There has been an increasing interest in cable-driven robotic rehabilitation systems with adjustable stiffness to provide safe and natural interactions for physical therapy. In this paper, we investigate the effectiveness of various stiffness modulation schema and alternate attachment configurations within a scaled planar elastic articulated-cable leg-orthosis emulator for gait training. Elasticity, incorporated by series-elastic springs or adjustable stiffness modules connected to nonflexible cables, can add substantial robustness during forceful interactions with uncertain environments. Other benefits include force-sensor-free tension control, i.e., without using force sensors connected to cables and better overall tension distribution. However, elasticity also degrades the accuracy of positioning and makes the system more disposed to external disturbances. Hence, we examine the performance of actively modulating the effective stiffness to smooth out any perturbations to the scaled normative rehabilitative motion patterns and achieve natural gaits (by simulation and experiment). Stiffness modulation can now be achieved by varying system configuration, antagonistic cable tension, or joint stiffness, and we examine the benefits of each. Finally, we also comparatively evaluate the functional performance of alternate attachment configurations ankle-cable configuration, articulated-cable configuration by way of simulation and experiments.

In network systems with a huge number of nodes, it is not possible to apply input signals to all network nodes to control them. In this paper, we show that this issue can be addressed by designing a network topology so that the nodes in the network system are controllable by a few nodes in the system. A theoretical framework that provides the basic link between structural controllability of network systems and the topology design problem is developed. The results also shed light on how new nodes can be added to the network system without having to introduce new control nodes. Hence, the results are useful in dealing with topology design to obtain a controllable network. Moreover, the results also show under what circumstances a network system with multiple identical nodes is uncontrollable. In many applications, groups of identical nodes are connected to each other which is called network of groups. Here, we address the structural controllability problem for multiple groups of network systems which provides information on proper topology design at both network level (i.e., interconnection of groups) and node level (i.e., interconnection of nodes within a group).

In this paper, we propose an integrated optimal planning and control technique for optical manipulation of a group of cells beyond the field of view. The proposed technique consists of a planning layer where a model predictive control is utilized to obtain a virtual input for manipulation of cells, and a control layer where the desired inputs for laser beams and motorized stage are obtained by means of the control allocation technique. Unlike existing methods on simultaneous manipulation of laser and motorized stage which the desired inputs for lasers and stage are given separately, here, the planning and control layers are integrated together to obtain optimal inputs for both laser and motorized stage. Finally, experimental results are presented to illustrate the performance of the proposed method.

Micromanipulation has received increasing attention from robotics researchers due to its wide applications in the manipulation of microobjects like biological cells and Bio-MEMS components. The demand for accurate and precise manipulation of microobjects opens up new challenges in automation of micromanipulation tasks. In this paper, we present a concurrent framework for optical manipulation of multiple groups of microobjects using robotic tweezers. The proposed framework is based on laser-stage coordination control and consists of two concurrent subschemes: 1) local coordination achieved by asynchronous manipulation of multiple groups of microobjects using laser beams and 2) global coordination achieved by manipulation of whole groups using a motorized stage. Unlike existing methods that are limited to the manipulation of a single microobject or a single group of microobjects, the proposed method considers concurrent laser-stage coordination of multiple groups of microobjects, which enhances the capability and flexibility in micromanipulation tasks. In addition, we introduce a unified social interaction function to achieve various cellular behaviors. A mathematical formulation is provided and stability analysis is presented. Using the proposed method, we are able to manipulate multiple groups of microobjects to construct time-varying microformations. Experimental results are presented to illustrate the performance of the proposed method.

Existing control techniques for optical tweezers utilize a single focused laser beam to directly trap and manipulate a target cell. However, a typical force generated by an optical trap is extremely small (few pico-newtons) and therefore it is not sufficient to manipulate a larger cell or object. The optical trap is also sensitive to the shape of the biological cell and the refractive index. Therefore, current automatic control techniques for optical tweezers cannot be used to manipulate a large cell or cell with irregular shape. In addition, excessive irradiation of the laser beam to the cell may also cause photodamage of even lead to death of the cell. In this paper, we propose a robotic control technique for optical tweezers to achieve automated manipulation of cell, which is beyond the capability of a single optical trap. First, multiple laser beams are generated, and each laser beam is used to trap one micro-particle to create a formation around the target cell to hold it. Then the target cell is manipulated to a desired position by controlling the motorized stage. The proposed control technique is particularly suitable for automated manipulation of sensitive biological cells, cells with large size or cells of irregular shape. Rigorous mathematical formulations have been developed to analyze the control system for automated cell manipulation. Experimental results are presented to illustrate the performance of the proposed controller.

Microbiology is mainly concerned with the study of coexistence, cooperation and interaction among groups of microorganisms. In order to study the biological systems consist of interacting groups of microorganisms, optical manipulation can be utilized as a useful tool. In fact, the ability to manipulate several groups of microorganisms is an essential step towards studying how biological microorganisms communicate and cooperate to perform a wide range of multicellular behaviours. In addition, decomposition of a group of cells into smaller groups gives capability and flexibility in manipulation tasks and remarkably increases environmental adjustability. In this paper, we aim to provide a primary result in micromanipulation of multiple groups of cells. We develop a control methodology for dynamic coordination of multiple groups of cells. A rigorous mathematical formulation is provided and the stability analysis is presented. Using the proposed method, we are able to manipulate multiple groups of microparticles to construct time-varying micro-formations. The proposed method is also useful in examination of the interactions between several groups of living organisms in the desired inter-cellular distance. Experimental results are presented to illustrate the performance of the proposed method.

Multi-cellular aggregation is a fundamental phenomenon observed in many biological processes. Investigating cells aggregation helps us to have better understanding of many biological processes. Moreover, it is useful in finding cure for the diseases caused by cells aggregation. In this paper, we present a control methodology to obtain multi-cellular aggregation by using multiple optical trapping. The proposed method is also useful for study of multiple cell fusion which is an important cellular process. Experimental results are presented to show the effectiveness of the proposed method in achieving multi-cellular aggregation.

This paper addresses the distributed formation trajectory planning for a group of nonholonomic vehicles. This is realized with a decentralized Model Predictive Control under dynamic virtual structure architecture. A specific limitation of virtual structure based formation method is the necessity of access to the desired reference. To remove this requirement, a distributed estimator is developed so that each vehicle can construct the desired reference based on the local information exchange. In formation trajectory planning, several issues are taken into consideration which includes: (i) distributed formation achievement by a team of nonholonomic vehicles from initial situation. (ii) inter-group collision avoidance. (iii) dynamic formation to obtain flexible manoeuvring during movement in unknown and cluttered environment. (iv) obstacle avoidance. Finally, simulation results are presented to illustrate the performance of the proposed methodology in producing optimal formation trajectory planning for multiple nonholonomic vehicles.

In region based shape control of multi-agent systems, the agents move together as a group inside a desired region while maintaining minimum distance among themselves. The desired formation is specified as the desired region for the whole group instead of desired trajectories for individual agents. One limitation of region based shape formation method is the necessity of access to the desired reference of the region i.e. desired movement of the entire group. This paper presents a distributed shape formation control method for multi-agent systems. We develop a state estimator for each agent to construct the desired reference based on local information. A Lyapunov-like function is proposed to examine the stability of the overall system. Simulation results are presented to illustrate the performance of the proposed method in distributed shape formation.

In this paper, we consider leader-based shape coordination for multi-robot systems. It is shown that having knowledge about desired velocity and effective interaction among individuals can help group members to continue the path even after leader failure. Since any collective behavior emerges from interaction among individuals, we propose interactive force to maintain minimum distance among agents as well as group unity during movement even after leader failure. Simulation results are presented to illustrate the performance of proposed method.