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Tendon-driven continuum robot kinematic models are frequently computationally expensive, inaccurate due to unmodeled effects, or both. In particular, unmodeled effects produce uncertainties that arise during the robot’s operation that lead to variability in the resulting geometry. We propose a novel solution to these issues through the development of a Gaussian mixture kinematic model. We train a mixture density network to output a Gaussian mixture model representation of the robot geometry given the current tendon displacements. This model computes a probability distribution that is more representative of the true distribution of geometries at a given configuration than a model that outputs a single geometry, while also reducing the computation time. We demonstrate uses of this model through both a trajectory optimization method that explicitly reasons about the workspace uncertainty to minimize the probability of collision and an inverse kinematics method that maximizes the likelihood of occupying a desired geometry.

This paper proposes a self-supervised model which enables a humanoid robot to learn to reach to visual targets. Only 400 training samples are used to learn a forward kinematic model of the six degree-of-freedom (DOF) arm. The forward model is represented compactly with just 150 hidden neurons and enables high accuracy reaching in real time. We provide an optimization process for the learning parameters and a careful analysis of reaching errors. An extension of the model is presented to address additional DOFs in the neck. The consistency of the model with physiological and psychological observations is elaborated.

An exoskeleton is a wearable robot with joints and links corresponding to those of the human body. With applications in rehabilitation medicine, virtual reality simulation, and teleoperation, exoskeletons offer benefits for both disabled and healthy populations. Analytical and experimental approaches were used to develop, integrate, and study a powered exoskeleton for the upper limb and its application as an assistive device. The kinematic and dynamic dataset of the upper limb during daily living activities was one among several factors guiding the development of an anthropomorphic, seven degree-of-freedom, powered arm exoskeleton. Additional design inputs include anatomical and physiological considerations, workspace analyses, and upper limb joint ranges of motion. Proximal placement of motors and distal placement of cable-pulley reductions were incorporated into the design, leading to low inertia, high-stiffness links, and back-drivable transmissions with zero backlash. The design enables full glenohumeral, elbow, and wrist joint functionality. Establishing the human-machine interface at the neural level was facilitated by the development of a Hill-based muscle model (myoprocessor) that enables intuitive interaction between the operator and the wearable robot. Potential applications of the exoskeleton as a wearable robot include (i) an assistive (orthotic) device for human power amplifications, (ii) a therapeutic and diagnostics device for physiotherapy, (iii) a haptic device in virtual reality simulation, and (iv) a master device for teleoperation.

The paper presents a novel method for solving the kinematics problems in real time for fast-moving robot manipulators, animation characters, and hexapod robots. The method uses certain properties of the kinematics map and is based on spatial decomposition, classification with fuzzy logic, and neural network representation of data that are performed during an off-line process. As a result of the preprocessing, the online time for computing the kinematics is extremely small making it possible to perform real-time operations. Examples are provided to demonstrate the performance of the method.

A novel metamorphic anthropomorphic hand is for the first time introduced in this paper. This robotic hand has a reconfigurable palm that generates changeable topology and augments dexterity and versatility of the hand. Structure design of the robotic hand is presented and based on mechanism decomposition kinematics of the metamorphic anthropomorphic hand is characterized with closed-form solutions leading to the workspace investigation of the robotic hand. With characteristic matrix equation, twisting motion of the metamorphic robotic hand is investigated to reveal both dexterity and manipulability of the metamorphic hand. Through a prototype, grasping and prehension of the robotic hand are tested to illustrate characteristics of the new metamorphic anthropomorphic hand.

Legged robots rely on an accurate calibration of the system’s kinematics for reliable motion tracking of dynamic gaits and for precise foot placement when moving in rough terrain. In our automatic foot-eye calibration approach, a monocular camera is attached to the robot and observes the robot’s moving feet, which are equipped with Augmented Reality (AR) markers. The measurements are used to formulate a non-linear least squares problem over a fixed time window in order to estimate the 33 unknown parameters. This is effciently solved with the Levenberg-Marquardt algorithm and we get estimates for both the kinematic and the camera parameters. The approach is successfully evaluated on a real quadruped robot.

In this paper, we design a 3DOF climbing robot in the software SolidWorks, and build the positive kinematics equation by the DH method; we use the csape function planted in the MATLAB to compute the curve of the robot’s gait which is appropriate. Then, we import the simplified model to the ADAMS software. After exerting constraints and drives, we get the simulation of the robot’s motion. We also define some markers to measure the angle, which can help us get the inverse kinematic solutions. Through fitting the curve in the MATLAB and the simulation in the ADAMS, we get the comfortable trajectory of the robot and the inverse kinematic solutions of the robot.

Underactuated mechanism, as one of the hot spots in the field of robot mechanism, has a number of difficulties to be solved, such as unsettling movement tracks and uneven internal force of the multi-unit mechanism. In this paper, a novel space multi-unit underactuated mechanism is analyzed. Firstly, the kinematics of the mechanism is calculated. Then the mechanical analysis of the mechanism is analyzed, and the strength and deformation of the mechanical are calculated. Finally, the modal analysis is analyzed, and the stability of the mechanism is verified. The analysis results show that the space multi-unit underactuated mechanism can achieve the desired trajectory, and the strength and modal of each unit can meet the design requirements, which provide a theoretical basis for the development of the experimental prototype.

This paper presents the leg design of the HexaQuaBip robot, namely a bio-inspired polymorphic robot intended to be able to reconfigure its morphology in most of hexapod, quadruped and biped animals. We first review segmentation and kinematics of their legs and define the HQB's reconfigurable kinematics. The resulting leg model is four-segmented and entails seven degrees of freedom. Then, we analyze the diversity in limb proportions of animal legs and determine where to put sliding joints on HQB's legs. We found that one sliding joint on the third segment of each leg is enough to approximate limb proportions of most of hexapod, quadruped and biped animals. Finally, we conclude by considering hardware implementations of the complex theoretically-designed HQB's morphology.

The paper develops a method for analyzing and improving by control obstacle clearance capacities of articulated multi-wheeled rovers. On uneven ground surface, load and traction force distributions through the wheel/ground contact system are highly coupled. They are both conditioned by the global equilibrium of the mechanical system and the contact stability constraints. The optimal traction force distribution problem is formulated here as a convex optimization problem using Linear Matrix Inequalities (LMls). Velocity and force transmissions in articulated multi-wheeled mobile robots are introduced under a generic form decomposed in task, joint and contact levels. Simulation results show that the traction distribution forces which is so determined lead to a significant increase in obstacle clearance capacities compared to a simple velocity control technique.

The rough terrain mobile robot "RT-Mover", which is a leg-wheel-type robot built of very simple mechanism, can move on continuous rough terrain.¹ However, in a real environment there is also discontinuous rough terrain, where it can not get about. The step-up gait for an upward step has been studied to walk on discontinuous rough terrain. In this paper, a flow of the step-up gait is introduced. After that, kinematics to climb up a step is discussed in detail, and is evaluated through simulation and experiment.

This paper presents the construction of individual dynamic models of human lower limbs using kinematics from Clinical Gait Analysis(CGA) data and Body Segment Inertia Parameters(BSIP) from predictive equations. It’s used human lower limbs BSIP from predictive equations and human kinematics from CGA data, to get individual BSIP and kinematic data. The the human dynamic model is built in a dynamic simulation software environment, to create human body dynamic models, and the CGA kinematic data is used as input to study model dynamics and control strategies. This approach would allow the testing and simulation of complex dynamic models without going through the tedious and error prone process of manually calculating equations of motion.

It’s shown the use of the strategy presented to collect the data to be used in the simulation of a teen age boy or girl to be used latter in the simulation of a lower limb exoskeleton.

This paper presents the unconventional five-legged walking robot. The machine has radial symmetry, and its legs are equally distributed around the body. This results in omnidirectionality – the ability to change the walking direction without the need of rotation. The main objective of the presented research was to test the concept of a five-legged, radially symmetric robot and to demonstrate the motion agility of such an unique configuration.

This article is devoted to the kinematics of the multilink body of a multilegged walking robot. The number of degrees of freedom for multilink body is obtained and the reverse kinematic problem is solved. The control algorithm for mosaic robot body is provided. All algorithms have been verified via multibody computer simulation.