This paper introduces a voice-controlled Human Machine Interface (HMI) tailored for an assistive robotic exoskeleton glove, aimed at assisting patients coping with Brachial Plexus Injuries (BPI) in regaining their lost grasping functionality. The development of this HMI draws upon clinical experimentation results, forming a foundation for its design. The paper delves into the challenges encountered while employing a prior voice-based HMI, which necessitated an internet connection for complex computations and exhibited limitations in effectively processing concise commands. To address these issues, an innovative voice-controlled HMI system is proposed, featuring fixed-word detection to replace the speech-to-text (STT) converter and the Neutral Language Processor (NLP) to reduce computational overhead. Furthermore, the new HMI replaces the previous text-independent speaker verification with a text-dependent, one-shot learning approach. This enhancement streamlines custom retraining, significantly improving speaker verification accuracy for concise commands. Experimental results substantiate the applicability of the proposed voice-controlled HMI for assisting individuals with BPI through specialized exoskeleton gloves.

This paper presents the development of an exoskeleton glove system for people who suffer from brachial plexus injuries, aiming to assist their lost grasping functionality. The robotic system consists of a portable glove system and an embedded controller. The glove system consists of Linear Series Elastic Actuators (LSEA), Rotary Series Elastic Actuators (RSEA), and optimized finger linkages to provide imitated human motion to each finger and a coupled motion of the hand. The design principles and optimization strategies were investigated to balance functionality, portability, and stability. The model-based force control strategy compensated with a backlash model and model-free force control strategy are presented and compared. Results show that our proposed model-free control method achieves the goal of accurate force control. Finally, experiments were conducted with the prototype of the developed integrated exoskeleton glove system. Results from 3 subjects with 150 trials show that our proposed exoskeleton glove system has the potential to be used as a rehabilitation device for patients.

This paper presents a systematical approach to develop a novel reduced complexity quadruped (RCQ) robot designed for serpentine robotic tail research purposes. The critical design requirements are determined based on careful dynamic analysis and synthesis results. Guided by formulated design requirements and principles, a robot prototype was designed and built. The robot has an overall weight of 5 Kg and the body size of a domestic cat. The existing electronic system allows a control frequency of up to 1 kHz and accepts both torque and position commands. These features guarantee that the platform could be used to explore the dynamic usages of robotic tails on legged locomotion. The preliminary tests show that the hardware can lift itself off the ground up to 112 mm (46.7% of its body height) and stay in the air for at least 0.3 seconds.

This paper presents the development and experimental evaluation of a portable haptic exoskeleton glove system designed for people who suffer from brachial plexus injuries to restore their lost grasping functionality. The proposed glove system involves force perception, linkage-driven finger mechanism, and personalized voice control to achieve various grasping functionality requirements. The fully integrated system provides our wearable device with lightweight, portable, and comfortable characterization for grasping objects used in daily activities. Rigid articulated linkages powered by Series Elastic Actuators (SEAs) with slip detection on the fingertips provide stable and robust grasp for multiple objects. The passive abduction-adduction motion of each finger is also considered to provide better grasping flexibility for the user. The continuous voice control with bio-authentication also provides a hands-free user interface. The experiments with different objects verify the functionalities and capabilities of the proposed exoskeleton glove system in grasping objects with various shapes and weights used in activities of daily living (ADLs).

This paper presents the design and development of a novel, low-profile, exoskeleton robotic glove aimed for people who suffer from brachial plexus injuries to restore their lost grasping functionality. The key idea of this new glove lies in its new finger mechanism that takes advantage of the rigid coupling hybrid mechanism (RCHM) concept. This mechanism concept couples the motions of the adjacent human finger links using rigid coupling mechanisms so that the overall mechanism motion (e.g., bending, extension, etc.) could be achieved using fewer actuators. The finger mechanism utilizes the single degree of freedom case of the RCHM that uses a rack-and-pinion mechanism as the rigid coupling mechanism. This special arrangement enables to design each finger mechanism of the glove as thin as possible while maintaining mechanical robustness simultaneously. Based on this novel finger mechanism, a two-finger low-profile robotic glove was developed. Remote center of motion mechanisms were used for the metacarpophalangeal (MCP) joints. Kinematic analysis and optimization-based kinematic synthesis were conducted to determine the design parameters of the new glove. Passive abduction/adduction joints were considered to improve the grasping flexibility. A proof-of-concept prototype was built and pinch grasping experiments of various objects were conducted. The results validated the mechanism and the mechanical design of the new robotic glove and demonstrated its functionalities and capabilities in grasping objects with various shapes and weights that are used in activities of daily living (ADLs).

This paper presents accurate grasp prediction algorithms that can be used for naturalistic, synergistic control of exoskeleton gloves with minimal user input. Recent research in exoskeleton systems has focused mainly on the development of novel soft or hard mechanical designs and actuation systems for rehabilitative and assistive applications. On the other hand, estimating user intent for intelligent grasp assistance is a problem that has remained largely unaddressed. As demonstrated by existing studies, the complex motions of human hand can be mapped to a latent space, thereby reducing perceived noise in individual joint angles as well as the number of variables upon which the prediction must be performed. To this extent, we present two latent space grasp prediction algorithms for intelligent exoskeleton glove control. The first presented algorithm is based on a linear regression to determine the slope and prediction horizon. The second algorithm is based on a Gaussian process trajectory matching where the trajectory of the grasping motion is probabilistically compared to existing data in order to form a prediction. Both algorithms were tested on published motion data collected from healthy subjects. In addition, the experimental validation of the algorithms was done using the RML glove (Robotics and Mechatronics Lab), which yielded similar prediction accuracy as compared to the simulation results. The proposed prediction algorithm can act as the backbone for a shifting authority controller that simultaneously amplifies the user's motion while guiding them toward their desired grasp. Preliminary work in this direction is also described in the paper, with directions for future research.

This paper presents a neural network based heterogeneous sensor fusion approach towards real-time traversability estimation of mobile robots using sensor data. Even though significant advances have been made for autonomous navigation in structured terrain conditions, obtaining reliable traversability estimates for tracked vehicle navigation in challenging terrain conditions is still an open research problem. In this regard, we propose a neural network architecture capable of fusing depth images along with roll and pitch measurements on board the robot to perform traversability estimation. The proposed architecture is trained in a variety of simulated structured and unstructured environments. As such, the proposed architecture is capable of extracting the relevant features from the sensor measurements in a data driven manner as compared to existing heuristic based approaches that fail to generalize for different environmental conditions. The reliability of the traversability estimates provided by the trained architecture was validated in indoor and outdoor conditions using real sensor data. In addition, the feasibility of using the traversability estimates in incremental path planning was also demonstrated through simulation. For both applications the proposed approach provided compelling results. Inferences based on the results of the experiments along with directions for future research are also outlined.

This paper presents the design, modeling, analysis, and experimental results of a bipedal robotic system that utilizes two interconnected single degree-of-freedom leg mechanisms to produce stable forward locomotion and steering. The legs are composed of double four-bar mechanism connected in series that maintain a parallel orientation of a flat foot, relative to the biped body, that is actuated via a Reuleaux triangle cam-follower system to produce a desirable foot trajectory. The mechanical design of the leg mechanism is presented followed by kinematic analysis of the cam-follower system to select the optimal foot trajectory and synthesize the mechanism dimensions and produce a desired step height and step length. The concept of leg sequencing is then presented to maintain a constant body height above the ground and a constant forward walking velocity. Experimental results using an integrated prototype indicate that the proposed biped robot is capable of maintaining quasi-static stability during locomotion, maintaining a constant robot body height, maintaining a constant body orientation, move forward with a constant maximum velocity of 27.4 cm/s, and steer.

This paper presents the foundations of a MATLAB framework for dynamic modeling and simulation of closed kinematic chain (CKC) mechanisms, with a particular focus on implementation with legged locomotive mechanisms. As such, the framework supports both floating-base and fixed-base systems. Through the use of singular perturbation theory, various CKC mechanisms can be modeled so that constraint errors asymptotically converge to zero, thus avoiding the numerical drift that plagues commonly used methods. A functional API and the relevant core commands necessary to construct a model are presented. Two robotic legs incorporating CKC mechanisms are utilized as case studies, and simulations of each leg performing a dynamic monopedal gait are illustrated.

This paper presents dynamic modeling and control of an articulated robotic tail to maneuver and stabilize a reduced degree-of-freedom (DOF) quadruped robot. Conventional legged robotic systems consist of leg mechanisms that provide simultaneous propulsion, maneuvering and stabilization. However, in nature animals have been observed to utilize their tails to assist the legs in multiple tasks. Similarly, by incorporating an articulated tail onboard a quadruped robot, dynamic tail motions can be used to aid maneuvering. Therefore, tail implementation can potentially lead to simplifications in design and control of the legged robot since the legs will be responsible for only propulsion tasks. In this paper, a robotic system design consisting of an articulated tail and quadruped robot system is presented. Dynamic models are derived to analyze an optimal tail mass and length ratio to enhance inertial adjustment applications and develop an outer loop controller to plan tail trajectories for desired maneuvering applications. Results of analytical optimization are corroborated with measured data from biological animals. To decouple the dynamics of the articulated tail mechanism an inner loop controller using feedback linearization maps the desired behavior to the actuator inputs. This approach is validated using hardware-in-the-loop experiments with tail prototype in conjunction with simulated quadruped platform. Results demonstrate the capabilities of the articulated tail in enabling precise left and right turning (maneuvering).

This paper presents the mechanical design and analysis of a novel leg mechanism that has only one active degree of freedom (DOF). The proposed mechanism is intended towards simplifying the mechanical and control complexity identified with the robotic legs implemented on quadrupedal platforms capable of dynamic locomotion. First, a survey of high-speed and reduced DOF legged robotic systems is presented to elucidate the design challenges and determine system requirements. Drawing from these requirements, a novel design of a six-bar leg mechanism with a single DOF is proposed. The novelty of the mechanism lies in its ability to trace a path that accommodates the execution of trot-gait by the quadrupedal platform realized by integrating the proposed leg. The kinematics of the mechanism is formulated and a multi-body model is used to perform a series of case studies on the sensitivity of the foot trajectory to the leg's dimensional parameters. Preliminary work on optimization of the foot trajectory is then performed. This research will ultimately assist the future design of quadrupedal robots to test the ability of spatial robotic tails in stabilizing and maneuvering the platform.

Efficient formulations for the dynamics of continuum robots are necessary to enable accurate modeling of the robot's shape during operation. Previous work in continuum robotics has focused on low-fidelity lumped parameter models, in which actuated segments are modeled as circular arcs, or computationally intensive high-fidelity distributed parameter models, in which continuum robots are modeled as a parameterized spatial curve. In this paper, a novel dynamic modeling methodology is studied that captures curvature variations along a segment using a finite set of kinematic variables. This dynamic model is implemented using the principle of virtual power (also called Kane's method) for a continuum robot. The model is derived to account for inertial, actuation, friction, elastic, and gravitational effects. The model is inherently adaptable for including any type of external force or moment, including dissipative effects and external loading. Three case studies are simulated on a cable-driven continuum robot structure to study the dynamic properties of the numerical model. Cross validation is performed in comparison to both experimental results and finite-element analysis.

This paper presents a new design for a docking interface that enables rigid, reversible and non-back-drivable coupling between robotic modules in a chain architecture. The distinctive merit of the proposed interface is exhibited in its ability to operate in three independent modes. In the drive mode, the motor torque is directed to drive the host module. In the neutral mode, the motor torque aligns the coupling elements prior to docking. In the clamp mode, the motor torque actuates the revolute joint resulting from this docking process, thus allowing one module to revolve relative to its neighbors in the formation. In this paper, an optimality analysis of the unique kinematic properties of the dual-rod slider-rocker (DRSR) mechanism which enables this tri-state operation is presented. This analysis is supplemented by simulations and experimental results that validate these optimal kinematics, as well as the rigidity and the three operation modes of the docking interface.

This video submission presents the experimental validation and testing of a novel hybrid mobile robot (HMR) system design using a complete physical prototype. The HMR consists of a combination of parallel and serially connected links resulting in a hybrid mechanism that consists of a locomotion platform and a manipulator arm for manipulation, both interchangeable functionally. The new design has the ability to interchangeably provide locomotion and manipulation capability, both simultaneously. This was accomplished by integrating the locomotion mechanism and the manipulator arm mechanism as one entity rather than two separate and attached mechanisms. The manipulator arm can be used as part of the locomotion platform and vice versa. The video demonstrates how this paradigm significantly enhances mobile robot functionality for locomotion and manipulation tasks.

This paper presents a new mobile robot design based on hybridization of the mobile platform and manipulator arm as one entity for robot locomotion as well as manipulation. The novel mechanical design is described in detail. To analyse the design, a virtual prototype tool was developed with ADAMS software for multi-body dynamic motion simulations of the complete robotic system. The simulation results were used to study the robot's mobility characteristics through animations of different possible tasks that require various locomotion and manipulation capabilities. The ability to visualize and validate various robot mobility cases and to study its functionality in the early design stages aided in optimizing the design and hence dramatically reduce physical prototype development time and cost. The design optimization process also involved proper components selection. Moreover, the simulations enabled us to define motor torque requirements and maximize end-effector payload capacity for different robot configurations.

In this paper, the design paradigm for a novel modular tele-robtoic system for MRI-guided neurosurgery is presented. Clinical requirements and design parameters are discussed. The overall infrastructure for MRI-guided intervention is addressed. The major focus is the application of the designed MR-compatible robotic system to MRI-guided brain biopsy. Candidate neurosurgical procedures enabled by this system include thermal ablation, radiofrequency ablation, deep brain stimulators DBS, and targeted drug delivery considering the modular structure of the slave manipulator. The mechanical design and preliminary MR-compatibility experiments are reported.