Building robotic prostheses requires a sensor-based interface designed to provide the robotic hand with the control required to perform hand gestures. Traditional Electromyography (EMG) based prosthetics and emerging alternatives often face limitations such as muscle-activation limitations, high cost, and complex calibrations. In this paper, we present a low-cost robotic system composed of a smart ankleband for intuitive, calibration-free control of a robotic hand, and a robotic prosthetic hand that executes actions corresponding to leg gestures. The ankleband integrates an Inertial Measurement Unit (IMU) sensor with a lightweight neural network to infer user-intended leg gestures from motion data. Our system represents a significant step towards higher adoption rates of robotic prostheses among arm amputees, as it enables one to operate a prosthetic hand using a low-cost, low-power, and calibration-free solution. To evaluate our work, we collected data from 10 subjects and tested our prototype ankleband with a robotic hand on an individual with an upper-limb amputation. Our results demonstrate that this system empowers users to perform daily tasks more efficiently, requiring few compensatory movements.

Many of our activities rely on tactile feedback perceived through mechanoreceptors in our skin. While visual and auditory devices provide immersive experiences, cutaneous feedback devices are typically limited in the range of sensations they provide and are hence usually used and tested on relatively simple synthetic surfaces. We present a device designed in a human-centered process, triggering the mechanoreceptors sensitive to pressure, low-frequency vibrations, and high-frequency vibrations, enabling one to experience touch of complex real-world surfaces. The device is based on a parallel manipulator and a pin-array, that operate simultaneously at 200Hz and emulate coarse and fine geometrical features, respectively. The decomposition into coarse and fine features, alongside the high operation frequency, enable simulation of virtual surfaces. This was corroborated via experiments on complex real-world surfaces via both a quantitative recognition test and a usability questionnaire. We believe that this design can be incorporated in numerous applications.

A central challenge in building robotic prostheses is the creation of a sensor-based system able to read physiological signals from the lower limb and instruct a robotic hand to perform various tasks. Existing systems typically perform discrete gestures such as pointing or grasping, by employing electromyography (EMG) or ultrasound (US) technologies to analyze muscle states. While estimating finger gestures has been done in the past by detecting prominent gestures, we are interested in detection, or inference, done in the context of fine motions that evolve over time. Examples include motions occurring when performing fine and dexterous tasks such as keyboard typing or piano playing. We consider this task as an important step towards higher adoption rates of robotic prostheses among arm amputees, as it has the potential to dramatically increase functionality in performing daily tasks. To this end, we present an end-to-end robotic system, which can successfully infer fine finger motions. This is achieved by modeling the hand as a robotic manipulator and using it as an intermediate representation to encode muscles' dynamics from a sequence of US images. We evaluated our method by collecting data from a group of subjects and demonstrating how it can be used to replay music played or text typed. To the best of our knowledge, this is the first study demonstrating these downstream tasks within an end-to-end system.

As orthopaedic implants become more sophisticated and complex, shaping the bone surface to match the implant becomes increasingly important. Accurate bone machining contributes to success of the implant and can potentially increase the implant's endurance and lifetime. Bone-mounted robots can eliminate intra-operative tracking errors during bone machining. However, registration errors still exist when aligning the pre-operative plan with the patient's anatomy because the plan is based on pre-operative images. Thus, a robotic system that is capable of executing both surface acquisition and bone machining in a single procedure and within the same coordinate system is preferable to the current state of the art. In this study we used a mini bone-attached robotic system (MBARS) with a haptic interface, to examine the accuracy of force-controlled surface acquisition of a femur model. The average distance error between acquired points and the surface model was less than 1 mm, which was further reduced by 5% with a compensation method which included curvature estimation of the reconstructed surface. An initial evaluation of in-situ bone machining based on these force-controlled scans yielded promising results.

Parallel mechanisms usually have several direct kinematic solutions that are attributed to different assembly modes (AMs) or postures. The present investigation deals with AM changing, and shows that beside the known cusp points, it is possible to change AM by moving on a path like a ramp, while encircling an alpha-curve in the joint space. For micromechanisms, where clearances at the mechanism joints are relatively large, AM changing may also occur when approaching a direct kinematic singularity.

We have developed a novel highly articulated robotic probe (HARP) that can thread through tightly packed volumes without disturbing the surrounding tissues and organs. We use cardiac surgery as the focal application of this work. As such, we have designed the HARP to enter the pericardial cavity through a subxiphoid port. The surgeon can effectively reach remote intrapericardial locations on the epicardium and deliver therapeutic interventions under direct control. Our device differs from others in that we use conventional actuation and still have great maneuverability. We have performed proof-of-concept clinical experiments to give us preliminary validation of the ideas presented here.

This paper introduces a new approach to identify singularities of planar parallel manipulators (PPMs). This method is based on Maxwell's reciprocal figure theory which establishes a duality between self stressed frameworks and reciprocal figures, which are abstract dual representations of frameworks. We use line geometry tools to introduce a new graphical construction called the mechanism's line of action graph (MLG). The MLG is introduced in order to implement Maxwell's reciprocal figure theory to mechanisms. We show that the configurations where the MLG has a connected reciprocal figure imply a singularity in the mechanism. This singularity analysis tool is also used to trace the singularity loci of the PPM. Finally, we provide detailed examples of the singularity analysis of two common PPMs; one consists of three limbs with a passive revolute joint, actuated prismatic joint and another passive revolute joint (3-RPR), the other consists of three limbs with three revolute joints, where only the first is actuated (3-RRR)

We address the problem of knee pathology assessment by using screw theory to describe the knee motion and by using the screw representation of the motion as an input to a machine learning classifier. The flexions of knees with different pathologies are tracked using an optical tracking system. The screw parameters which describe the transformation of the tibia with respect to the femur in each two successive observation are represented as the instantaneous screw axis of the motion given in its Plucker line coordinate, along with its corresponding pitch. The set of screw parameters associated with a particular knee with a given pathology is then identified and clustered in R6to form a "signature" of the motion for the given pathology. Bone model and two cadaver knees with different pathologies were tracked, and the resulting screws were used to train a classifier system. The system was then tested successfully with new, never trained before data. The classifier demonstrated a very high success rate in identifying the knee pathology

This paper presents the design, construction, and testing of a two-wheeled low-cost mobile robot platform that has high survivability when subjected to large impact forces and general rough handling. The design of the drive transmission system and integrated suspension system is developed, along with general equations of motion describing their dynamics. Analyses were conducted to insure stability of the various subsystems and optimize parameters for the desired vibration characteristics. Equations of motion were also developed to describe the rocking chassis phenomenon inherent to the two-wheeled design. A flywheel compensation scheme which helps eliminate the rocking chassis problem is also outlined. An impact analysis combining theory and empirical data was used to predict the survivability threshold. Finally, three series of experiments were conducted, with the first two followed by design improvements. In contrast to currently available commercial robots, our new design employs a flexible mechanical platform capable of absorbing energy during high load impacts. This design was substantiated during the final tests when the robot survived a third story drop without any damage.

This paper presents a novel compact design for a two degrees of freedom (DOF) joint mechanism. The joint is optimized for compactness, strength and range of motion which makes it ideal for constructing spatial or three-dimensional hyper redundant robots. We also identify and classify various prior joint designs that led to the development of this new concept. Finally, we present the joint forward kinematics, and force and torque calculations to verify the joint's range of motion and mechanical advantage.

In this work we introduce a new concept of a search and rescue robotic system that is composed of an elephant trunk-like robot mounted on a mobile base. This system is capable not only of inspecting areas reachable by the mobile base but also to inspect unreachable areas such as small cracks, and pipes, using the camera mounted on its elephant trunk robot. In the report we describe the mechanical structure of the elephant trunk robot, the kinematic analysis of the structure, the robot control, and its human interface systems.