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.

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.

Tactile sensing and force reflection have been the subject of considerable research for tumor localization in soft-tissue palpation. The work presented in this paper investigates the relevance of force feedback (presented visually as well as directly) during tactile sensing (presented visually only) for tumor localization using an experimental setup close to one that could be applied for real robotics-assisted minimally invasive surgery. The setup is a teleoperated (master-slave) system facilitated with a state-of-the-art minimally invasive probe with a rigidly mounted tactile sensor at the tip and an externally mounted force sensor at the base of the probe. The objective is to capture the tactile information and measure the interaction forces between the probe and tissue during palpation and to explore how they can be integrated to improve the performance of tumor localization. To quantitatively explore the effect of force feedback on tactile sensing tumor localization, several experiments were conducted by human subjects to locate artificial tumors embedded in the ex vivo bovine livers. The results show that using tactile sensing in a force-controlled environment can realize, on average, 57 percent decrease in the maximum force and 55 percent decrease in the average force applied to tissue while increasing the tumor detection accuracy by up to 50 percent compared to the case of using tactile feedback alone. The results also show that while visual presentation of force feedback gives straightforward quantitative measures, improved performance of tactile sensing tumor localization is achieved at the expense of longer times for the user. Also, the quickness and intuitive data mapping of direct force feedback makes it more appealing to experienced users.

Robot teams require planning and adaptive capabilities in order to perform cooperative manipulation tasks in dynamic or unstructured environments. Since these capabilities are inherent to humans, it is suitable to consider human-robot team teleoperation for cooperative manipulation where a single human collaborates with the robot team. In this paper, we present a subtask-based control approach which enables a simultaneous execution of two subtasks by the robot team, interacting with the object: trajectory tracking and formation preservation. Control inputs for both subtasks are provided by the human operator. The commands are projected onto the spaces of subtasks using a command mapping strategy. Analogously, measured interacting forces are projected onto the space of feedback signals, provided to the human via wearable fingertip haptic devices through a feedback mapping strategy. Experimental results validate the proposed approach.