Publications

Abstract:

In this paper, we answer two interleaved questions. The first one is, having a redundant serial manipulator with a given cyclic task, how can we benefit simultaneously from both natural dynamics modification (NDM) and kinematic redundancy resolution to reduce the actuators’ torque? Here, the NDM is done by devising parallel nonlinear monoarticular compliances (MACs), which span one joint, and nonlinear biarticular compliances (BACs), which pass over two joints. We take advantage of kinematic redundancy to exploit the robot’s natural dynamics. The second question is howdo kinematic redundancy resolution and the NDM interact to minimize the cost? To answer these questions, we cast the problem of simultaneous modification and exploitation of natural dynamics into a constrained multiobjective optimization problem. We show that the set of optimal compliances has an analytical solution as a parametric function of joint trajectories. Accordingly, we study how the components of cost function affect the profile of optimal compliant elements. The proposed method is implemented on a simulated planar 3-DoF manipulator and a simulated nonplanar 4-DoF manipulator for three different tasks. The results shed light on how kinematic redundancy resolution influences efficiency of using MACs and BACs and, consequently, increases attainable gains from the NDM. Moreover, analysis of the results specifies the roles of mono- and BACs and especially explains the reason behind the particular importance of having BACs to reduce the actuation cost.

Abstract:

Deciding on the suitable values for robot’s morphological parameters is a complex task. Robot designers require a scientific tool to observe the influence of these parameters on the output behavior to help them decide about their implementation. Changing the structure is not an easy task even in the current available simulators. Moreover, using a dynamics engine from scratch is a complex task. In this paper, we introduce a simulator for quadruped robots using the ODE library to make the morphological study as simple as possible. It uniquely provides the opportunity to transfer morphological changes to the simulation instantly and to obtain performance characteristics such as transportation cost and robot’s average speed. An illustrative example highlights the outline of this simulator, its features and capabilities.

Abstract:

Distinguishing tip-toe walking from normal walking, in human locomotion patterns, becomes important in applications such as Autism disorder identification. In this paper, we propose a novel approach for tip-toe walking detection based on the walk’s Central Pattern Generator (CPG) parameters. In the proposed approach, the tip-toe walking is modeled by a CPG. Then, the motions of subjects are recorded and skeleton data are extracted using the first-generation Microsoft Kinect sensor. The CPG parameters of these motions are determined and compared to the given patterns to distinguish between tip-toe walking and normal walking. The accuracy of classification is promising while further data will improve the accuracy rate.

Abstract:

In this paper, a novel method towards approaching perfect tracking performance in periodic motions for robotic joints with serial elastic actuators, is proposed. The method is in an adaptive feed-forward scheme which has the ability to learn the required controlling signal, leading to reduced tracking error. Ordinary learning feed-forward methods do not have the capability of learning frequency of the motion; but here the method first learns the frequency of a motion adaptively and then basis functions are created based on the learned frequency. Finally the magnitudes of the injected basis functions are found and the tracking error will be lowered. In the simulations the effectiveness of the proposed method for a two DOF planar manipulator is verified. The results for two cases of tracking linear and circular periodic trajectories of end-effector prove satisfactory.

Abstract:

Obtaining the dynamical model of a system with high degrees of freedom (DOF) is an extremely tedious and error-prone task. On the other hand, designing suitable and energy efficient gaits for legged robots is a difficult procedure due to the large number of parameters that require tuning and calibration. In this paper we obtain the equations of motion for a quadruped robot with 12 DOF and active spine in sagittal plane. Later, we address the problem of gait implementation and optimization. We propose an evolutionary approach towards fining the optimal trajectory to minimize energy requirements. We present a nonlinear control methodology to achieve exponential stability of the gait. The results of simulations show that the method successfully reduced energy consumption of the system compared to traditional hand-tuned approaches.

Abstract:

We present a data-driven method for designing parallel compliance. Designing such compliance helps the system to improve energy efficiency, mainly by reducing negative work. The core idea is to design a controller first and then find springs working in parallel with each actuator such that force-displacement graph is lined up around displacement axis. By doing so, we simply shape the natural dynamics for performing the task efficiently. Maximum torque reduction for actuators is a byproduct of this design method. The method can be used in different cyclic robotic application, especially in legged locomotion systems. In this paper, we design a spinal compliance for a bounding quadruped robot in Webots. The results show that the power consumption and the maximum torque are reduced significantly.