This paper presents recent results and applications of our planar kinematic synthesis of serial and parallel linkages to guide a rigid body, such that it does not violate normal direction and curvature constraints imposed by contact with objects in the environment. The paper briefly reviews the recently developed theory on transforming contact direction and curvature constraints into conditions on velocity and acceleration of certain points in the moving body to obtain synthesis equations which can, subsequently be solved to find the dimensions of a mechanical linkage. The main contribution of the paper is in demonstrating the applicability of the proposed theory to the kinematic synthesis of both open and closed-loop kinematic linkages. We provide preliminary results on the synthesis of kinematic chains based on novel task specifications that incorporate curvature constraints with a variety of applications, such as passive suspensions for small rovers, assistive technologies, as well as grasping.

An S-R-S (Spherical-Revolute-Spherical) redundant manipulator is similar to a human arm and is often used to perform dexterous tasks. To solve the inverse kinematics analytically, the arm-angle was usually used to parameterise the self-motion. However, the previous studies have had shortcomings; some methods cannot avoid algorithm singularity and some are unsuitable for configuration control because they use a temporary reference plane. In this paper, we propose a method of analytical inverse kinematics resolution based on dual arm-angle parameterisation. By making use of two orthogonal vectors to define two absolute reference planes, we obtain two arm angles that satisfy a specific condition. The algorithm singularity problem is avoided because there is always at least one arm angle to represent the redundancy. The dual arm angle method overcomes the shortcomings of traditional methods and retains the advantages of the arm angle. Another contribution of this paper is the derivation of the absolute reference attitude matrix, which is the key to the resolution of analytical inverse kinematics but has not been previously addressed. The simulation results for typical cases that include the algorithm singularity condition verified our method.

Two identical end-effectors are indispensable for self-relocation of a space manipulator, which is an effective way of extending its servicing capability. The prototype design is intimately linked to the requirements. The significant features and functionality of the end-effector and its grapple fixture are described, including the key analysis efforts. The characteristics of the end-effector and their suitability for self-relocation and payload handling were confirmed by testing, which used two prototype end-effectors, a semi-physical simulation testbed system with two, six degrees of freedom (DOF) industrial robot arms, and an air-bearing testbed system with a seven DOF manipulator. The results demonstrate that the end-effector satisfies the requirements and it can work well in a simulated space environment. With the compliance motion of the manipulator, the end-effector can perform soft capture and the manipulator can securely self-relocate and handle the payload.

Although the registration of a robot is crucial in order to identify its pose with respect to a tracking system, there is no reported solution to address this issue for a hybrid robot. Different from classical registration, the registration of a hybrid robot requires the need to solve an equation with three unknowns where two of these unknowns are coupled together. This property makes it difficult to obtain a closed-form solution. This paper is a first attempt to solve the registration of a hybrid robot. The Degradation-Kronecker (D-K) method is proposed as an optimal closed-form solution for the registration of a hybrid robot in this paper. Since closed-form methods generally suffer from limited accuracy, a purely nonlinear (PN) method is proposed to complement the D-K method. With simulation and experiment results, it has been found that both methods are robust. The PN method is more accurate but slower as compared to the D-K method. The fast computation property of the D-K method makes it appropriate to be applied in real-time circumstances, while the PN method is suitable to be applied where good accuracy is preferred.

Visual Homing is a navigation method based on comparing a stored image of a goal location to the current image to determine how to navigate to the goal location. It is theorized that insects such as ants and bees employ visual homing techniques to return to their nest or hive, and inspired by this, several researchers have developed elegant robot visual homing algorithms. Depth information, from visual scale, or other modality such as laser ranging, can improve the quality of homing. While insects are not well equipped for stereovision, stereovision is an effective robot sensor. We describe the challenges involved in using stereovision derived depth in visual homing and our proposed solutions. Our algorithm, Homing with Stereovision (HSV), utilizes a stereo camera mounted on a pan-tilt unit to build composite wide-field stereo images and estimate distance and orientation from the robot to the goal location. HSV is evaluated in a set of 200 indoor trials using two Pioneer 3-AT robots showing it effectively leverages stereo depth information when compared to a depth from scale approach.

A novel hybrid robotic arm with three fingers is proposed for assembly, operation and rescue. It is composed of an upper 3RPS-type parallel manipulator, a lower 3SPR-type parallel manipulator and three fingers. Its dynamics are studied and analyzed systematically. First, the kinematics formulae of the moving links at their mass centers in the hybrid robotic arm with three fingers are established. Second, the formulae for solving the inertial wrench of the moving links at their mass centers are derived. Third, a dynamics formula is established for solving the dynamic active/constrained forces of the hybrid robotic arm and the fingers. Finally, an analytic example is given for solving the kinematics and dynamics of the hybrid robotic arm with three fingers and the analytic solved solutions are verified by a simulation mechanism.

Force control is important in robotics research for safe operation in the interaction between a manipulator and a human operator. The elasticity center is a very important characteristic for controlling the force of a manipulator, because a force acting at the elasticity center results in a pure displacement of the end-effector in the same direction as the force. Similarly, a torque acting at the elasticity center results in a pure rotation of the end-effector in the same direction as the torque. A stiffness synthesis strategy is proposed for a desired elasticity center for three-degree-of-freedom (DOF) planar parallel mechanisms (PPM) consisting of three revolute-prismatic-revolute (3RPR) links. Based on stiffness analysis, the elasticity center is derived to have a diagonal stiffness matrix in an arbitrary configuration. The stiffness synthesis is defined to determine the configuration when the elasticity center and the diagonal matrix are given. The seven nonlinear system equations are solved based on one reference input. The existence and the solvability of the nonlinear system equations were analyzed using reduced Gröbner bases. A numerical example is presented to validate the method.

This work presents a method based on spherical trigonometry for computing all joint angles of the spherical metamorphic palm. The spherical palm is segmented into spherical triangles which are then solved and combined to fully solve the palm configuration. Further, singularity analysis is investigated with the analysis of each spherical triangle the palm is decomposed. Singularity-avoidance-based design criteria are then presented. Finally, point clouds are generated that represent the joint space of the palm as well as the workspace of the hand with the advantage of an articulated palm is shown.

The paper addresses the problem of speed adaptation of movements subject to environmental constraints. Our approach relies on a novel formulation of velocity profiles as an extension of dynamic movement primitives (DMP). The framework allows for compact representation of non-uniformly accelerated motion as well as simple modulation of the movement parameters. In the paper, we evaluate two model free methods by which optimal parameters can be obtained: iterative learning control (ILC) and policy search based reinforcement learning (RL). The applicability of each method is discussed and evaluated on two distinct cases, which are hard to model using standard techniques. The first deals with hard contacts with the environment while the second process involves liquid dynamics. We find ILC to be very efficient in cases where task parameters can be easily described with an error function. On the other hand, RL has stronger convergence properties and can therefore provide a solution in the general case.

Reliable assessment of terrain traversability using multi-sensory input is a key issue for driving automation, particularly when the domain is unstructured or semi-structured, as in natural environments. In this paper, LIDAR-stereo combination is proposed to detect traversable ground in outdoor applications. The system integrates two self-learning classifiers, one based on LIDAR data and one based on stereo data, to detect the broad class of drivable ground. Each single-sensor classifier features two main stages: an adaptive training stage and a classification stage. During the training stage, the classifier automatically learns to associate geometric appearance of 3D data with class labels. Then, it makes predictions based on past observations. The output obtained from the single-sensor classifiers are statistically combined in order to exploit their individual strengths and reach an overall better performance than could be achieved by using each of them separately. Experimental results, obtained with a test bed platform operating in rural environments, are presented to validate and assess the performance of this approach, showing its effectiveness and potential applicability to autonomous navigation in outdoor contexts.

It is well known that the use of multi-rate control techniques have improved the performance of many systems in general, and robotic systems, in particular. The main contribution of this paper is the generalization of the Reference Filtering control strategy from a dual-rate point of view, improving its inherent properties by overcoming the problem of sensor latency. In the paper, we discuss and analyze the improvements introduced by the novel dual-rate reference filtering control strategy in terms of convergence time, reachability and robustness. More specifically, we discuss the capability to solve positioning tasks, when hardware limitations are present with large sampling rates. In addition, a comparison is made between the single-rate and the proposed dual-rate control strategies to prove the advantages of the latter approach. A complete set-up has been prepared for validation, including a six degree of freedom (DOF) industrial manipulator, a smart camera and embedded hardware used as a high level controller.

This paper introduces a task-space dynamics formulation for fixed-base serial-link kinematically redundant manipulators and a motion/force controller based on it. The aim is to alleviate joint-space instability problems that have been observed with other motion/force controllers. The dynamics are represented in floating-base coordinates, wherein the end effector is regarded as the floating base. This representation gives rise to a momentum-conserving redundancy resolution scheme based on the reaction null-space (RNS) method used in past studies on free-floating and flexible-base space robots. A generalized inverse is obtained that is shown to satisfy the conditions for dynamic consistency in the sense of the operational space (OS) formulation, but may lead to the joint-space instabilities observed earlier. The proposed controller is based on the pseudoinverse of the coupling inertia matrix and ensures reactionless link motion that does not disturb the force balance at the end effector. The performance of the RNS motion/force controller is examined by comparison to that with an OS motion/force controller. It is shown that while the performance in task-space of both controllers is satisfactory, the joint-space performance of the proposed controller is superior.

We designed a quadruped robot with a one-degree-of-freedom (1-DOF)-pitch head, a 1-DOF-roll tail, and 14 active DOFs in total, which are controlled via a central pattern generator (CPG) based on a Hopf oscillator. Head and tail movements are coupled to the leg movements with fixed phase differences. Experiments show that tail swinging in roll can equilibrate feet–ground reaction forces (GRF), reducing yaw errors and enabling the robot to maintain its direction when trotting. Head swing in pitch has the potential to increase flight time and stride length of the swinging legs and increase the robot's forward velocity when running in bounds.