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.

SLAM Benchmark plays a pivotal role in the field by providing a common ground for performance evaluation. In this paper, a novel methodology of simultaneous localization and mapping benchmark and map accuracy improvement (SLAMB&MAI) is introduced. It can objectively evaluate errors of localization and mapping, and further improve map accuracy by utilizing evaluation results as feedback. The proposed benchmark transforms all elements into a global frame and measures the errors between them. The comprehensiveness consists in the benchmark of both localization and mapping, and the objectivity consists in the consideration of the correlation between localization and mapping by the preservation of the original pose relations between all reference frames. The map accuracy improvement is realized by first obtaining the optimization that minimizes the errors between the estimated trajectory and ground truth trajectory and then applying it to the estimated map. The experimental results showed that the map accuracy can be improved by an average of 15%. The optimization that yields minimal localization errors is obtained by the proposed Centre Point Registration-Iterative Closest Point (CPR-ICP). This proposed Iterative Closest Point (ICP) variant pre-aligns two point clouds by their centroids and least square planes and then uses traditional ICP to minimize the error between them. The experimental results showed that CPR-ICP outperformed traditional ICP, especially in cases involving large-scale environments. To the extent of our knowledge, this is the first work that can not only objectively benchmark both localization and mapping but also revise the estimated map and increase its accuracy, which provides insights into the acquisition of ground truth map and robot navigation.

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.

This paper explores and experimentally compares the effectiveness of robot-stopping approaches based on the speed and separation monitoring for improving fluency in collaborative robotics. In the compared approaches, a supervisory controller checks the distance between the bounding volumes enclosing human operator and robot and prevents potential collisions by determining the robot’s stop time and triggering a stop trajectory if necessary. The methods are tested on a Franka Emika robot with 7 degrees of freedom, involving 27 volunteer participants, who are asked to walk along assigned paths to cyclically intrude the robot workspace, while the manipulator is working. The experimental results show that scaling online the dynamic safety zones is beneficial for improving fluency of human-robot collaboration, showing significant statistical differences with respect to alternative approaches.

While initially conceived for human motion augmentation, wearable robots have gradually evolved as technological aids in motion assistance and rehabilitation. There are increasing real-world applications in industrial and medical scenarios. Though efforts have been made on wearable robotic systems, e.g. robotic prostheses and exoskeletons, there are still several challenges in kinematics and actuation solutions, dynamic analysis and control of human-robot systems, neuro-control and human-robot interfaces; ergonomics and human-in-the-loop optimization. Meanwhile, real-world applications in industrial or medical scenarios are facing difficulties considering effectiveness.

This article proposes a control method for underactuated cartpole systems using semi-implicit cascaded proportional-derivative (PD) controller. The proposed controller is composed of two conventional PD controllers, which stabilizes the pole and the cart second-order dynamics respectively. The first PD controller is realized by transforming the pole dynamics into a virtual PD controller, with the coupling term exploited as the internal tracking target for the cart dynamics. Then, the second PD controller manipulates the cart dynamics to track that internal target. The solution to the internal tracking target relies on an equation set and features a semi-implicit process, which exploits the internal dynamics of the system. Besides, the design of second PD controller relies on the parameters of the first PD controller in a cascaded manner. A stability analysis approach based on Jacobian matrix is proposed and implemented for this fourth-order system. The proposed method is simple in design and intuitive to comprehend. The simulation results illustrate the superiority of proposed method compared with conventional double-loop PD controller in terms of convergence, with the theoretical conclusion of at least locally asymptotic stability.

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 November 2012, the eleventh Workshop on Distributed Autonomous Robotic Systems (DARS 2012) was held in Baltimore, Maryland on the campus of Johns Hopkins University. Previous DARS workshops were held in 1992, 1994, and 1996 in Riken, Wako, Japan; Karlsruhe, Germany (1998); Knoxville, Tennessee, USA (2000); Fukuoka, Japan (2002); Toulouse, France (2004); Minneapolis, Minnesota, USA (2006); Tsukuba, Ibaraki, Japan (2008); and Lausanne, Switzerland (2010).

In the original version of this paper the email of the corresponding author, Reza Mahboobi Esfanjani, was given incorrectly. The correct email is [email protected].

The publisher apologises for this error.

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.

This paper describes the development of a desktop robotic system that enables the plug-and-play function through the USB (universal serial bus) port of a personal computer (PC). Thus a new kind of desktop PC peripheral is invented that has programmable manipulability. The robotic system is realized on an internally distributed control structure that facilitates higher system reliability. A PID control algorithm is implemented on a prototype of the proposed system, to demonstrate the system's ability to implement feedback control. Experimental results show the performance and properties of the proposed system.

The work demonstrates a new approach to design of a level of intelligent control of robotic systems. The analytical model results in operational decisions. The structure of these decisions make them readily available to be implemented as an expert system. The approach is applied to a case study of mobile supervisory robots. The model presented here was motivated by manufacturing robotic systems and a type of autonomous robots that collect information at different sites for safety and other control purposes. The robot actions are directly affected by the obta~ned data. At each site the amount of available information (and thus the correctness of the robot decision) can be increased if the robot keeps collecting data at that site for a longer period of t~me. This means a delay in reacting and in reaching next site and accordingly, a decrease in the general amount of robot's information on the whole system.

The method of finding an economic amount of information collected by a robot at each site is based on the theory of controlled discrete event stochastic systems developed in our earlier works. This theory combines he basic concepts of discrete event control extended to stochastic systems with some aspects of information economics.

This article proposes an observer design for two important variables in the studies of single-leg hopping robot (SLHR), the apex height, and the vertical velocity of SLHR during its stance phase. At first, the Euler–Lagrange (EL) dynamics of SLHR are obtained and apex height is identified in the state-space representation of the EL dynamics. Apex height is the state variable that represents the robot body’s height at the top point, which keeps on changing as the robot functions. Vertical velocity is the velocity of the robot in the vertical direction. An observer design is presented in this article which will estimate these variables when required. The quality of the estimation is validated by the simulation results where the estimation error is zero which means the model output is correct and observer performance is good.

This paper presents the design and simulation of a Parallel Kinematic (PK) testbed for head impacts. The proposed design is presented as a novel head impact testbed using a parallel platform as main motion simulation mechanism. The testbed is used to give a motion to a head mannequin to impact against a steel plate. In addition, the platform in the testbed allows to modify the orientation of the head mannequin model to evaluate different types of impacts. The testbed has been modeled with software MS ADAMS® to evaluate its performance with a dynamic simulation and to characterize the testbed design during top and lateral impact events. Results show that PK testbed gives a significant force and acceleration to the head mannequin at the moment of the impact.

A new approach to flow measurement and visualisation in fluid dynamics based on a group of perceptive communicating capsules has been developed. Experiments were carried out with fluid-mobilised and stationary capsules deployed in a fluid flow test rig (raceway pond). Each capsule contains a microcontroller, battery, infra-red and visible LEDs and other electronics. Using optical communications, capsules can record encounters with one another. From the resulting interaction patterns, fluid flow speed and path-frequency measurements were obtained. Additionally, the capsules have shown the capacity for distributed sensing, and their streaklines provide a valuable means of external visualisation.