E. Ilhan Konukseven

Localization and control of an autonomous orchard vehicle

A new row localization system which uses a laser scanner is proposed.The proposed methodology offers a successful turning between rows of trees.The proposed methodology can run without using a GPS system.The algorithms can be adapted into the real autonomous orchard applications. In this paper we propose a novel model-based control method for an autonomous agricultural vehicle that operates in tree fruit orchards. The method improves path following performance by taking into account the vehicles motion model, including the effects of wheel sideslip, to calculate speed and steering commands. It also generates turn paths that improve visibility of the orchard rows, thus increasing the probability of a successful turn from one row into another, while respecting maximum steering rate limits. The method does not depend on GPS signals for either state estimation or path following, relying instead only on data from a planar laser scanner and wheel and steering encoders. This makes it suitable for real agricultural applications where acquisition cost is key to a farmers decision to invest in new technologies. We show the controllers stability using Lyapunov functions and demonstrate its feasibility in experiments conducted in an orchard-like nursery.

Passive haptic interface with mr-brakes for dental implant surgery

In this research a passive haptic interface is explored as a surgical aid for dental implant surgery. The placement of a dental implant is critical since positioning mistakes can lead to permanent damage in the nerves controlling the lips, long lasting numbness, and failure of the implant and the crown on it. Haptic feedback to the surgeon in real time can decrease dependence on the surgeons skill and experience for accurate implant positioning and increase the overall safety of the procedure. The developed device is a lightweight mechanism with weight compensation. Rotary magnetorheological (MR) brakes were custom designed for this application using the serpentine flux path concept. The resulting MR-brakes are 33% smaller in diameter than the only commercially available such brakes, yet produce 2.7 times more torque at 10.9 Nm. Another contribution of this research was a ferro-fluidic sealing technique which decreased the off-state torque. The control system implemented the passive force manipulability ellipsoid algorithm for force rendering of rigid wall-following tasks. Usability experiments were conducted to drill holes with haptic feedback. The maximum average positioning error was 2.88 mm along the x axis. The errors along the y and z axes were 1.9 mm and 1.16 mm, respectively. The results are on the same order of magnitude as other dental robotic systems. The innovative new MR-brake actuators, inherent safety of the system, and simplicity of control make this passive haptic interface a viable option for further exploration.

Optimal Posture Control for a 7 DOF Haptic Device Based on Power Minimization

The aim of this study is to put forward potential advantages of redundant haptic devices. The use of redundancy in haptic devices basically provides a larger workspace without changing kinematics parameters such as joint variables, joint offsets, effective link lengths and twist angles. Besides an increase in the workspace, redundant manipulators allow appropriate posture selection for different purposes, such as singularity avoidance, obstacle avoidance, inertia minimization, power minimization. These purposes can be considered either together or separately in order to determine optimal posture. The study in this paper is focused on optimal posture control of a 7 DOF haptic device based on power minimization. The designed haptic device has 4 DOF for positioning stage and 3 DOF for orientation stage.

Transparency improvement in haptic devices with a torque compensator using motor current

Transparency of a haptic interface can be improved by minimizing the effects of inertia and friction through the use of model based compensators. However, the performance with these algorithms is limited due to the estimation errors in the system model and in the velocity and acceleration from quantized encoder data. This paper contributes a new torque compensator based on motor current to improve transparency. The proposed method was tested experimentally in time and frequency domains by means of an excitation motor attached at the user side of the device. The excitation motor enabled evaluation of the algorithms with smooth trajectories and high frequencies, which cannot be generated by user hand. Experimental results showed that the algorithm significantly improves transparency and doubles the transparency bandwidth.

Optimum Design of 6R Passive Haptic Robotic Arm for Implant Surgery

The aim of this research was to design an optimum 6R passive haptic robotic arm (PHRA) to work in a limited workspace during dental implant surgery. Misplacement of an implant during dental surgery causes longer recuperation periods and functional disorders. In this study, a passive guidance robot arm was designed as a surgical aid tool for a dentist during the operation to reduce the surgical complications. Optimum design of a 6R robot is a complex issue since minimum energy has to be consumed while maximum workspace is to be achieved using optimized link lengths. The methodology used deals not only with link lengths of manipulator but also mass and inertia of the links along with the location of the tool path. Another feature of the methodology is to maximize haptic device transparency using an objective function that includes end-effector torques/forces with workspace limits taken as constraints. The objective function was obtained from dynamic equations and the constraints were defined using kinematic equations. The constrained nonlinear optimization problem was solved using Sequential Quadratic Programming (SQP) and Genetic Algorithms (GA). Main contribution of this paper is an optimization algorithm that considers spatial dynamics to reduce parasitic torques leading to an optimal 6R robot design. Details of the methodology, solutions, and performance of the optimization techniques are presented.

Dynamic modeling and parameter estimation for traction, rolling, and lateral wheel forces to enhance mobile robot trajectory tracking

Studying wheel and ground interaction during motion has the potential to increase the performance of localization, navigation, and trajectory tracking control of a mobile robot. In this paper, a differential mobile robot is modeled in a way that (traction, rolling, and lateral) wheel forces are included in the overall system dynamics. Lateral wheel forces are included in the mathematical model together with traction and rolling forces. A least square parameter estimation process is proposed to estimate the parameters of the wheel forces. In order to implement the proposed methodologies, an experimental setup is used. The setup contains a differentially driven mobile robot, a specially constructed test surface, and a camera system attached at the top of surface for obtaining ground truth. Models having one or more wheel forces are simulated to find the most realistic model. Simulation results are verified by experiments.

Kinematic model calibration of a 7-DOF capstan-driven haptic device for pose and force control accuracy improvement

The literature on kinematic calibration of industrial robots and haptic devices suggests that proper model calibration is indispensable for accurate pose estimation and precise force control. Despite the variety of studies in the literature, the effects of transmission errors on positioning accuracy or the enhancement of force control by kinematic calibration is not fully studied. In this article, an easy to implement kinematic calibration method is proposed for the systems having transmission errors. The presented method is assessed on a 7-DOF Phantom-like haptic device where transmission errors are inherently present due to the use of capstan drives. Simulation results on pose estimation accuracy and force control precision are backed up by experiments.

Stability and transparency improvement in haptic device employing both MR-brake and active actuator

An ideal haptic device should transmit a wide range of stable virtual model impedances (Z-width) with high transparency. Magneto-rheological fluid (MR) brakes are advantageous in haptic devices since they are passive actuators. However, they cannot provide high transparency and smooth interaction due to high viscous friction, residual torque, slow response, sticking and hysteresis effects. On the other hand, active actuators cannot simulate high virtual impedances stably, but provide high transparency with a closed loop control algorithm. In the proposed hybrid actuation a task divider control (TDC) algorithm was developed for torque sharing between two actuators to provide a large Z-width and improve both transparency and smoothness. The algorithm employs two parameters which were estimated experimentally and extended to entire achievable impedance range by artificial neural network (ANN) and curve fitting techniques. A 1-DOF device having an excitation motor at the user side and brushless DC motor and MR-brake in the haptic side was used in the experiments. The excitation motor is used to generate a white noise torque input to simulate a user for frequency domain transparency tests. Results of the proposed and conventional closed loop impedance control (CLIC) algorithms were compared. The proposed algorithm improves the transparency of MR-brake by eliminating its drawbacks and presents a larger Z-width than the active actuator alone.

Kinematic calibration of a 7 DoF hapic device

Precise positioning and precise force control requirement in haptic devices necessitate the kinematic calibration of the device. Since force control algorithms in haptic interfaces employ Jacobian matrix which includes kinematic model parameters, kinematic calibration is not only important for pose accuracy but also for force control. The deviation of kinematic parameters and joint transmission errors are main reasons disturbing the kinematic calibration of the manipulators. In haptic device design, capstan drives and parallelogram mechanisms are preferred to use for actuation. Hence, their transmission errors should be estimated in the kinematic calibration. This paper presents a simulation study including the estimation of the kinematic parameters and transmission errors due to the capstan drives and parallelogram mechanism for a 7 DOF haptic device. The closed chain kinematic model is preferred to use for easy implementation in the presented kinematic calibration study.

Optimal posture control algorithm to improve the stability of redundant haptic devices

Stability is indispensable to haptic interfaces for the simulation of a large variety of virtual environments. On a multi-degree of freedom (multi-DOF) haptic device, the passivity condition must be satisfied in both end-effector and joint space to achieve stable interaction. In this study, a conservative passivity condition is utilized for the stability such that guaranteeing the passivity at all joints is a sufficient condition for the passivity and then stability of the whole haptic system. An optimal posture control algorithm is developed to satisfy this passivity condition and maximize the stability performance of a redundant haptic device. The algorithm optimally adjusts the device postures, which are estimated by a Golden Section Search algorithm. The proposed control algorithm was experimentally implemented on a virtual sphere by using a 7-DOF redundant haptic device. Z-width stability metric was used to evaluate the performance of the proposed algorithm. The results show that the optimal posture control approach significantly improves the stability of the redundant haptic devices.