Machine vision for plant phenotyping is an emerging research area for producing high throughput in agriculture and crop science applications. Since 2D based approaches have their inherent limitations, 3D plant analysis is becoming state of the art for current phenotyping technologies. We present an automated system for analyzing plant growth in indoor conditions. A gantry robot system is used to perform scanning tasks in an automated manner throughout the lifetime of the plant. A 3D laser scanner mounted as the robot's payload captures the surface point cloud data of the plant from multiple views. The plant is monitored from the vegetative to reproductive stages in light/dark cycles inside a controllable growth chamber. An efficient 3D reconstruction algorithm is used, by which multiple scans are aligned together to obtain a 3D mesh of the plant, followed by surface area and volume computations. The whole system, including the programmable growth chamber, robot, scanner, data transfer, and analysis is fully automated in such a way that a naive user can, in theory, start the system with a mouse click and get back the growth analysis results at the end of the lifetime of the plant with no intermediate intervention. As evidence of its functionality, we show and analyze quantitative results of the rhythmic growth patterns of the dicot Arabidopsis thaliana (L.), and the monocot barley (Hordeum vulgare L.) plants under their diurnal light/dark cycles.

Implementation of haptic feedback in minimally invasive surgical teleoperator systems may lead to improved performance in many common surgical procedures; however, most of the currently available surgical teleoperators do not provide force feedback, mainly because of the associated stability issues. In this paper, we study the effect of a special type of force reflection algorithms, called projection-based force reflection (PBFR) algorithms, on the stability and performance of a dual-arm haptics-enabled teleoperator system for minimally-invasive surgical applications. In particular, the teleoperator system's performance is experimentally evaluated in three common tasks, which are knot tightening, pegboard transfer, and object manipulation, in the presence of negligible as well as non-negligible communication delays. The results obtained indicate that, in almost all cases, the PBFR algorithms demonstrate statistically significant improvement of performance in comparison with conventional direct force feedback.

In this paper, a robotic solution is proposed to deal with the challenges caused by lung motion during needle insertion. To accomplish this goal, a macro-micro robotic tool is designed to compensate for tissue motion using the macro part, while performing the needle insertion independently with the micro part. The main application of this work is for robotics-assisted lung tumor biopsy, where the combined motions of respiration and heartbeat may compromise success. An impedance-based controller keeps the macro reference coordinate in contact with the moving soft tissue using measurements from small pressure sensors mounted at the tip of the macro shaft. The micro part, mounted at the end of the macro robot, manipulates the needle in the harmonized reference coordinate system. Preoperative identification of ex vivo soft tissue is performed to estimate the dynamic behavior of the tissue. The controller is then synthesized based on the identified model. The effects of identification error and high frequency uncertainty are addressed in the control design. A prototype was built to evaluate the proposed approach using: 1) two Mitsubishi PA-10 robots, one for manipulating the macro part and the other for mimicking tissue motion, 2) one motorized linear stage to handle the micro part, and 3) a Phantom Omni haptic device for remote manipulation. Experimental results demonstrate the performance of the motion compensation system.

This work is aimed at developing a new minimally invasive approach to characterize tissue properties in real time during telerobotic palpation and to localize tissue abnormality while estimating its depth. This method relies on using a minimally invasive probe with a rigidly mounted tactile sensor at the tip to capture the force distribution map and the indentation depth by each tactile element and thereby generating a stiffness map for the palpated tissue. The hybrid impedance control technique is used for this approach to enable the operator to switch between position control and force control and thereby to autonomously obtain the required information from the remote tissue. The operator would then be able to localize tissue abnormality based on the force distribution map, the tissue stiffness map and the indentation depth which are visually presented to him/her in real time. This method also enables the operator to estimate the depth at which the tissue abnormality is located. Our results show that tactile sensing alone may be unable to detect tumors embedded deep inside tissue and may also not be a good alternative for palpation on uneven tissue surfaces.

This paper presents a new tactile-force integrated method to localize tumors minimally invasively using robotic assistance. This method relies on using a capacitive sensor at the tip of a Tactile Sensing Instrument (TSI) which can be inserted into a patient's body in a minimally invasive manner. In this work, the operator palpates tissue containing tumors in a minimally invasive surgical (MIS) training box, representing the patient's body, through a master-slave teleoperation system which consists of a 7 degrees-of-freedom (DOF) haptic interface, used as the master, and a Mitsubishi PA10-7C robot as the slave. Using the proposed method, the operator would be able to palpate the tissue consistently, observe the pressure distribution over the tissue by a color contour map on a screen and feel the tumor on his/her fingers through a grasping mechanism of the haptic interface as a result of higher stiffness of the tumor. The tissue used for the experiments was ex vivo bovine lung and seven participants were asked to locate artificial tumors embedded in the lungs. The results show an accuracy of 93% in tumor localization using the proposed method while the average force applied to the tissue was 3.42N and the force never exceeded 6N.

This paper focuses on the problem of incorporating haptics-enabled teleoperation in minimally invasive tumor localization. Since the stiffness of a tumor is higher than that of the surrounding tissue, it can be identified as a hard nodule when palpated. Using a Tactile Sensing Instrument (TSI) developed at CSTAR, the distributed pressure profiles along the contacting surface can be measured during remote tissue palpation. The tumor can be detected by using a visualization software that creates a color contour map based on the magnitude of the pressure over the palpated area. The accuracy of this method depends on the uniformity of the force applied to the tissue. A haptics-enabled teleoperation system provides the surgeon with the opportunity to feel the interaction force between the instrument and tissue during Minimally Invasive Surgery (MIS). The objective of this research was to assess the feasibility of combining force feedback with tactile feedback in order to increase the overall performance of tumor localization. The teleoperation system used in this work consists of a Mitsubishi PA10 robot as the slave that is remotely controlled (over a dedicated network) through a 7 Degree-Of-Freedom (DOF) haptic interface. A two-channel architecture, along with hybrid impedance control was utilized to form a bilateral teleoperation system in which the master is under force control and the slave is under position control. The experimental results confirm the effectiveness of using force feedback in robot-assisted tactile sensing for tumor detection.

In this paper, we present the design of a 7 degrees-of-freedom (DOF) Haptic Interface for applications in Minimally Invasive Surgery (MIS). The design of the interface is based on an existing dual-panthograph Haptic Wand and is capable of position and force reflection in three translational, three rotational DOF and grasping motion. The paper presents the implementation of a novel cable driven differential transmission to include the yaw and grasping force reflection to the interface. The kinematic and dynamic properties of the interface are characterized and presented. Experimental results demonstrate that the device is capable of high-force reflection with good transparency.