An anticipative kinematic limitation avoidance algorithm for collaborative robots : two-dimensional case

This paper presents an anticipative robot kinematic limitation avoidance algorithm for collaborative robots. The main objective is to improve the performance and the intuitivity of physical human-robot interaction. Currently, in such interactions, the human user must focus on the task as well as on the robot configuration. Indeed, the user must pay a close attention to the robot in order to avoid limitations such as joint position limitations, singularities and collisions with the environment. The proposed anticipative algorithm aims at relieving the human user from having to deal with such limitations by automatically avoiding them while considering the user's intentions. The framework developed to manage several limitations occurring simultaneously in three-dimensional space is first presented. The algorithm is then presented and detailed for each individual limitation of a spatial RRR serial robot. Finally, experiments are performed in order to assess the performance of the algorithm

An anticipative kinematic limitation avoidance algorithm for collaborative robots : Three-dimensional case

This paper presents an anticipative robot kinematic limitation avoidance algorithm for collaborative robots. The main objective is to improve the performance and the intuitivity of physical human-robot interaction. Currently, in such interactions, the human user must focus on the task as well as on the robot configuration. Indeed, the user must pay a close attention to the robot in order to avoid limitations such as joint position limitations, singularities and collisions with the environment. The proposed anticipative algorithm aims at relieving the human user from having to deal with such limitations by automatically avoiding them while considering the user's intentions. The framework developed to manage several limitations occurring simultaneously in three-dimensional space is first presented. The algorithm is then presented and detailed for each individual limitation of a spatial RRR serial robot. Finally, experiments are performed in order to assess the performance of the algorithm

Assistive robotic device: evaluation of intelligent algorithms

Assistive robotic devices can be used to help people with upper body disabilities gaining more autonomy in their daily life. Although basic motions such as positioning and orienting an assistive robot gripper in space allow performance of many tasks, it might be time consuming and tedious to perform more complex tasks. To overcome these difficulties, improvements can be implemented at different levels, such as mechanical design, control interfaces and intelligent control algorithms. In order to guide the design of solutions, it is important to assess the impact and potential of different innovations. This paper thus presents the evaluation of three intelligent algorithms aiming to improve the performance of the JACO robotic arm (Kinova Robotics). The evaluated algorithms are 'preset position', 'fluidity filter' and 'drinking mode'. The algorithm evaluation was performed with 14 motorized wheelchair's users and showed a statistically significant improvement of the robot's performance.Comment: 4 page

Improving cable driven parallel robot accuracy through angular position sensors

Conventionally, a cable driven parallel mechanism (CDPM) pose is obtained through the forward kinematics from measurements of the cable lengths. However, this estimation method can be limiting for some applications requiring more precision. This paper proposes to use cable angle position sensors in addition to cable length measurements in order to improve the accuracy of such mechanisms. The robot pose is first obtained individually by the cable length measurements and the cable angle position measurements. A data fusion scheme combining these two types of measurements is then proposed in order to improve the CPDM accuracy. Finally, simulations and experiments are presented in order to assess the benefits of using cable angle position sensors on the CDPM

Modeling of physical human–robot interaction : admittance controllers applied to intelligent assist devices with large payload

Enhancement of human performance using an intelligent assist device is becoming more common. In order to achieve effective augmentation of human capacity, cooperation between human and robot must be safe and very intuitive. Ensuring such collaboration remains a challenge, especially when admittance control is used. This paper addresses the issues of transparency and human perception coming from vibration in admittance control schemes. Simulation results obtained with our suggested improved model using an admittance controller are presented, then four models using transfer functions are discussed in detail and evaluated as a means of simulating physical human–robot interaction using admittance control. The simulation and experimental results are then compared in order to assess the validity and limitations of the proposed models in the case of a four-degree-of-freedom intelligent assist device designed for large payload

A Questionnaire for the Evaluation of Physical Assistive Devices (QUEAD) : testing usability and acceptance in physical human-robot interaction

Many novel physical assistance devices are beginning to incorporate intelligent robotic systems and mechatronic components. In terms of a human-centered design it is crucial to assess the perceived subjective usability and acceptance of these systems. A questionnaire was thus designed to evaluate novel physically assisting devices in order to support developers in their design decisions as well as users during individualizing of their assistive devices. Two studies (m = 9, n2 = 21), using two different devices, were conducted to analyze objectivity, reliability, and validity. The results show an overall high internal consistency (Cronbach's α > 0.8), which indicates reliability and applicability of the QUEAD. Criterion validity was tested applying correlations with established objective measures for efficiency (time to task completion), effectivity (errors and collisions), and commitment (mean force). Construct validity was applied using a proposed model and correlations to verify convergence. The results show that the QUEAD is able to assess perceived usability and acceptance

Design and experimental validation of planar programmable inertia generators

This paper investigates the design and experimental development of planar programmable inertia generators. An inertia generator is a hand-held haptic device that has a programmable inertia. By moving internal masses in reaction to accelerations induced by the user, the effective inertia of the device is modified in order to render a prescribed inertia. In this paper, a one-degree-of-freedom device with one internal moving mass is first proposed. The corresponding dynamic model is developed and the rendering capabilities of the device are investigated. Then, a controller is designed to produce the appropriate motion of the internal mass in reaction to the acceleration induced by the user. A prototype is presented and experimental results are discussed. A mechanical architecture is then proposed for the design of a planar three-degree-of-freedom inertia generator. The corresponding dynamic model is derived, and it is shown that the generalized inertia matrix of the proposed mechanism is always of full rank. The rendering capabilities of the device are also investigated. Finally, simulation results obtained with the three-degree-of-freedom inertia generator are reported and discussed

Active stability observer using artificial neural network for intuitive physical human–robot interaction

Physical human-robot interaction may present an obstacle to transparency and operations’ intuitiveness. This barrier could occur due to the vibrations caused by a stiff environment interacting with the robotic mechanisms. In this regard, this paper aims to deal with the aforementioned issues while using an observer and an adaptive gain controller. The adaptation of the gain loop should be performed in all circumstances in order to maintain operators’ safety and operations’ intuitiveness. Hence, two approaches for detecting and then reducing vibrations will be introduced in this study as follows: 1) a statistical analysis of a sensor signal (force and velocity) and 2) a multilayer perceptron artificial neural network capable of compensating the first approach for ensuring vibrations identification in real time. Simulations and experimental results are then conducted and compared in order to evaluate the validity of the suggested approaches in minimizing vibrations

Preliminary development of an active planar upper limb rehabilitation robotic device

This paper presents the development of a low-cost active planar upper limb rehabilitation robotic device, which aims to help in the rehabilitation process of people living with movement disorders. Many people living with conditions such as cerebral palsy, stroke, spinal cord injury or muscular dystrophy experience upper limb impairments (muscle spasticity, lack of selective motor control, muscle weakness or tremors), and require physical and occupational therapy to maintain or gain motor performance. The proposed device is designed to be fixed on a table. Direct current (DC) motors control the two degrees of freedom (DOF) of the mechanism. The user interacts with the device using a handle. The device is designed so that the handle stays in the same orientation all the time. The device offers different levels of assistance to guide planar movements, going from a complete assistance, where the user is guided by the mechanism that performs predefined movements recorded by the therapist, to the addition of resistance during the movement, where the user moves the end effector without the help of the mechanism and the latter adds perturbations