experiments are performed to demonstrate the effectiveness of the proposed approach.

Automatic manipulation and patterning of biological cells into an artificial scaffold is an imperative step in the production of high-quality tissue for tissue transplantation. This paper examines the incorporation of dielectrophoresis into a three-dimensional (3D) scaffold body for batch manipulation and patterning of cells. To facilitate dielectrophoresis-based manipulation, a multi-layer biocompatible scaffold structure utilizing its body as the integrated micro-electrodes was designed and fabricated using soft lithography. Voltage of opposite polarity was applied to the scaffold structure and the resultant electric field from the scaffold body polarized the cells in the culture medium and attracted them to migrate towards the scaffold body. Experiments were conducted and the results confirm that the proposed multi-layer scaffold is capable of generating dielectrophoretic forces to manipulate the cells to the scaffold surface, forming a three-dimensional cellular pattern automatically.

In numerous cellular applications, cells are transported to specific positions or extracted from complex cell solutions. Therefore, an efficient cell transportation path planner for these applications is important for avoiding collisions with other cells or obstacles. In this paper, a path planning approach to transporting cells using a robot-aided optical manipulation system is presented. Optical tweezers functions as a special end-effector in transporting a target cell to the desired position along the generated path. The path planner is designed based on the rapidly exploring random trees (RRT) algorithm for calculating a collision-free path for cell transportation. Both static and dynamic path planners are developed. For the dynamic path planner, an online monitoring strategy is employed to dynamically avoid collisions with randomly appeared obstacles caused by environmental influence such as the Brownian movement of microparticles. Experiments of transporting yeast cells are performed to demonstrate the effectiveness of the proposed approach. Note to Practitioners - Manipulations of cells and other microparticles represent an essential process for most cell-based bioengineering applications, such as cytopathology, cell sociology, and cytotaxonomy. Cell transportation, which is treated as a typical cell manipulation task, has recently received considerable attention because of its wide applications. This paper presents a novel approach to applying RRT-based path planner to cell transportation with a robot-aided optical manipulation system. The research outcome provides a unique solution to achieving cell transportation automatically and efficiently.

This paper proposes a novel and mechanically decoupled leg and wheel hybrid transformable robot called HyTRo-I that combines two mobility concepts. For example, while wheeled vehicles shares higher speed than legged and tracked machines on a flat ground, they have relatively lower degree of flexibility than the other two on irregular terrain. The HyTRo-I robot evolves three motion modes: wheeled rolling, quadrupedal walking and leg-wheel hybrid mode. Despite the over-whelming complexity of obstacles, only several typical obstacles are selected for the study, which are stairs, large protrusions and ditches. Firstly, the transition locomotion mechanism between wheeled rolling mode and quadrupedal walking mode should be studied in detail. In the course of reciprocal transition locomotion, the static and reversible transformation gait not only guarantees the shifting stability and a small number of transition steps, but also the relatively balanced torque of joints. Secondly, after HyTRo-I converting to effective locomotion mode, the adaptive gait control strategies are proposed to traverse three types of obstacles. Finally, a serial of experiments were performed to verify the validity of the proposed transformation gait and adaptive step-up gaits.

This paper presents a path planning approach to the transportation of biological cells with combined robotics and optical tweezers technologies. A rapid path planner based on RRT (Rapidly-exploring random trees) algorithm is applied to find a collision-free path for automatic cell transportation. The optical tweezers are employed to trap and move the cell along the generated path toward a pre-specified goal position. Extending our early reported work on static path planning, a new dynamic path planner that considers the environmental change due to the Brownian movement of the cells is developed. This dynamic path planner can successfully enable the trapped cell to avoid collisions with other cells during transportation in a dynamic environment. Experiments on transporting yeast cells are performed to demonstrate the effectiveness of the proposed approach.

The amphibious robot is so attractive and challenging for its broad application and its complex working environment. It should walk on rough ground, maneuver underwater and pass through transitional terrain such as sand and mud, simultaneously. To tackle with such a complex task, a novel amphibious robot (AmphiHex-I) with transformable leg-flipper composite propulsion is proposed and developed. This paper presents the detailed structure design of the transformable leg-flipper propulsion mechanism and its drive module, which enables the amphibious robot passing through the terrain, water and transitional zone between them. A preliminary theoretical analysis is conducted to study the interaction between the elliptic leg and transitional environment such as granular medium. An orthogonal experiment is designed to study the leg locomotion in the sandy and muddy terrain with different water content. Finally, basic propulsion experiments of AmphiHex-I are launched, which verified the locomotion capability on land and underwater is achieved by the transformable leg-flipper mechanism.

In the existing literatures of multirobots, it is usually assumed that the networked robots remain connected in topology during the task execution. In practice, however, it is not easy to guarantee connectivity of the networked robots in a clustered environment. Failure to maintain connectivity may decrease the performance of the networked robots or even fail the task. In this paper, we propose a multirobot motion coordination strategy that can maintain multirobot connectivity as well as guarantee obstacle avoidance. A potential function is proposed to generate bounded control inputs for networked robots. The efficiency of the proposed approach is demonstrated in both simulation and experiment performed on multirobot consensus tasks.

This paper presents a systematic study of how to enhance recommender systems under volatile user interest drifts. A key development challenge along this line is how to track user interests dynamically. To this end, we first define four types of interest patterns to understand users' rating behaviors and analyze the properties of these patterns. We also propose a rating graph and rating chain based approach for detecting these interest patterns. For each users' rating series, a rating graph and a rating chain are constructed based on the similarities between rated items. The type of a given user's interest pattern is identified through the density of the corresponding rating graph and the continuity of the corresponding rating chain. In addition, we propose a general algorithm framework for improving recommender systems by exploiting these identified patterns. Finally, experimental results on a real-world data set show that the proposed rating graph based approach is effective for detecting user interest patterns, which in turn help to improve the performance of recommender systems.

This paper investigates the problem of delay-dependent robustHinfinfiltering design for a class of uncertain discrete-time state-delayed Takagi-Sugeno (T-S) fuzzy systems. The state delay is assumed to be time-varying and of an interval-like type, which means that both the lower and upper bounds of the time-varying delay are available. The parameter uncertainties are assumed to have a structured linear fractional form. Based on a novel fuzzy-basis-dependent Lyapunov-Krasovskii functional combined with Finsler's lemma and an improved free-weighting matrix technique for delay-dependent criteria, a new sufficient condition for robustHinfinperformance analysis is first derived, and then, the filter synthesis is developed. It is shown that by using a simple linearization technique incorporating a bounding inequality, a unified framework can be developed such that both the full-order and reduced-order filters can be obtained by solving a set of linear matrix inequalities (LMIs), which are numerically efficient with commercially available software. Finally, simulation examples are provided to illustrate the advantages and less conservatism of the proposed approach.

This paper investigates the problem of delay-dependent robust H℞filtering design for a class of uncertain discrete-time state-delayed T-S fuzzy systems. The state delay is assumed to be time-varying and of an interval-like type, which means that both the lower and upper bounds of the time-varying delay are available. The parameter uncertainties are assumed to have a structured linear fractional form. Based on a novel delay and fuzzy-basis-dependent Lyapunov-Krasovskii functional combined with Finsler’s Lemma, a new sufficient condition for robust H℞performance analysis is firstly derived and then the filter synthesis is developed. It is shown that by using a new linearization technique incorporating a bounding inequality, a unified framework can be developed such that both the full-order and reduced-order filters can be obtained by solving a set of linear matrix inequalities, which are numerically efficient with commercially available software. Finally, a numerical example is provided to illustrate the advantages and less conservatism of the proposed approach.

This paper revisits the problem of delay-dependent robust Hinfinfiltering design for a class of continuous-time polytopic linear systems with a time-varying state delay. Based on a delay and parameter-dependent Lyapunov-Krasovskii functional combined with Projection Lemma, a new sufficient condition for robust Hinfinperformance analysis is firstly derived and then the filter synthesis is developed by using a novel matrix linearization technique. It is shown that the desired filters can be constructed by solving a set of linear matrix inequalities. Finally, a numerical example is given to show the effectiveness and less conservatism of the proposed method in comparison with the existing approaches.

A social network consists of events and individuals, in which the events denote the activities happening in the system and the individuals denotes the peoples who are attracted into the activities. A memory feature exists in a dynamic social network which leads to the decay of the event attraction, and further influences the structure and the dynamics of the network. In the paper, an agent model for a social memory network is built and implemented. The simulation result reveals the dynamics of the average life span of events. The result also discovers how a social network with a small "diameter" and a large clustering coefficient evolves. The model is validated with the empirical data from USTC bulletin board system (BBS).

Researchers have recently discovered several interesting, self-organized regularities from the World Wide Web, ranging from the structure and growth of the Web to the access patterns in Web surfing. What remains to be a great challenge in Web log mining is how to explain user behavior underlying observed Web usage regularities. We address the issue of how to characterize the strong regularities in Web surfing in terms of user navigation strategies, and present an information foraging agent-based approach to describing user behavior. By experimenting with the agent-based decision models of Web surfing, we aim to explain how some Web design factors as well as user cognitive factors may affect the overall behavioral patterns in Web usage.