This paper proposes a fully distributed continuous region-reaching controller for multi-robot systems which can effectively eliminate the chattering issues and the negative effects caused by discontinuities. The adaptive control gain technique is employed to solve the distributed region-reaching control problem. By performing Lyapunov function-based stability analysis, it is shown that all the robots can move cohesively within the desired region under the proposed distributed control algorithm. In addition, collision avoidance and velocity matching within the moving region can be guaranteed under properly designed control gains. Simulation examples are given to verify the capabilities of the proposed control method.

In this paper, the kinematic workspace characteristics of a crab-like legged vehicle are investigated using a 2-D model. The alternative kinematic configurations and their corresponding workspace constraints are discussed, and the vehicle configuration of most interest identified. It is shown that, for constant vehicle body attitude, only two parameters affect the kinematic workspace, foot overlap and thigh length. Analytical methods for calculating the workspace characteristics are presented and, using these methods, the effects of the design geometry on the kinematic workspace are investigated.

The work aims to realize energy-efficient bipedal walking by employing the three-mass inverted pendulum model (3MIPM) and compare its energy performance with linear inverted pendulum model (LIPM). To do this, a general optimal index on center of mass (CoM) acceleration is first derived for energetic cost evaluation. After defining the equivalent zero moment point (ZMP) motion, an unconstrained optimization approach for CoM generation is extended for 3MIPM, which can track different ZMP references and address the height variation as well. To make use of the allowable ZMP movement, a constrained optimization method is also employed, contributing to lower energetic cost. Simulation and hardware experiments on a humanoid robot demonstrate that the 3MIPM could achieve higher energy efficiency.

Multi-level manipulators are those mechanisms in which two or more levels, that define the main chain of the manipulator, are joined in parallel to each other. Besides, each level is linked to the base in parallel by some limbs. Based on the idea of multi-level manipulators and using the concept of plain leg surfaces, the synthesis of partially decoupled manipulators with five degrees of freedom is presented. Among the different possibilities that exist to design the main chain of the manipulator, one is selected and the different manipulators that can be obtained from this option are analyzed. The concept of control distribution per level is presented and compared with the distribution of degrees of freedom per level. Finally, each of the proposed manipulators is studied and those which decouple the rotations are chosen.

Overconstrained manipulators in lower subspaces with unique motions can be created and analyzed. However, far too little attention has been paid to creating a generic method for overconstrained manipulators kinematic analysis. This study aimed to evaluate a generic methodology for kinematic analysis of overconstrained parallel manipulators with partial subspaces (OPM-PS) using decomposition to parallel manipulators (PMs) in lower subspaces. The theoretical dimensions of the method are depicted, and the use of partial subspace for overconstrained manipulators is portrayed. The methodology for the decomposition method is described and exemplified by designing and evaluating the method to two overconstrained manipulators with 5 degrees of freedom (DoF) and 3 DoF. The inverse kinematic analysis is detailed with position analysis and Jacobian along with the inverse velocity analysis. The workspace analysis for the manipulators using the methodology is elaborated with numerical results. The results of the study show that OPM-PS can be decomposed into PMs with lower subspace numbers. As imaginary joints are being utilized in the proposed methodology, it will create additional data to consider in the design process of the manipulators. Thus, it becomes more beneficial in design scenarios that include workspace as an objective.

The postural stability of bipedal robots is investigated in perspective of foot-rotation during locomotion. With foot already rotated, the biped is modeled as an underactuated kinematic structure. The stability of such biped robots is analyzed by introducing the concept of rotational stability. The rotational stability investigates whether a biped would lead to a flat-foot posture or the biped would topple over. The rotational stability is quantified as a ground reference point named “rotational stability index (RSI)” point. Conditions are established to achieve rotational stability during biped locomotion using the concept of the RSI point. The applicability of the RSI point is illustrated through experimentation for the landing stability analysis of the bipedal jumping gaits.

The traditional stability criteria such as zero-moment point (ZMP) [M. Vukobratovic and B. Borovac, “Zero-moment point – thirty five years of its life,” Int. J. Humanoid Robot. 1(1), 157–173 (2004)] and foot-rotation indicator (FRI) [A. Goswami, “Postural stability of biped robots and the foot-rotation indicator (FRI) point,” Int. J. Robot. Res. 18(6), 523–533 (1999)] are not applicable to analyze biped's postural stability when foot is already rotated. The RSI point is established as a stability criteria for planar bipedal locomotion in presence of foot rotation.

The automatic landmark identification is very important in autonomous robotnavigation tasks. In this paper, we use a monocular omnidirectional visionsystem to extract the image features and the conformal geometric algebra tocompute the projective invariants from such features. We show how these featurescan be used to compute projective and permutationp2-invariants from any kind ofomnidirectional vision system. Thep2-invariants represent scenesublandmarks, and a set of them characterize a landmark. The advantage of thisrepresentation is that the landmarks are more robust than the singlecross-ratio.

Fuzzy control has been widely applied in industrial controls and domestic electrical equipment. The automatic learning of fuzzy rules is a key technique in fuzzy control. In this paper, a software development system for fuzzy control is presented. Since the learning of fuzzy rules can be seen as finding the best classifications of fuzzy memberships of input-output variables in a fuzzy controller, it can also be seen as the combination optimization of input-output fuzzy memberships. Multi-layer feedforward network and genetic algorithms (GA) can be used for the automatic learning of fuzzy rules. The algorithms and their characteristics are described. The software development system has been successfully used for the design of some fuzzy controllers.

ELEVENTH INTERNATIONAL CONGRESS OF CYBERNETICS AND SYSTEMS

Dedicated to the memory of the late

Professor Frank H. George

Brunel University, Uxbridge (West London),

Middlesex, United Kingdom, 23–27 August 1999

In this study, a novel kinematic calibration method is proposed to improve the absolute positioning accuracy of 6R robot. This method can achieve indirect compensation of the 25 parameters of modified Denavit–Hartenberg (MDH). The procedures of the method are threefold. Firstly, the 25-parameter errors model of MDH is initially established. However, only the errors of 10 parameters can be directly compensated in the 25-parameter errors model, since the inverse kinematics algorithm has to meet Pieper criterion. Subsequently, a calibration method is proposed to improve accuracy of the absolute position, which uses the Newton–Raphson method to transform the 25-parameter errors into 10-parameter errors (namely T-10 parameter model). Finally, the errors corresponding to 10 parameters in the T-10 parameters model are identified through the least square method. The calibration performances of T-10 parameters model are comprehensively validated by experimentation on two ER6B-C60 robots and one RS010N robot. After kinematic calibration, the average absolute positioning accuracy of the three robots can be improved by about 90%. The results indicate that the proposed calibration method can achieve more precise absolute positioning accuracy and has a wider range of universality.

This paper investigates the contributions of each joint in perturbed balance by employing multiple balance strategies and exploring gain scheduling. Hybrid controllers are developed for sagittal standing in response to constant pushes, and a hypothesis is then investigated that postural feedback gains in standing balance should change with perturbation size via an optimization approach. Related research indicates the roles of each joint: the ankles apply torque to the ground, the hips and/or arms generate horizontal ground forces, and the knees and hips squat. To investigate it from an optimization point of view, this paper uses a horizontal push of a given size, direction, and location as a perturbation, and optimizes controllers for different push sizes, directions, and locations. It applies to the ankle, hip, squat, and arm swinging strategies in standing balance. By comparing the capability of handling disturbances and investigating the feedback gains of each strategy, this paper quantitatively analyzes the contributions of each joint to perturbed balance. We believe this work is also instructive to study the progressive behavioral changes as the model gets more and more complex.

Today, robots can be found helping humans with their daily tasks. Some tasks require the robot to visit a set of locations in the environment efficiently, like in the Traveling Salesman Problem. As indoor environments are maze-like areas, feasible paths connecting locations must be computed beforehand, so they can be combined during the scheduling, which can be impracticable for real-time applications. This work presents an on-line Route Scheduling supported by a Fast Path Planning Method able to adjust pre-built paths. Experiments were carried out with virtual and real robots to evaluate time and quality of tours.

It has become a common practice to use simulation to generate large databases of good grasps for grasp planning in robotics research. However, the existence of a generic simulation context that enables the generation of high quality grasps that can be used in several different contexts such as bin-picking or picking objects from a table, has to our knowledge not yet been discussed in the literature.

In this paper, we investigate how well the quality of grasps simulated in a commonly used “generic” context transfers to a specific context, both, in simulation and in the real world.

We generate a large database of grasp hypotheses for several objects and grippers, which we then evaluate in different dynamic simulation contexts e.g., free floating (no gravity, no obstacles), standing on a table and lying on a table.

We present a comparison on the intersection of the grasp outcome space across the different contexts and quantitatively show that to generate reliable grasp databases, it is important to use context specific simulation.

We furthermore evaluate how well a state of the art grasp database transfers from two simulated contexts to a real world context of picking an object from a table and discuss how to evaluate transferability into non-deterministic real world contexts.

This paper proposes a grasp planning for a multifingered hand-arm robot in the presence of obstacles. When the hand grasps an object, neither the hand nor the arm should collide with obstacles. However, it is very difficult to generate a collision-free grasp configuration of the hand-arm robot due to its abundant degrees of freedom of motion. To overcome this difficulty, we first decompose the hand-arm robot into the multifingered hand part and the arm part. We develop two methods of the grasp planning. In one method, a collision-free configuration of the hand part is planned first. Then, the arm configuration is planned so as to enable the hand configuration. In the other method, the collision-free configuration of the arm part is planned first and the multi-fingered hand configuration second. The best method is selected according to the space structure of the environment. Various heuristics are developed to improve the efficiency of the planning and implementation of the system. Simulation results are presented.

Continuum robots offer unique advantages in performing tasks within extremely confined environments due to their exceptional dexterity and adaptability. However, their soft materials and elastic structures inherently introduce nonlinearity and shape instability, especially when the robot encounters external contact forces. To address these challenges, this paper presents a comprehensive model and experimental study to estimate the shape deformation of a switchable rigid-continuum robot (SRC-Bot). The kinematic analysis is first conducted to specify the degrees of freedom (DoF) and basic motions of SRC-Bot, including motion of bending, rotating, and elongating. This analysis assumes that the curvature varies along the central axis and maps the relationship between joint space and driven space. Subsequently, an equivalence concept is proposed to unify the stiffness addressing each DoF, which is then utilized in the establishment of the dynamic model. According to the mechanical structural design, the deformed posture of SRC-Bot is discretized into five segments, corresponding to the distribution of the guiders. The dynamics model is then derived using Newton’s second law and Euler’s method to simulate the deformation under gravity, friction, and external forces. Additionally, the stiffness in three directions is quantified through an identification process to complete the theoretical model. Furthermore, a series of experiments are conducted and compared with simulated results to validate the response and deformed behavior of SRC-Bot. The comparative results demonstrate that the proposed model-based simulation accurately captures the deformable characteristics of the robot, encompassing both static deformed postures and dynamic time-domain responses induced by external and actuation forces.

Robots and inertial measurement units (IMUs) are typically calibrated independently. IMUs are placed in purpose-built, expensive automated test rigs. Robot poses are typically measured using highly accurate (and thus expensive) tracking systems. In this paper, we present a quick, easy, and inexpensive new approach to calibrate both simultaneously, simply by attaching the IMU anywhere on the robot’s end-effector and moving the robot continuously through space. Our approach provides a fast and inexpensive alternative to both robot and IMU calibration, without any external measurement systems. We accomplish this using continuous-time batch estimation, providing statistically optimal solutions. Under Gaussian assumptions, we show that this becomes a nonlinear least-squares problem and analyze the structure of the associated Jacobian. Our methods are validated both numerically and experimentally and compared to standard individual robot and IMU calibration methods.

An algorithm for the motion planning of the multifingered hand is proposed to generate finite displacements and changes in orientation of objects by considering sliding contacts as well as rolling contacts between the fingertip and the object at the contact point. Specifically, a nonlinear optimization problem is firstly formulated and solved to find the minimum joint velocity and the minimum contact force to impart a desired motion to the object at each time step. Then, the relative velocity at the contact point is found by calculating the velocity of the fingertip and the object at the contact point. Finally, time derivatives of the surface variables and the contact angle of the fingertip and the object at the current time step is computed using the Montana's contact equation to find the contact parameters of the fingertip and the object at the next time step. To show the validity of the proposed algorithm, a numerical example is illustrated by employing the robotic hand manipulating a sphere with three fingers each of which has four joints

Space manipulators are typically installed on spacecraft using an emergency separation device (ESD). In the event of a malfunction, the ESD ejects the manipulator from the spacecraft. However, due to the relative rotation of the manipulator’s joints during the ejection, the equivalent ejection mass varies depending on different attitudes. This paper focuses on studying manipulators equipped with separation slide rails and analyzes their ejection characteristics under different attitudes to determine the optimal manipulator attitude for ejection. Initially, the ejection dynamics model of the space manipulator is established using the Lagrangian method, based on the kinetic energy equation, kinematics equation, and the boundary condition between the manipulator and ESD. Afterward, the space dynamics model is transformed into the dynamic model of plane ejection state by recursion formula. From this model, the equivalent ejection mass and ejection velocity are obtained, and the joint angular variation during ejection is acquired by considering joint friction torque. Using the law of conservation of angular momentum, the ejection angular velocity is then calculated. Finally, this study selected a 7-DOF space manipulator as an example and adjusted the damping parameter B of the joint for more precise calculations by choosing the attitude with a relatively larger joint angular variation. The modified model was then tested for its applicability to other attitudes. After determining the value of B, the correctness of the algorithm was validated by MATLAB calculation, ADAMS simulation, and real object ejection test.