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We report automated nonprehensile magnetic micromanipulation of surrogate biological objects in the presence of a fluid flow. We utilise ferromagnetic microparticles (in the size range of 200 - 350 μm) as microbots and silica beads (having size range of 150 - 350 μm) as surrogate biological objects. The microbot is actuated using magnetic field generated by a set of electromagnetic coils placed in a quadrupole configuration and manipulated using a proportional controller developed for the purpose. We deploy a feedback-based manoeuvre planner that invokes one of the five motion manoeuvres, namely, Arrest, Approach, Align, Push, and Home, based on the instantaneous locations of the microbot, target object, and goal location, for automated nonprehensile manipulation of the target objects. Using this protocol we demonstrate the sorting of surrogate biological objects in a bifurcated fluidic channel. The developed system can be utilised to study the useful properties of large microscopic biological objects in an ambient fluid-flow environment. The demonstrated synergy between microrobotics and microfluidics has tremendous scope for applications in key areas including soft-matter science, cell biology and cancer research. [ABSTRACT FROM AUTHOR]

The problem of nonprehensile manipulation of a stick in three-dimensional space using intermittent impulsive forces is considered. The objective is to juggle the stick between a sequence of configurations that are rotationally symmetric about the vertical axis. The dynamics of the stick is described by five generalized coordinates and three control inputs. Between two consecutive configurations where impulsive inputs are applied, the dynamics is conveniently represented by a Poincaré map in the reference frame of the juggler. Stabilization of the orbit associated with a desired juggling motion is accomplished by stabilizing a fixed point on the Poincaré map. The Impulse Controlled Poincaré Map approach is used to stabilize the orbit, and numerical simulations are used to demonstrate convergence to the desired juggling motion from an arbitrary initial configuration. In the limiting case, where consecutive rotationally symmetric configurations are chosen arbitrarily close, it is shown that the dynamics reduces to that of steady precession of the stick on a hoop. [ABSTRACT FROM AUTHOR]

Robots are expected to replace menial tasks such as housework. Some of these tasks include nonprehensile manipulation performed without grasping objects. Nonprehensile manipulation is very difficult because it requires considering the dynamics of environments and objects. Therefore imitating complex behaviors requires a large number of human demonstrations. In this study, a self-supervised learning that considers dynamics to achieve variable speed for nonprehensile manipulation is proposed. The proposed method collects and fine-tunes only successful action data obtained during autonomous operations. By fine-tuning the successful data, the robot learns the dynamics among itself, its environment, and objects. We experimented with the task of scooping and transporting pancakes using the neural network model trained on 24 human-collected training data. The proposed method significantly improved the success rate from 40.2% to 85.7%, and succeeded the task more than 75% for other objects.

Pivoting gait is an efficient way for robots to manipulate a heavy object. Although we can cope with the contact constraints of the pivoting gait by using the model predictive control (MPC), systems with complex dynamics, including the pivoting gait, usually require long horizons in the MPC and it leads to a heavy computational load. To overcome this problem, we introduce basis functions to parameterize the free variables in the MPC and formulate an optimization problem with new decision variables, which are coefficients of the basis functions. We especially introduce multiple basis functions and compare their performances in generating the robotic pivoting gait. As a result, the most effective reduction in the dimension of the free variables is achieved by using the Laguerre basis function and the computational efficiency of the MPC is greatly improved. The simulation and experiments show that the time cost of the generation of pivoting gaits by the proposed method is remarkably reduced and the generated pivoting gaits are feasible and robust where a dual-arm robot successfully manipulates a toy piano by the pivoting gait. [ABSTRACT FROM AUTHOR]

Pivoting gait, in which a robot iteratively tilts an object, rotates it around a vertex, and then places it down on the floor, is efficient for manipulating a large and heavy object with a relatively small manipulating force. However, pivoting gait can easily fail, even with a small external disturbance, due to its instability. To address this problem, we propose a controller to robustly control the object’s motion during pivoting gait by introducing two gait modes, i.e., double-support mode, which can manipulate a relatively light object with higher speed, and quadruple-support mode, which can manipulate a relatively heavy object with slower speed. To control the pivoting gait, a graph model predictive control is applied by considering these two gait modes. The experiments show that by adaptively switching the gait mode according to the applied external disturbance, a robot can stably perform the pivoting gait even when an external disturbance is applied to the object. The experimental results lead us to automate the manipulation of a large and heavy object.

In robots, nonprehensile manipulation operations such as pushing are a useful way of moving large, heavy, or unwieldy objects, moving multiple objects at once, or reducing uncertainty in the location or pose of objects. In this study, we propose a reactive and adaptive method for robotic pushing that uses rich feedback from a high-resolution optical tactile sensor to control push movements instead of relying on analytical or data-driven models of push interactions. Specifically, we use goal-driven tactile exploration to actively search for stable pushing configurations that cause the object to maintain its pose relative to the pusher while incrementally moving the pusher and object toward the target. We evaluate our method by pushing objects across planar and curved surfaces. For planar surfaces, we show that the method is accurate and robust to variations in initial contact position/angle, object shape, and start position; for curved surfaces, the performance is degraded slightly. An immediate consequence of our work is that it shows that explicit models of push interactions might be sufficient but are not necessary for this type of task. It also raises the interesting question of which aspects of the system should be modeled to achieve the best performance and generalization across a wide range of scenarios. Finally, it highlights the importance of testing on nonplanar surfaces and in other more complex environments when developing new methods for robotic pushing. [ABSTRACT FROM AUTHOR]

This paper discusses a nonprehensile manipulation method using a vibrating plate driven by a single actuator. Non-uniform friction distribution is employed to generate three-DoF (degrees of freedom) motion of an object on the plate. First, an analytical model of plate-object system is introduced. Based on the model, the object velocity for given elliptical vibration orbit and surface friction coefficient of the plate is explored. It is revealed that there exists particular parameter setting where the moving direction of the object reversed as the increase of the frequency of the vibration of the plate. Then, three types of non-uniform friction distribution including the particular friction condition are introduced. It is shown that such non-uniform friction distributions have a potential to induce three-DoF motion of the object. Finally, the proposed method is experimentally validated.

To achieve human-level object manipulation capability, a robot must be able to handle objects not only with prehensile manipulation, such as pick-and-place, but also with nonprehensile manipulation. To study nonprehensile manipulation, we studied robotic batting, a primitive form of nonprehensile manipulation. Batting is a challenging research area because it requires sophisticated and fast manipulation of moving objects and requires considerable improvement. In this paper, we designed a batting system for dynamic manipulation of a moving ball and proposed several algorithms to improve the task performance of batting. To improve the recognition accuracy of the ball, we proposed a circle-fitting method that complements color segmentation. This method enabled robust ball recognition against illumination. To accurately estimate the trajectory of the recognized ball, weighted least-squares regression considering the accuracy according to the distance of a stereo vision sensor was used for trajectory estimation, which enabled more accurate and faster trajectory estimation of the ball. Further, we analyzed the factors influencing the success rate of ball direction control and applied a constant posture control method to improve the success rate. Through the proposed methods, the ball direction control performance is improved. [ABSTRACT FROM AUTHOR]

This article discusses nonprehensile manipulation of an asymmetric object using a robotic manipulator from a motion planning point of view. Four different aspects of the problem will be analyzed:object stability, motion planning, manipulator control, and experimental validation. Specifically, via an analysis of marginal stability of an object resting on a moving tray, the work establishes the critical accelerations of the manipulator's end-effector, below which the object's stability is guaranteed. These critical accelerations guide the design of the end-effector's motion for successful nonprehensile manipulation of the object. In particular, we propose two methods to formulate polynomial asymmetric s-curve trajectories such that the end-effector completes its motion in minimum time. In one method, the trajectory is divided into segments whose time intervals are then computed via a recursive algorithm. In the other method, we formulate an optimization problem and design the minimum-time trajectory by balancing the tradeoff between the travel time and actuator effort. A series of experiments with a robotic arm is designed to validate and compare these motion planning methods in the context of nonprehensile manipulation. In addition, the experimental results demonstrate the advantages of the asymmetric s-curve motion profiles over the traditional symmetric s-curves. [ABSTRACT FROM AUTHOR]

Tactile sensing is a key sensor modality for robots interacting with their surroundings. These sensors provide a rich and diverse set of data signals that contain detailed information collected from contacts between the robot and its environment. The data are however not limited to individual contacts and can be used to extract a wide range of information about the objects in the environment as well as the actions of the robot during the interactions. In this article, we provide an overview of tactile information and its applications in robotics. We present a hierarchy consisting of raw, contact, object, and action levels to structure the tactile information, with higher-level information often building upon lower-level information. We discuss different types of information that can be extracted at each level of the hierarchy. The article also includes an overview of different types of robot applications and the types of tactile information that they employ. Finally we end the article with a discussion for future tactile applications which are still beyond the current capabilities of robots. [ABSTRACT FROM AUTHOR]

Nonprehensile manipulation produces underconstraint motions that are sensitive to environmental dynamics. Legged locomotion constitutes a floating-based movement, whose dynamic is underactuated with respect to the inertial frame. When these two tasks are combined, system motion planning and control are complex due to their inherent underactuated features. This article presents a motion planning framework for a legged robot that uses its limbs for nonprehensile manipulation, as well as locomoting motions. First, issues related to the description of the robot–object–environment system and the task are presented. The velocity constraint that prevents separation and the force constraint that restricts interactive forces are then integrated into the system dynamic model to produce bounds on the system acceleration as a function of the system state. Then, we solve the motion planning problem by reducing the system dimensions in operational space and programming feasible trajectories within the phase plane. This approach is employed to control the quadruped robot TITAN-VIII to manipulate objects and locomote itself using Drive Mode, Inchworm Mode, Scoot Mode, and Throw Mode. Experimental results obtained through simulations and physical tests are reported to demonstrate the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

In this paper, we present a feedback controller that enables contact juggling manipulation of a disk with a disk-shaped manipulator, called the mobile disk-on-disk. The system consists of two disks in which the upper disk (object) is free to roll on the lower disk (hand) under the influence of gravity. The hand moves with a full three degrees of freedom in a vertical plane. The proposed controller drives the object to follow a desired trajectory through rolling interaction with the hand. Based on the mathematical model of the system, dynamic feedback linearization is used in the design of the controller. The performance of the controller is demonstrated through simulations considering disturbances and uncertainties.

This paper presents a novel method for nonprehensile manipulation of parts on a circularly oscillating platform when the effective coefficient of dry friction between the part and the platform is being dynamically controlled. Theoretical and experimental analyses have been performed to validate the proposed method and to determine the control parameters that define the characteristics of the part’s motion. A mathematical model of the manipulation process with dynamic dry friction control was developed and solved. The modeling showed that by changing the phase shift between the function for dynamic dry friction control and the function defining the circular motion of the platform, the part can be moved in any direction as the angle of displacement can be controlled in a full range from 0 to 2π. The nature of the trajectory and the mean displacement velocity of the part mainly depend on the width of the rectangular function for dynamic dry friction control. To verify the theoretical findings, an experimental setup was developed, and experiments of manipulation were carried out. The experimental results qualitatively confirmed the theoretical findings. The presented analysis enriches the classical theories of nonprehensile manipulation on oscillating platforms, and the presented findings are relevant for mechatronics, robotics, mechanics, electronics, medical, and other industries.

When robots are used to manipulate objects in various ways, they often have to consider the dynamic constraint. Machine learning is a good candidate for such complex trajectory planning problems. However, it sometimes does not satisfy the task objectives due to a change in the objective or a lack of guarantee that the objective functions will be satisfied. To overcome this issue, we applied a method of trajectory deformation by using sequence-to-sequence (seq2seq) models. We propose a method of adjusting the generated trajectories, by utilizing the architecture of seq2seq models. The proposed method optimizes the latent variables of the seq2seq models instead of the trajectories to minimize the given objective functions. The verification results show that the use of latent variables can obtain the desired trajectories faster than direct optimization of the trajectories. [ABSTRACT FROM AUTHOR]

This work addresses the problem of object delivery with a mobile robot in real-world environments. We introduce a multilayer, modular pushing skill that enables a robot to push unknown objects in such environments. We present a strategy that guarantees obstacle avoidance for object delivery by introducing the concept of a pushing corridor. This allows pushing objects in scattered and dynamic environments while exploiting the available collision-free area. Moreover, to push unknown objects, we propose an adaptive pushing controller that learns local inverse models of robot-object interaction on the fly. We performed exhaustive tests showing that our controller can adapt to various unknown objects with different mass and friction distributions. We show empirically that the proposed pushing skill leads towards successful pushes without prior knowledge and experience. The experimental results also demonstrate that the robot can successfully deliver objects in complex scenarios. [ABSTRACT FROM AUTHOR]

This paper proposes a dexterous nonprehensile manipulation using the vibration of a plate, in which a three-degree-of-freedom (DoF) motion of a part is controlled based on a single actuator. First, a manipulator whose end effector is a flat plate is introduced. The manipulator employs a hybrid joint mechanism with a viscoelasticity and a nonparallel axis layout. The characteristic of the mechanism is that the shape, orientation, and size of the vibrational orbit of the plate vary based on the sinusoidal displacement input to the actuator. Subsequently, the trajectories of multiple point masses on the plate are analyzed to understand the approximated three-DoF motion of a part. The simulation results reveal that the whirlpool-like characteristics of the trajectory map, which aid in the rotational and translational motions of the part, can be managed by the input frequency, offset angle, and amplitude of the sinusoidal displacement input. Based on the trajectory maps, nine primitives for manipulating the part are designed. Finally, the proposed manipulation scheme is experimentally validated using a prototype. After confirming the nine primitives in the experiment, applications to one-DoF, two-DoF, and three-DoF parts feeding tasks are demonstrated. [ABSTRACT FROM AUTHOR]

To achieve human-level object manipulation capability, a robot must be able to handle objects not only with prehensile manipulation, such as pick-and-place, but also with nonprehensile manipulation. To study nonprehensile manipulation, we studied robotic batting, a primitive form of nonprehensile manipulation. Batting is a challenging research area because it requires sophisticated and fast manipulation of moving objects and requires considerable improvement. In this paper, we designed a batting system for dynamic manipulation of a moving ball and proposed several algorithms to improve the task performance of batting. To improve the recognition accuracy of the ball, we proposed a circle-fitting method that complements color segmentation. This method enabled robust ball recognition against illumination. To accurately estimate the trajectory of the recognized ball, weighted least-squares regression considering the accuracy according to the distance of a stereo vision sensor was used for trajectory estimation, which enabled more accurate and faster trajectory estimation of the ball. Further, we analyzed the factors influencing the success rate of ball direction control and applied a constant posture control method to improve the success rate. Through the proposed methods, the ball direction control performance is improved.

Abstract This study proposes a mechanism and a methodology for large force input to the environment by a mobile robot. To determine the limits on the force that a mobile robot can apply to a target object, we analyzed the forces between the robot, ground, and object, and the frictional-force limits between any two of these three bodies. To prevent the mobile robot from falling during the large-force application, the manipulator is connected to the robot via a passive rotational joint. This mechanism enables the mobile robot to search the environmental parameters. A new mobile robot fitted with the proposed mechanism, named ARODA, was developed. In a validation experiment, the developed mobile robot successfully tilted a relatively large and heavy object while searching the environmental parameters (the frictional coefficients of the floor and object and the size of the object). Equipped with the proposed mechanism, the mobile robot refrained from falling while applying a large force to the object by trial and error. Highlights • A mechanism for a mobile robot to apply a large force without falling is proposed. • The mobile robot with the proposed mechanism named ARODA is developed. • The ARODA successfully tilted a heavy object while searching the unknown parameters. [ABSTRACT FROM AUTHOR]

This paper addresses a remaining gap between today's academic catching robots and their future in industrial applications: reliable task execution. A novel parameterization is derived to reduce the three-dimensional (3-D) catching problem to 1-D on the ballistic flight path. Vice versa, an efficient dynamical system formulation allows reconstruction of solutions from 1-D to 3-D. Hence, the body of the work in hybrid dynamical systems theory, in particular on the 1-D bouncing ball problem, becomes available for robotic catching. Uniform Zeno asymptotic stability from bouncing ball literature is adapted, as an example, and extended to fit the catching problem. A quantitative stability measure and the importance of the initial relative state between the object and end-effector are discussed. As a result, constrained dynamic optimization maximizes convergence speed while satisfying all kinematic and dynamic limits. Thus, for the first time, a quantitative success-oriented comparison of catching motions becomes available. The feasible and optimal solution is then validated on two symmetric robots autonomously playing throw and catch. [ABSTRACT FROM AUTHOR]

Equilibrium points exploration is crucial for successful nonprehensile manipulation of multi-link objects by cooperative arms which is promising for a class of future robotics applications. This paper presents the equilibrium area numerical analysis, with experimental verification, for nonprehensile manipulation of a three-rigid link object by two cooperative arms in a plane. Inspired by an assistive nursing robot project for manipulating a patient, the interaction between the object and the arms is performed in a way that one of the arms contacts two links of the object while the other arm contacts the object third link. It would be a useful step for the most complicated process of a patient manipulation. The purpose of the equilibrium area analysis is to obtain the equilibrium contact area, associated with different interaction forces, for statically holding the object at all its possible configurations. The dynamic model of the system is presented from which the static equations are deduced. Static equations are analyzed in the presence of friction forces and motion constraints leading to equilibrium contact lengths for a range of angles leading to equilibrium area for every object's configuration. Numerical simulation results for the equilibrium area analysis are presented. Experimental results, for validating the presented numerical results, are also introduced. [ABSTRACT FROM AUTHOR]

This paper presents a novel nonprehensile manipulation method that uses the vibration of a plate, where the two degrees of freedom of a part on the plate are controlled by only one actuator. First, a manipulator whose end effector is a flat plate is introduced. By employing an underactuated joint mechanism, the shape and orientation of the vibrational orbit of the plate vary according to frequency and offset angle of the sinusoidal displacement input to an actuator. Then, simulation analyses reveal that the manipulator can omnidirectionally induce translational velocity to the part on the plate. There exists an orthogonality between the effects of the frequency and offset angle on the velocity map of the part. Based on this characteristic, a visual feedback control for manipulating the part is designed. Finally, the proposed method is validated via experiments using a prototype manipulator. A target-trajectory tracking task and a four-way part-feeding task are demonstrated.

The task of inducing, via continuous static state-feedback control, an asymptotically stable heteroclinic orbit in a nonlinear control system is considered in this paper. The main motivation comes from the problem of ensuring convergence to a so-called point-to-point maneuver in an underactuated mechanical system. Namely, to a smooth curve in its state–control space which is consistent with the system dynamics and connects two (linearly) stabilizable equilibrium points. The proposed method uses a particular parameterization, together with a state projection onto the maneuver as to combine two linearization techniques for this purpose: the Jacobian linearization at the equilibria on the boundaries and a transverse linearization along the orbit. This allows for the computation of stabilizing control gains offline by solving a semidefinite programming problem. The resulting nonlinear controller, which simultaneously asymptotically stabilizes both the orbit and the final equilibrium, is time-invariant, locally Lipschitz continuous, requires no switching, and has a familiar feedforward plus feedback–like structure. The method is also complemented by synchronization function–based arguments for planning such maneuvers for mechanical systems with one degree of underactuation. Numerical simulations of the non-prehensile manipulation task of a ball rolling between two points upon the "butterfly" robot demonstrates the efficacy of the synthesis. [ABSTRACT FROM AUTHOR]

The last two decades have seen a number of developments in creating robots to play billiards. The designed robotic systems have successfully incorporated the kinematics required and have had appropriate machine vision elements for a decent gameplay. Independently, computer scientists have also developed the artificial intelligence programs needed for the strategy to play billiards. Despite these developments, the accurate ball manipulation aspect of the game, needed for good performance, has not been addressed enough; two important parameters are the potting accuracy and advantageous cue ball positioning for next shot. In this regard, robotic ball manipulation by predicting the ball trajectories under the action of various dynamic phenomena, such as ball spin, impacts and friction, is the key consideration of this research. By establishing a connection to the methods used in nonprehensile robotic manipulation, a forward model is developed for the rolling, sliding, and two distinct types of frictional impacts of billiards balls are developed. High-speed camera-based tracking is performed to determine the physical parameters required for the developed dynamic models. To solve the inverse manipulation problem, i.e., the decision on shot parameters, for accurate ball positioning, an optimization based solution is proposed. A simplistic ball manipulator is designed and used to test the theoretical developments. Experimental results show that a 90% potting accuracy and a 100–200 mm post-shot cue ball positioning accuracy has been achieved by the autonomous system within a table area of $6 \times 5$ ft2. [ABSTRACT FROM PUBLISHER]

A new theory in contact pressure distribution and friction limit surfaces for modeling of hemicylindrical soft fingertips is introduced, to define the relationship between friction force and the moment with respect to the normal axis of contact. A general pressure-distribution function is proposed to capture material properties and contact geometry with various pressure profiles, and the coefficient of pressure distribution over the rectangular contact area is found between π and π/2. Combining the results of the contact mechanics model with the contact pressure distribution, the normalized friction limit surface can be derived for anthropomorphic soft fingers. The numerical friction limit surface of hemicylindrical soft-finger contact can be approximated by an ellipse, with the major and minor axes as the maximum friction force and the maximum moment with respect to the normal axis of contact, respectively. The results show that the friction limit surfaces are improved (13%–17%), if hemicylindrical fingertips are used rather than hemispherical fingertips at the same radius of fingertip, shape factor of the pressure profile, and applied load. Furthermore, the results of the contact mechanics model and the pressure distribution for soft fingers facilitate the construction of numerical friction limit surfaces, enabling to analyze and simulate the contact behaviors of grasping and manipulation in humanoid robots, prosthetic hands, and robotic hands. [ABSTRACT FROM AUTHOR]

This paper presents feedback stabilization control of a rolling manipulation system called the disk-on-disk. The system consists of two disks in which the upper disk (object) is free to roll on the lower disk (hand) under the influence of gravity. The goal is to stabilize the object at the unstable upright position directly above the hand. We show that it is possible to stabilize the object at the upright position, while the hand or object rotates to a specific orientation or spins at a constant velocity. We use full-state feedback linearization to derive control laws. We present simulation as well as experimental results demonstrating the controllers. [ABSTRACT FROM PUBLISHER]

A rigid plate end-effector at the tip of a high-speed manipulator can remotely manipulate an object without grasping it. This paper discusses a dynamic nonprehensile manipulation strategy to rotate thin deformable objects on a rigid plate with two degrees of freedom (DOFs). The deformation of the object due to dynamic effects is exploited to produce fast and stable rotation. By varying the frequency of the rotational component of the plate’s motion, we show that the dynamic behavior of the object mimics either a sliding, walking, or running gait of a biped. We introduce a model to simulate this type of system in which the object is constructed of multiple nodes that are connected by viscoelastic joint units with three DOFs. The joint’s viscoelastic parameters are estimated experimentally in order to model real food. Afterward, simulation analysis is used to investigate how the object’s rotational behavior and its angular velocity change with respect to the plate’s motion frequency. We show how the object’s behavior during rotation is analogous to bipedal sliding, walking, and running gaits and then obtain optimal plate motions leading to the maximal angular velocity of the object. We also reveal that an appropriate angular acceleration of the plate is essential for a dynamically stable and fast object’s rotation. We further show that the friction coefficient that maximizes the object’s angular velocity depends on its gait. [ABSTRACT FROM AUTHOR]

Distributed manipulation systems induce motions on objects through the application of many external forces. Many of these systems are abstracted as planar programmable force fields. Quadratic potential fields form a class of such fields that lend them- selves to analytical study and exhibit useful stability properties. This paper introduces a new methodology to build quadratic potential fields with simple devices using the naturally existing phenomena of airflow, which is an improvement to the traditional use of the complicated programmable actuator arrays. It also provides a basis for the exploitation, in distributed manipulation, of natural phenomena like airflow, which require rigorous analysis and display stability difficulties. A demonstration and verification of the theoretical results for the special case of the elliptic field with airflows is also presented. [ABSTRACT FROM AUTHOR]

We describe a programmable apparatus that uses a vibrating surface for sensorless, nonprehensile manipulation, where parts are systematically positioned and oriented without sensor feedback or force closure. The idea is to generate and change the dynamic modes of a vibrating surface. Depending on the node shapes of the surface, the position and orientation of the parts can be predicted and constrained. The vibrating surface creates a two-dimensional force vector field. By chaining together sequences of force fields, the equilibrium states of a part in the field can be successively reduced to obtain a desired final state. We describe efficient polynomial-time algorithms that generate sequences of force fields for sensorless positioning and orienting of planar parts, and we show that these strategies are complete. Finally we consider parts feeders that can only implement a finite set of force fields. We show how to plan and execute strategies for these devices. We give numerical examples and experiments. and discuss tradeoffs between mechanical complexity and planning complexity. [ABSTRACT FROM AUTHOR]

This paper reports a feedback-based manoeuvre planning approach for automated nonprehensile selective micromanipulation of large, microscopic biological objects (∼ 100 μ m). We employ ferromagnetic micro-particles as microrobots actuated via a global magnetic field produced by electromagnetic coils placed in quadrupole configuration. The microrobot motion is programmed to push the target object to the goal location. We employ a three-step approach comprising: (a) generate a collision-free optimal path between the initial and the commanded goal location, (b) generate a manoeuvre planning algorithm that invokes one of the three motion manoeuvres, namely, 'approach', 'push', and 'align' depending upon the instantaneous locations of the microrobot, target object, and the desired waypoint, and (c) deploy a simple proportional controller that determines the currents required in the electromagnetic coils that can produce a suitable magnetic field for executing the manoeuvre invoked by the manoeuvre planner. This paper reports a number of validation experiments conducted on both zebrafish, i.e., Danio rerio embryos and silica beads as target objects. We envisage that the developed inexpensive approach can be useful in robotic manipulation of biological objects with sizes in hundreds of microns including large biological cells, polyploid giant cancer cells (PGCC), multicellular spheroids, Dictyostelium slug, human oocytes, and autophagy candidates. We also believe that functionalizing the microrobots with living cells or suitable chemicals will make it possible to perform on-chip biological experiments in future. • Automated nonprehensile magnetic micromanipulation of large (∼ 100 μ m) microscopic biological objects. • Path planning for the generation of a collision-free optimal path to minimize travel time. • Development of a heuristic function to speed up the A* algorithm-based path search. • Manoeuvre-based feedback planning for closed-loop control of the micromanipulation. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for nonprehensile manipulation of parts on a circularly oscillating platform when the effective coefficient of dry friction between the part and the platform is being dynamically controlled. Theoretical and experimental analyses have been performed to validate the proposed method and to determine the control parameters that define the characteristics of the part's motion. A mathematical model of the manipulation process with dynamic dry friction control was developed and solved. The modeling showed that by changing the phase shift between the function for dynamic dry friction control and the function defining the circular motion of the platform, the part can be moved in any direction as the angle of displacement can be controlled in a full range from 0 to 2π. The nature of the trajectory and the mean displacement velocity of the part mainly depend on the width of the rectangular function for dynamic dry friction control. To verify the theoretical findings, an experimental setup was developed, and experiments of manipulation were carried out. The experimental results qualitatively confirmed the theoretical findings. The presented analysis enriches the classical theories of nonprehensile manipulation on oscillating platforms, and the presented findings are relevant for mechatronics, robotics, mechanics, electronics, medical, and other industries. [ABSTRACT FROM AUTHOR]

This paper presents a novel nonprehensile manipulation method that uses the vibration of a plate, where the two degrees of freedom of a part on the plate are controlled by only one actuator. First, a manipulator whose end effector is a flat plate is introduced. By employing an underactuated joint mechanism, the shape and orientation of the vibrational orbit of the plate vary according to frequency and offset angle of the sinusoidal displacement input to an actuator. Then, simulation analyses reveal that the manipulator can omnidirectionally induce translational velocity to the part on the plate. There exists an orthogonality between the effects of the frequency and offset angle on the velocity map of the part. Based on this characteristic, a visual feedback control for manipulating the part is designed. Finally, the proposed method is validated via experiments using a prototype manipulator. A target-trajectory tracking task and a four-way part-feeding task are demonstrated. [ABSTRACT FROM AUTHOR]