Machine Vision System for 3D Plant Phenotyping.

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.

The Role of Direct and Visual Force Feedback in Suturing Using a 7-DOF Dual-Arm Teleoperated System.

The lack of haptic feedback in robotics-assisted surgery can result in tissue damage or accidental tool-tissue hits. This paper focuses on exploring the effect of haptic feedback via direct force reflection and visual presentation of force magnitudes on performance during suturing in robotics-assisted minimally invasive surgery (RAMIS). For this purpose, a haptics-enabled dual-arm master-slave teleoperation system capable of measuring tool-tissue interaction forces in all seven Degrees-of-Freedom (DOFs) was used. Two suturing tasks, tissue puncturing and knot-tightening, were chosen to assess user skills when suturing on phantom tissue. Sixteen subjects participated in the trials and their performance was evaluated from various points of view: force consistency, number of accidental hits with tissue, amount of tissue damage, quality of the suture knot, and the time required to accomplish the task. According to the results, visual force feedback was not very useful during the tissue puncturing task as different users needed different amounts of force depending on the penetration of the needle into the tissue. Direct force feedback, however, was more useful for this task to apply less force and to minimize the amount of damage to the tissue. Statistical results also reveal that both visual and direct force feedback were required for effective knot tightening: direct force feedback could reduce the number of accidental hits with the tissue and also the amount of tissue damage, while visual force feedback could help to securely tighten the suture knots and maintain force consistency among different trials/users. These results provide evidence of the importance of 7-DOF force reflection when performing complex tasks in a RAMIS setting.

The role of visual and direct force feedback in robotics-assisted mitral valve annuloplasty.

BACKGROUND: The objective of this work was to determine the effect of both direct force feedback and visual force feedback on the amount of force applied to mitral valve tissue during ex vivo robotics-assisted mitral valve annuloplasty. METHODS: A force feedback-enabled master-slave surgical system was developed to provide both visual and direct force feedback during robotics-assisted cardiac surgery. This system measured the amount of force applied by novice and expert surgeons to cardiac tissue during ex vivo mitral valve annuloplasty repair. RESULTS: The addition of visual (2.16 ± 1.67), direct (1.62 ± 0.86), or both visual and direct force feedback (2.15 ± 1.08) resulted in lower mean maximum force applied to mitral valve tissue while suturing compared with no force feedback (3.34 ± 1.93 N; P < 0.05). CONCLUSIONS: To achieve better control of interaction forces on cardiac tissue during robotics-assisted mitral valve annuloplasty suturing, force feedback may be required.