IROS 2022 论文列表

As the aging of society continues to accelerate, the number of elderly patients is increasing, as is the demand for manpower to care for them. In particular, there is an urgent need for bedridden patient care. However, limitations in the supply of human resources have caused an increase in the burden for care. In particular, nursing personnel often experience inconvenience and difficulties owing to the great deal of effort required to transfer a patient from bed to wheelchair, or vice versa. The most difficult process during the patient transfer is inserting the sling under the patient. Aiming to solve this problem, a mechanical Growing Sling was devised. The proposed sling adapts a growing mechanism comprising a low-friction fabric and steel shafts, and the sling is inserted under the patient by towing the steel shafts with cables connected to a motor. For the comfort and safety of the sling insertion, the required towing force was analyzed to find the minimum diameter of the shaft. The results from experimental evaluations using the proposed sling verified that it can be inserted under the patient without moving the patient, and with an acceptable level of pressure being applied to the patient.

Undulatory fin motions in fish-like robots are typically created using intricate arrays of servo motors. Motor arrays offer impressive versatility in terms of kinematics, but their complexity leads to constraints on size, hydrodynamic force production, and power consumption, particularly when studying propulsive performance at high-frequencies. Here we present an alternative design that uses a single motor and a tunable rotary cam-train system to achieve a spectrum of fin motions running from oscillation (wavenumber < 1) to undulation (wavenumber > 1). Our platform enables thrust, lift, power, and wake measurements at prescribed pitch amplitudes, frequencies, and wavenumbers. We demonstrated the platform's oscillating and undulating capabilities via force and wake measurements in a water tank. Studies of fin wavenumber offer design insights for fish-like underwater robots, particularly those with stingray-inspired designs.

This paper presents a cooperative driving testbed based on vehicle-to-vehicle (V2V) communication, which can be used for research in intelligent transportation systems, such as collision avoidance in mixed traffic of both human-driven vehicles and autonomous vehicles. To achieve the goal, an intelligent copilot is developed. The copilot can share the data regarding vehicle status, intention, etc, with other nearby vehicles through V2V communication. Several case studies are conducted to validate the proposed testbed and evaluate the performances of cooperative driving. When dangerous situations occur, the copilot solves the collision avoidance problem using Mixed Integer Programming (MIP), which either provides control commands to the autonomous vehicle, or advises the human driver to take action. Experimental results show that the safety and stability of the involved vehicles have been significantly enhanced. This cooperative driving testbed can be used by researchers to develop and test cooperative driving algorithms before they are deployed in real vehicles.

This paper presents the design and development of a novel, low-profile, exoskeleton robotic glove aimed for people who suffer from brachial plexus injuries to restore their lost grasping functionality. The key idea of this new glove lies in its new finger mechanism that takes advantage of the rigid coupling hybrid mechanism (RCHM) concept. This mechanism concept couples the motions of the adjacent human finger links using rigid coupling mechanisms so that the overall mechanism motion (e.g., bending, extension, etc.) could be achieved using fewer actuators. The finger mechanism utilizes the single degree of freedom case of the RCHM that uses a rack-and-pinion mechanism as the rigid coupling mechanism. This special arrangement enables to design each finger mechanism of the glove as thin as possible while maintaining mechanical robustness simultaneously. Based on this novel finger mechanism, a two-finger low-profile robotic glove was developed. Remote center of motion mechanisms were used for the metacarpophalangeal (MCP) joints. Kinematic analysis and optimization-based kinematic synthesis were conducted to determine the design parameters of the new glove. Passive abduction/adduction joints were considered to improve the grasping flexibility. A proof-of-concept prototype was built and pinch grasping experiments of various objects were conducted. The results validated the mechanism and the mechanical design of the new robotic glove and demonstrated its functionalities and capabilities in grasping objects with various shapes and weights that are used in activities of daily living (ADLs).

A surface microstructure that mimics the surface of a gecko's foot can exert a large gripping force with a small contact force. If such a structure is applied to the fingertips of a two-fingered parallel gripper, stable grasping can be achieved independent of the wetting and frictional state of the contact surface. However, the adhesive force of the microstructure is large while releasing the object, which hinders the release of the object. In this study, we developed a release method using a conveyor mechanism that easily peels off in the direction of rotation with a focus on the characteristics of the micro-protrusion structure. This mechanism is driven in conjunction with the gripper's grasping and releasing motions. Our experiments confirmed that the gripper can stably release the object using the proposed mechanism. The proposal in this paper is a mechanism that dynamically changes the adhesive force on a fingertip by mechanically switching the surface state in accordance with the gripper's grasping and releasing states. This idea can be applied to not only surface microstructure such as gecko-inspired surfaces but also adhesive surfaces such as adhesive tape, and provides novel knowledge in the field of robotics as a method of mechanically changing the fingertip adhesive force.

This paper presents a new 6 DOF soft robotic manipulator intended for colorectal surgery. The manipulator, based on a novel design that employs an inextensible tube to limit axial extension, is shown to maximize the force exerted at its tip and the bending angle, the latter being measured with a soft sensing skin. Manufacturing of the prototype is achieved with a lost-wax silicone-casting technique. The kinematic model of the manipulator, its workspace, and its manipulability are discussed. The prototype is evaluated with extensive experiments, including pressure-deflection measurement with and without tip load, and lateral force measurements with and without the soft sensing skin to assess hysteresis. The experimental results indicate that the prototype fulfils the key design requirements for colorectal surgery: (i) it can generate sufficient force to perform a range of laparoscopic tasks; (ii) the workspace is commensurate with the dimensions of the large intestine; (iii) the soft sensing skin only results in a marginal reduction of the maximum tip rotation within the range of pressures and external loads relevant for the chosen application.

This paper reports a tensegrity manipulator driven by 40 pneumatic cylinders without mechanical springs. In general, tensegrity robots use mechanical springs to achieve a stable/curved tensegrity structure, and this is true even when a component extends/retracts with an actuator. The stiffness of the mechanical spring should be high to increase the stiffness of the entire structure and improve the control response, but low to deform the structure. This fact means that the introduction of mechanical springs causes serious trade-offs in its design and control. In this study, we use pneumatic actuators not only for active deformation but also for passive. In this paper, we introduce the design and control system and then show the difference in response characteristics between the case with and without a spring, demonstrating the importance of the approach without a mechanical spring.

A robot designed to coexist and work with humans in the same workspace should be able to work at the same speed as humans and have safe contact with humans and with the environment. However, when a robot arm has been given flexibility through mechanisms and controls for the purpose of coexistence, it is difficult for it to perform tasks at the speed and accuracy desired by humans if it is moved simply by using conventional position-based controls. With such an arm, we consider that the use of learning-based control is necessary to achieve both safety and speed. Therefore, we prototyped a low-inertia, high-backdrivability arm as a platform for studying learning-based control and tested two types of learning-based control. This paper describes our design process, in which hardware suitable for learning-based control was developed according to the requirements of the specific task. It also presents the results of our evaluation experiments, in which tasks involving quick movements and motion requiring physical contact with an object were performed using learning-based control.

Marine autonomous vehicles deployed to conduct marine geophysical surveys are becoming an increasingly used asset in the commercial, academic, and defense industries. However, the ability to collect high-quality data from applicable sensors is directly related to the robustness of vehicle motion caused by environmental disturbances. In this paper we designed and integrated a new path following controller on an autonomous surface vehicle (ASV) that minimizes the linear and angular accelerations on the sensor's local frame. Simulation and experimental results verify reduction of vehicle motion, improvement in path following, and improvement in preliminary sonar data quality compared to that of the existing proportional-yaw path following controller.

This paper presents the development and experimental evaluation of a portable haptic exoskeleton glove system designed for people who suffer from brachial plexus injuries to restore their lost grasping functionality. The proposed glove system involves force perception, linkage-driven finger mechanism, and personalized voice control to achieve various grasping functionality requirements. The fully integrated system provides our wearable device with lightweight, portable, and comfortable characterization for grasping objects used in daily activities. Rigid articulated linkages powered by Series Elastic Actuators (SEAs) with slip detection on the fingertips provide stable and robust grasp for multiple objects. The passive abduction-adduction motion of each finger is also considered to provide better grasping flexibility for the user. The continuous voice control with bio-authentication also provides a hands-free user interface. The experiments with different objects verify the functionalities and capabilities of the proposed exoskeleton glove system in grasping objects with various shapes and weights used in activities of daily living (ADLs).

Robotic automation is steadily growing in different industries around the world. However, in some industries, such as garment manufacturing, most tasks are still predominantly manual, due to the flexible nature of clothes. Garment and clothes are easily deformed when some force is applied, so it is difficult for robots to handle them while predicting their deformation. Our general research goal is to realize flexible cloth handling using robots to automate different tasks in the garment manufacturing industry. We draw inspiration from the actions that humans perform when manipulating clothes and emulate them using a robotic system. In this paper, we developed a robot hand with a camera at the finger, to obtain local information of the contact between the garment and the robot hand, in order to achieve garment handling tasks. Specifically, we focus on the pinch and slide motion that humans perform when straightening a piece of cloth. We selected a specific task to be automated and proposed three manipulation strategies to approach the garment using visual information from the finger camera that enabled the system to perform the task consistently. We carried out two validation experiments to demonstrate the effectiveness of the proposed methods, and an application experiment where we evaluate their applicability to a specific task.

For Lifelong SLAM, one has to deal with temporary localization failures, e.g., induced by kidnapping. We achieve this by starting a new map and merging it with the previous map as soon as relocalization succeeds. Since relocalization methods are fallible, it can happen that such a merge is invalid, e.g., due to perceptual aliasing. To address this issue, we propose methods to detect and undo invalid merges. These methods compare incoming scans with scans that were previously merged into the current map and consider how well they agree with each other. Evaluation of our methods takes place using a dataset that consists of multiple flat and office environments, as well as the public MIT Stata Center dataset. We show that methods based on a change detection algorithm and on comparison of gridmaps perform well in both environments and can be run in real-time with a reasonable computational cost.

While deep neural networks (DNNs) achieve impressive performance on environment perception tasks, their sensitivity to adversarial perturbations limits their use in practical applications. In this paper, we (i) propose a novel adversarial perturbation detection scheme based on multi-task perception of complex vision tasks (i.e., depth estimation and semantic segmentation). Specifically, adversarial perturbations are detected by inconsistencies between extracted edges of the input image, the depth output, and the segmentation output. To further improve this technique, we (ii) develop a novel edge consistency loss between all three modalities, thereby improving their initial consistency which in turn supports our detection scheme. We verify our detection scheme's effectiveness by employing various known attacks and image noises. In addition, we (iii) develop a multi-task adversarial attack, aiming at fooling both tasks as well as our detection scheme. Experimental evaluation on the Cityscapes and KITTI datasets shows that under an assumption of a 5% false positive rate up to 100% of images are correctly detected as adversarially perturbed, depending on the strength of the perturbation. Code is available at https://github.com/ifnspaml/AdvAttackDet. A short video at https://youtu.be/KKa6gOyWmH4 provides qualitative results.

In this paper we present a potential energy map based approach that provides a framework for the design and control of a robotic grasper. Unlike other potential energy map approaches, our framework considers friction for a more realistic perspective on grasper performance. Our analysis establishes the importance of considering dynamically variable geometry in grasper design, namely palm width, link lengths, and transmission ratios, which are assumed to be able to change in real-time. Our analysis assumes a two-phalanx tendon-pulley underactuated grasper, but it can be extended to other underactuated mechanisms. We demonstrate the utility of these novel potential energy maps and the method used to generate them in order by showing how various design parameters impact the grasping and in-hand manipulation performance of a particular design across a range of object sizes and friction coefficients. Optimal grasping designs have palms that scale with object size and transmission ratios that scale with the coefficient of friction. Using a custom in-hand manipulation metric, we compared the in-hand manipulation capabilities of a grasper that only dynamically varied its palm size, link lengths, and transmission ratios to a grasper with a variable palm and controllable actuation efforts. The analysis revealed the advantage of dynamically variable geometry; by varying only its palm size, link lengths, and transmission ratios in real-time, safe, caged in-hand manipulation of a wide range of objects could be performed.

Existing robotic endoscopes for laparoscopic surgery, predominantly rigid or limited in dexterity, occupy a large motion space1, The large occupied motion space necessitates large incisions and reduces the motion space for surgeons to simultaneously operate other surgical instruments. Meanwhile, surgeons only have limited view adjustment capability to avoid occlusion and they often have to lift/push some organs to observe occluded target lesions in some operations such as cholecystectomy. The situation gets worse when the operations are on obese patients. In this paper, we develop a novel dexterous robotic flexible endoscope (DRFE), which is comprised of a concentric cable-driven structure and a 2-DoF articulated joint attached to the end of DRFE, for laparoscopic surgery. The proposed design occupies much less motion space both inside and outside human body as compared to conventional robotic flexible endoscopes. When used in surgery, the part of the endoscope outside the body can remain still, which reduces the risk of expanding the incision and simplifies the structure of the remote center mechanism. Simulation and experimental studies are performed to validate the effectiveness of the proposed device in the improvement of vision occlusion and usability. Initial results reveal that the DRFE is highly dexterous and accurate in observing lesions with vision occlusion.

In this paper, we introduce a composable and extensible drone with tilting rotors (CEDTR). We aimed for a function that could optimally match the load capacity, degree of freedom (DOF), speed and endurance with diverse mission requirements by changing the quantity and form of combinations. First, we propose a decentralized modular controller to allow a team of physically connected modules to fly cooperatively. Second, we divide all the combinations into three categories according to the different control methods. Three generalized control strategies are proposed to control both position and attitude independently by tilting the directions of the propellers. We carried out experiments to demonstrate the feasibility of this mechanical design and control method. The experiment video is available at https://youtu.be/7RvxiV4FPq4.

Enabling vertical take-off and landing while pro-viding the ability to fly long ranges opens the door to a wide range of new real-world aircraft applications while improving many existing tasks. Tiltrotor vertical take-off and landing (VTOL) unmanned aerial vehicles (UAVs) are a better choice than fixed-wing and multirotor aircraft for such applications. Prior works on these aircraft have addressed the aerodynamic performance, design, modeling, and control. However, a less explored area is the study of their potential fault tolerance due to their inherent redundancy, which allows them to tol-erate some degree of actuation failure. This paper introduces tolerance to several types of actuator failures in a tiltrotor VTOL aircraft. We discuss the design and modeling of a custom tiltrotor VTOL UAV, which is a combination of a fixed-wing aircraft and a quadrotor with tilting rotors, where the four propellers can be rotated individually. Then, we analyze the feasible wrench space the vehicle can generate and design the dynamic control allocation so that the system can adapt to actuator failures, benefiting from the configuration redundancy. The proposed approach is lightweight and is implemented as an extension to an already-existing flight control stack. Extensive experiments validate that the system can maintain the controlled flight under different actuator failures. To the best of our knowledge, this work is the first study of the tiltrotor VTOL's fault-tolerance that exploits the configuration redundancy. The source code and simulation can be accessed from https://theairlab.org/vtol.

Compliance is good. However, it is challenging for one compliant continuum robot to finish both high precision manipulation and environmental-adapted motions. In this paper, a modular continuum robot with the alterable compliance characteristic is proposed. Besides, an actuation module is also proposed using a tubular-screw mechanism for non-slippage transmission. Kinematic analyses and dynamic co-simulation are performed to study the continuum robot. Furthermore, two potential application scenarios of pick-and-place manipulation and confined space navigating are carried out to demonstrate the advantages of the alterable compliance design. This study presents a capable continuum robotic solution for non-structural inspection tasks, with potential for in-situ applications in restricted and hazardous environments.

The field of bioacoustics is concerned with monitoring wild animals based on their vocalisations. Passive acoustic recorders are now commonly used to collect data of the soundscapes of our wild places. While the data they collect is extremely useful, the majority of the recorders use a single omnidirectional microphone, and thus cannot independently perform localisation of a calling animal. Localisation can be useful to differentiate between multiple calling animals, to improve statistical estimates of abundance, and to locate calling posts, which may be close to nests. In this paper, we consider the design of a low-cost, practical, passive directional acoustic recorder that will facilitate animal localisation, and present and evaluate a prototype system for this purpose.