Aliakbar Alamdari

Robotic Physical Exercise and System (ROPES): A Cable-Driven Robotic Rehabilitation System for Lower-Extremity Motor Therapy

Assisted motor therapies play a critical role in enhancing the functional musculoskeletal recovery and neurological rehabilitation. Our focus here is to assist the performance of repetitive motor-therapy of the human lower limbs ‐ in both the sagittal and frontal planes. Hence, in this paper, we develop a lightweight, reconfigurable hybrid (articulated-multibody and cable) based robotic rehabilitative device as a surrogate for a human physiotherapists and analyze feasibility and performance. A hybrid cable-actuated articulated multibody system is formed when multiple cables are attached from a ground-frame to various locations on the lower limbs. The combined system now features multiple holonomic cable-loop-closure constraints acting on a tree-structured multibody system. Hence the paper initially focuses on developing the Newton-Euler dynamic equilibrium equations of the cable-driven lower limbs to develop a symbolic analysis framework. The desired motion for the proposed rehabilitative exercise are prescribed based upon normative subjects motion patterns. Trajectory-tracking within this system is realized by a position-based impedance controller in task-space and a feedback-linearized PD controllers in joint-space. Careful coordination of the multiple cable-motors are now necessary in order to achieve the co-robotic control of the overall system, avoiding development of internal stresses and ensuring continued satisfaction of the unilateral cable-tension constraints throughout the workspace. This is now evaluated via a simulation case-study and development of a physical testbed is underway.

Design and Analysis of a Cable-Driven Articulated Rehabilitation System for Gait Training

Assisted motor therapies play a critical role in enhancing functional musculoskeletal recovery and neurological rehabilitation. Our long-term goal is to assist and automate the performance of repetitive motor-therapy of the human lower limbs. Hence, in this paper, we examine the viability of a light-weight and reconfigurable hybrid (articulated-multibody and cable) robotic system for assisting lower-extremity rehabilitation and analyze its performance. A hybrid cable-actuated articulated-multibody system is formed when multiple cables are attached from a ground-frame to various locations on an articulated-linkage-based orthosis. Our efforts initially focus on developing an analysis and simulation framework for the kinematics and dynamics of the cable-driven lower limb orthosis. A Monte Carlo approach is employed to select configuration parameters including cuff sizes, cuff locations, and the position of fixed winches. The desired motions for the rehabilitative exercises are prescribed based upon motion patterns from a normative subject cohort. We examine the viability of using two controllers—a joint-space feedback-linearized PD controller and a task-space force-control strategy—to realize trajectory- and path-tracking of the desired motions within a simulation environment. In particular, we examine performance in terms of (i) coordinated control of the redundant system; (ii) reducing internal stresses within the lower-extremity joints; and (iii) continued satisfaction of the unilateral cable-tension constraints throughout the workspace.

PARALLEL ARTICULATED-CABLE EXERCISE ROBOT (PACER): NOVEL HOME-BASED CABLE-DRIVEN PARALLEL PLATFORM ROBOT FOR UPPER LIMB NEURO-REHABILITATION

This paper examines the design, analysis and control of a novel hybrid articulated-cable parallel platform for upper limb rehabilitation in three dimensional space. The proposed lightweight, low-cost, modular reconfigurable parallel-architecture robotic device is comprised of five cables and a single linear actuator which connects a six degrees-of-freedom moving platform to a fixed base. This novel design provides an attractive architecture for implementation of a home-based rehabilitation device as an alternative to bulky and expensive serial robots. The manuscript first examines the kinematic analysis prior to developing the dynamic equations via the Newton-Euler formulation. Subsequently, different spatial motion trajectories are prescribed for rehabilitation of subjects with arm disabilities. A low-level trajectory tracking controller is developed to achieve the desired trajectory performance while ensuing that the unidirectional tensile forces in the cables are maintained. This is now evaluated via a simulation case-study and the development of a physical testbed is underway.

KINEMATIC MODELING, ANALYSIS AND CONTROL OF HIGHLY RECONFIGURABLE ARTICULATED WHEELED VEHICLES

The Articulated Wheeled Vehicle (AWV) paradigm examines a class of wheeled vehicles where the chassis is connected via articulated chains to a set of ground-contact wheels. Actively- or passively- controlled articulations can help alter wheel placement with respect to chassis during locomotion, endowing the vehicle with significant reconfigurability and redundancy. The ensuing ‘leg-wheeled’ systems exploit these capabilities to realize significant advantages (improved stability, obstacle surmounting capability, enhanced robustness) over both traditional wheeledand/or legged-systems in a range of uneven-terrain locomotion applications. In our previous work, we exploited the reconfiguration capabilities of a planar AWR to achieve internal shape regulation, secondary to a trajectory-following task. In this work, we extend these capabilities to the full 3D case – in order to utilize the full potential of kinematic- and actuationredundancy to enhance rough-terrain locomotion.

Active Reconfiguration for Performance Enhancement in Articulated Wheeled Vehicles

Leg-wheel architectures for locomotion systems offer many advantages, not the least of which is reconfigurability of wheel-axle with respect to the chassis. Thus, locomotion systems with multiple leg-wheels now permit enormous reconfigurability of the chassis frame with respect to the ground frame. We seek to systematically exploit this ability to reconfigure within this highly-redundant system to enhance contact kinematics i.e., reducing the slippage and improving traction forces at wheel-ground interfaces. In addition, reconfiguration can also be used to mitigate undesirable system-level effects (such as judder) and lead to greatly improved estimation for navigation. In this paper, we examine a systematic analytical approach to the modeling, analysis and reconfiguration of articulated leg-wheel systems, to enhance both traction as well as stability-margin, while navigating over rough-terrains. The derivations will also be specialized to a particular example of an ultra-mobile actively-articulated vehicle to illustrate the developed procedure.Copyright

QUANTITATIVE KINEMATIC PERFORMANCE COMPARISON OF RECONFIGURABLE LEG-WHEELED VEHICLES

The Leg-Wheel-Vehicle paradigm offers remarkable and diverse opportunities for creation of mobile and maneuverable terrestrial locomotion systems. However, this capability needs to be unlocked by careful design and control of the individual articulations, the sub-chains and the systems as a whole. Viewing leg-wheel vehicles as another class of parallelkinematic systems now facilitates the systematic application of the rich theory of Articulated Multi-body systems to quantitatively evaluate design and control of such systems.

Random matrix based uncertainty model for complex robotic systems

In this paper, we generalize our random matrix based (RM-based) uncertainty model for manipulator Jacobian matrix to the dynamic model of the robotic systems. Conventional random variable based (RV-based) schemes require a detailed knowledge of the system parameters variation and may be not able to fully characterize the uncertainties of the complex dynamic systems. However, the proposed RM-based approach provides a probabilistic framework for systematic characterization of the uncertainties in the complex systems with limited available information. Moreover, RM-based uncertainty model is an efficient mathematical tool that ensures the kinematic and dynamic consistency and takes into account the system complexity, configuration, structural inter-dependencies, etc. The application of the RM-based uncertainty model is investigated using an example of kinematically redundant planar parallel manipulator (3-(P)RRR). The simulation results are compared with those obtained through conventional RV-based approach and the effectiveness of the proposed method is discussed.

A Random Matrix Approach to Manipulator Jacobian

Traditional kinematic analysis of manipulators, built upon a deterministic articulated kinematic modeling often proves inadequate to capture uncertainties affecting the performance of the real robotic systems. While a probabilistic framework is necessary to characterize the system response variability, the random variable/vector based approaches are unable to effectively and efficiently characterize the system response uncertainties. Hence in this paper, we propose a random matrix formulation for the Jacobian matrix of a robotic system. It facilitates characterization of the uncertainty model using limited system information in addition to taking into account the structural inter-dependencies and kinematic complexity of the manipulator. The random Jacobian matrix is modeled such that it adopts a symmetric positive definite random perturbation matrix. The maximum entropy principle permits characterization of this perturbation matrix in the form of a Wishart distribution with specific parameters. Comparing to the random variable/vector based schemes, the benefits now include: incorporating the kinematic configuration and complexity in the probabilistic formulation, achieving the uncertainty model using limited system information (mean and dispersion parameter), and realizing a faster simulation process. A case study of a 6R serial manipulator (PUMA 560) is presented to highlight the critical aspects of the process. A Monte Carlo analysis is performed to capture the deviations of distal path from the desired trajectory and the statistical analysis on the realizations of the end effector position and orientation shows how the uncertainty propagates throughout the system.Copyright

ENHANCED FULL-STATE ESTIMATION AND DYNAMIC-MODEL-BASED PREDICTION FOR ROAD-VEHICLES

In this paper, we address the enhanced state estimation and prediction system for automobile applications by fusing relatively low-cost and noisy Inertial Navigation System (INS) sensing with Global Positioning System (GPS) measurements. An unscented Kalman filter is used to merge multi-rate measurements from GPS and INS sensors together with a highfidelity vehicle-dynamics model for state-predictions. The highfidelity motion model (including suspension-effects) for the vehicle motion trajectory on uneven terrain is captured by a 20state system of nonlinear differential equations. Computer simulation results illustrate the effectiveness of sensor-fusion (building upon the merger of an inexpensive INS sensing with GPS based measurements) to accurately estimate the full system-state. The relative ease of implementation, accuracy and predictive performance with low-cost sensing will facilitate its use in various electronic control and safety-systems, such as Electronic Stability Program, Anti-lock Brake Systems, and the Lateral Dynamic Stability Control.

Static balancing of highly reconfigurable articulated wheeled vehicles for power consumption reduction of actuators

This paper presents the static balancing of a highly reconfigurable articulated wheeled vehicles with multiple leg-wheel subsystem. Articulated wheeled vehicles are a class of mobile robots, which offer immense possibilities for enhanced locomotion-performance of autonomous mobile vehicles by virtue of the enormous reconfigurability within their articulated structure. However, changing the vehicle platform elevation could require considerable actuator power because of the payload. Hence, the main focus of this paper is to carefully evaluate various means for reducing or eliminating these static forces, principally due to the mass- and inertia-distribution within the system. It is noteworthy that although known apriori, such static forces often are significantly dependent upon the articulated-wheeled vehicle configuration. Hence, realising the static balancing for all possible configurations of vehicle imposes special set of conditions on the geometric, mass and inertial parameters. In this paper, elastic elements such as springs are used in conjunction with reconfigurable four-bar mechanism to achieve the static balancing. The essential principle is to realise that the total potential energy including the elastic potential energy stored in springs and gravitational potential energy becomes constant. Finally, we show that elimination of static torques due to gravity reduces the torque requirements and provides much more efficient design with significant reduction of the actuator sizes.