IROS 2017 论文列表

A special type of rotary-wing Unmanned Aerial Vehicles (UAV), called Quadcopter have prevailed to the civilian use for the past decade. They have gained significant amount of attention within the UAV community for their redundancy and ease of control, despite the fact that they fall under an under-actuated system category. They come in a variety of configurations. The “+” and “x” configurations were introduced first. Literature pertinent to these two configurations is vast. However, in this paper, we define 6 additional possible configurations for a Quadcopter that can be built under either “+” or “x” setup. These configurations can be achieved by changing the angle that the axis of rotation for rotors make with the main body, i.e., fuselage. This would also change the location of the COM with respect to the propellers which can add to the overall stability. A comprehensive dynamic model for all these configurations is developed for the first time. The overall stability for these configurations are addressed. In particular, it is shown that one configuration can lead to the most statically-stable platform by adopting damping motion in Roll/Pitch/Yaw, which is described for the first time to the best of our knowledge.

This paper proposes an architecture with a two-layered structure for implementing an air-hockey robot that performs tactically in the deployment of entertainment robots. The two-layered architecture is comprised of two components: a tactical component that governs tactics and a skill component that deals with individual shots. The skill layer shoots a puck autonomously by selecting an appropriate way of shooting while considering what is physically feasible. The tactical layer controls the behavior of the skill layer by adjusting a probability function for selecting shooting methods. In this study, we implemented the architecture and conducted experiments to demonstrate its usefulness.

This work presents a rapidly deployable system for automated precision weeding with minimal human labeling time. This overcomes a limiting factor in robotic precision weeding related to the use of vision-based classification systems trained for species that may not be relevant to specific farms. We present a novel approach to overcome this problem by employing unsupervised weed scouting, weed-group labeling, and finally, weed classification that is trained on the labeled scouting data. This work demonstrates a novel labeling approach designed to maximize labeling accuracy whilst needing to label as few images as possible. The labeling approach is able to provide the best classification results of any of the examined exemplar-based labeling approaches whilst needing to label over seven times fewer images than full data labeling.

This paper is motivated by the questions: What would happen if a humanoid robot is put on a Segway? Is it possible for the humanoid robot to use this transportation device that is specifically designed for human? Simulation involving a two-wheeled mobile platform (TWMP) and our humanoid robot COMAN (COmpliant HuMANoid Platform) shows that it is indeed feasible without any hardware modification. Regarding the implementation, the full dynamics of the humanoid robot is considered and quadratic optimization is employed to generate whole-body joint torques to realise two types of tasks according to the interaction type between the TWMP and the humanoid robot. The TWMP is considered as unknown disturbance and the humanoid robot has to keep balancing on it in the first type of task. On the contrary, the active movement of the humanoid robot is utilised as an interface to intuitively drive the TWMP in the second type of task. For both tasks, tracking the position of center of mass (CoM) and regulating the angular momentum around it are considered as primary objectives, stabilizing the posture of certain part of its body is optional. In addition, both tasks are repeated on uneven terrain to demonstrate the robustness of the control method.

Picking various objects in cluttered narrow space automatically is required for warehouse automation. In this space, multi-fingered robot hands have difficulty in grasping objects as objects are surrounded by obstacles. On the other hand, vacuum grippers have difficulty in grasping various objects stably. In this paper, we propose the Suction Pinching Hand, which has two underactuated fingers and one extendable and foldable suction finger whose fingertip has a suction cup. This hand can grasp objects in cluttered narrow space using the suction finger. In addition, it can grasp various objects stably using suction and pinch at the same time. The ability to grasp various objects stably of this hand is confirmed by tabletop experiments. We also propose a picking strategy using suction and pinch simultaneously in cluttered narrow space. We evaluate our proposed methods with shelf bin picking experiments. With our methods, a robot can pick various objects in cluttered narrow space.

This paper presents a simple prototype of a lightweight sensing and tactile communication system that allows bidirectional communication between two humans, or between a human and a computer. This system tracks the user's actions with simple sensors, and uses tiny vibration motors as feedback devices. Vibration motors provide feedback that is both intuitive and minimally intrusive. The design is simple, flexible, and extensible to large-scale, full-body motion tasks.

We present a systematic co-design optimization framework that enables comparison of antagonist variable stiffness actuators (VSA) with and without spring symmetry constraints. The proposed framework promotes a fair comparative analysis by maintaining design continuity among system-optimal designs of symmetric and asymmetric VSA configurations. Through a case study of a VSA-powered knee prosthesis, we not only demonstrate that co-design of robots driven by VSAs can provide important performance benefits with respect to sub-system level control-optimal designs, but also provide evidence that relaxing symmetry constraints for certain periodic tasks can result in substantial advantages in performance. Our systematic comparative analysis justifies the use of asymmetric stiffness arrangements for antagonistic VSA-powered robotic systems performing periodic tasks.

Precision is an important feature in modern robotics and manipulation technology. Elevation of the robot's end-effector precision depends on different features as stiffness, tolerance etc. which should be considered during the synthesis and design phase of the manipulator. The focus of this study is on the structural stiffness of parallel kinematic manipulators (PKM) exhibiting actuation redundancy. It is determined how the stiffness depends on physical and geometrical characteristics of the manipulator and how it is possible to take advantage of redundancy to enhance the stiffness of the manipulator. It is shown that redundantly actuated PKM (RA-PKM) with components made of softer and accordingly lighter materials demonstrate comparable stiffness to the non-redundant manipulators which consequently decrease the required energy for moving the dead-load in operation. Based on the model built in this study, optimizations are conducted and manipulators with optimal morphologies for different tasks are introduced. As a case study, RA-PKM of type n-R RPaRs are considered.

As robots participate in human's daily activities more and more frequently, mobility performance has become one of the main factors determining how robots will share an environment with humans harmoniously in the near future. Among several different kinds of mobile platforms, using omnidirectional configurations is gradually becoming a trend in the robotics community; however, few researchers have addressed the impact of omnidirectional mobility from the perspective of human-robot interaction (HRI). In this paper, we have proposed a socializing model for the robot while participating in an interaction with a group of human peers to achieve its socially optimal position. From a theoretic perspective, we first identify the most prominent features required for social acceptance of robots interacting with multiple humans, backing our arguments with relevant sociological theory. To validate our results, we have conducted experiments where human participants were invited to interact with a robot, which can be constrained to perform either holonomic or nonholonomic motions only. Then, through an observer survey, we testify the appropriateness of utilizing omnidirectional mobility and verify the promotion of social acceptance using the aforementioned features, which is a goal that both the HRI and robotics communities aim to achieve.

Twisted string actuators are widely used in different areas of robotics, however, their lifetime remains one of the main concerns for robotics. There are no comprehensive studies that relate the lifetime of a twisted string to its material properties and operation conditions, which can be important to improve the life cycle. This paper provides preliminary results of an extensive experimental study on twisted string actuators, using strings made of different materials and operating in various working conditions. We experimentally investigated the life time of two different strings and provided empiric mathematical model which relates operating conditions of TSAs and string material and properties to their endurance. Based on experimental results, the observations are made that the life cycle of the strings decreases exponentially with the increase in load forces and stroke and increases linearly with the increase in the number of strings.

The increasing energy consumption within the industrial sector causes great concerns among numerous countries. Accordingly, an extensive reorientation towards an energy-efficient facility and processes design is essential for innovative production systems. In terms of automated object manipulation, energy efficiency significantly is affected by the physical design as well as by the dynamic characteristics of the manipulator. Since the influence on physical design parameters often is limited, a great impact on energy-efficiency of innovative manufacturing systems may result from an intelligent task management and suitable motion strategies. This contribution identifies energy-efficiency potentials for industrial manipulators in terms of motion design and redundant actuator configurations. In this context, an efficient trajectory planning algorithm is proposed, estimating the energy demand of object manipulation tasks in consideration of dynamic motion parameters as well as redundant actuator configurations. For this purpose, the geometric path as well as the motion law of given trajectories are optimized by a spatial displacement of predefined nodes and by an adjustment of corresponding time intervals. In order to verify its generality, the presented method is applied to the spatial n-PRPaR manipulator exhibiting actuation redundancy. According results show a significant energy reduction, establishing high potentials for an increased efficiency of industrial robots.

Trajectory optimization with direct collocation are widely used in various bipedal walking studies, from dynamic simulation in biomechanics to efficient bipedal walking motion generation with multiple contact domains. Although the latter has gained popularity, most of the approaches in this field in general rely on pre-determined contact sequence (domains). This motivates us to use trajectory optimization through contact for generating an efficient and human-like walking gait, because this approach can automatically generate the contact sequence by solving a nonlinear program (NLP) with complementary constraints. However, in this approach the initial guess affects the result significantly, and the direct collocation with Euler method may not be accurate enough for the system dynamics. Therefore, we propose a modified framework and constraints to improve the generated results. We used a zero moment point (ZMP)-based flat-feet walking gait as an initial guess. We also show how to add virtual components like springs at ankle joints to alter the behavior of the resultant walking gait. In addition, considering the one-sided springs at the passive toe joints of the bipedal robot AMBER 3, additional complementary constraints are introduced for a better match of the full dynamics. The results of our modified approach with different constraint conditions are presented and discussed.

Achieving stable bipedal robotic walking on deformable terrain is an open and challenging problem at the intersection of robotics and physics. Ground deformation introduces underactuation; uncertainty in terrain dynamics further complicates dynamical modeling and control methods. This work provides a stability criterion for flat-footed bipedal locomotion and allows model-based control methods to function on homogeneous deformable granular terrain (e.g. sand and dirt). By characterizing static reaction forces from granular materials, in conjunction with granular resistive force theory (RFT), we model and validate a static stability region for the center of mass (CoM) projection of a biped on a granular surface. We show that this stability region approximates the admissible Zero Moment Point (ZMP) region for walking, rendering common Linear Inverted Pendulum Model (LIPM) methods valid with our foot placement strategy. By interpreting the stability region as the maximum reaction moment of the terrain, we formulate walking as a hybrid dynamical system and utilize the partial hybrid zero dynamics (PHZD) based methodology to generate walking gaits. Finally, we experimentally validate both the ZMP and PHZD walking gaits on a planar bipedal robot, showing that the stability region criterion permits stable dynamic walking on homogeneous granular terrain.

We consider an orienteering problem (OP) where an agent needs to visit a series (possibly a subset) of depots, from which the maximal accumulated profits are desired within given limited time budget. Different from most existing works where the profits are assumed to be static, in this work we investigate a variant that has arbitrary time-dependent profits. Specifically, the profits to be collected change over time and they follow different (e.g., independent) time-varying functions. The problem is of inherent nonlinearity and difficult to solve by existing methods. To tackle the challenge, we present a simple and effective framework that incorporates time-variations into the fundamental planning process. Specifically, we propose a deterministic spatio-temporal representation where both spatial description and temporal logic are unified into one routing topology. By employing existing basic sorting and searching algorithms, the routing solutions can be computed in an extremely efficient way. The proposed method is easy to implement and extensive numerical results show that our approach is time efficient and generates near-optimal solutions.

We introduce RoomsSeg, a novel method for segmenting occupancy grid maps into regions that represent rooms and corridors in the real world. The segmentation is utilized for systematic room-by-room cleaning on autonomous vacuum cleaners running in private homes. RoomsSeg is based on automated clutter removal and watershed segmentation on grid maps. Segmented regions are merged into rooms by semantic decision rules. Presented experimental results clearly indicate the efficiency and accuracy of the approach when compared with state of the art methods. When deployed on cleaning robots, a substantial decrease in mission time can be achieved.

Objective: This work presents a method for the use of a soft multi-axis force sensor to determine tissue trauma in Minimally Invasive Surgery. Despite recent developments, there is a lack of effective haptic sensing technology employed in instruments for Minimally Invasive Surgery (MIS). There is thus a clear clinical need to increase the provision of haptic feedback and to perform real-time analysis of haptic data to inform the surgical operator. This paper establishes a methodology for the capture of real-time data through use of an inexpensive prototype grasper. Fabricated using soft silicone and 3D printing, the sensor is able to precisely detect compressive and shear forces applied to the grasper face. The sensor is based upon a magnetic soft tactile sensor, using variations in the local magnetic field to determine force. The performance of the sensing element is assessed and a linear response was observed, with a max hysteresis error of 4.1% of the maximum range of the sensor. To assess the potential of the sensor for surgical sensing, a simulated grasping study was conducted using ex vivo porcine tissue. Two previously established metrics for prediction of tissue trauma were obtained and compared from recorded data. The normalized stress rate (kPa.mm-1) of compression and the normalized stress relaxation (ΔσR) were analyzed across repeated grasps. The sensor was able to obtain measures in agreement with previous research, demonstrating future potential for this approach. In summary this work demonstrates that inexpensive soft sensing systems can be used to instrument surgical tools and thus assess properties such as tissue health. This could help reduce surgical error and thus benefit patients.

Small robots benefit from the ability to go places where humans cannot and are attractive for numerous practical reasons such as portability and manufacturing simplicity. However, with smaller scale comes more difficulty traversing rough terrain, especially for robots which use wheel-based locomotion. Previous approaches to overcome this drawback have included auxiliary mechanisms such as jumping, transformations of the robot or its appendages, and alternative forms of locomotion such as aerial flight capability. This paper presents a small scale robot that is capable of both ground travel and aerial flight. In combination, these methods of locomotion allow for efficient ground-based movement as well as the ability to overcome obstacles and explore otherwise unreachable locations through air travel. The novel aspect of the robot design is a transformation between ground and air configurations. This feature offers advantages over previous approaches such as a highly compact ground configuration and protection of delicate flight hardware when not in use. In this paper, the robot concept is compared to other approaches to address ground robot mobility drawbacks. This is followed by a detailed design description with a focus on the transformation between the ground and air modes. Lastly, a fully functional prototype is presented which is capable of ground and air locomotion and the transformation between these configurations.

This paper presents the development of a skull-mounted robotic headframe for intracranial neurosurgery. The headframe is primarily comprised of a pedestal, a Stewart platform, and a linear actuation module interfacing with a mesoscale neurosurgical robot. In addition to kinematic modeling, motion planning is carried out for neurosurgical procedures using the headframe. Due to the symmetric neurosurgical robot and the insertion and retraction motion of the linear actuation module, the headframe includes kinematic redundancy and it is utilized to enhance the positioning accuracy of the system. In this paper, several simulations are conducted to evaluate the headframe workspace, followed by an experimental study of the positioning error of the neurosurgical robot and a proof-of-concept demonstration of the headframe interfacing with the neurosurgical robot.

It is important for a robot to appropriately respond to its surrounding environment and events to communicate smoothly with humans as opposed to following fixed movements specified in advance. In this paper, a simple bi-layered architecture (SB architecture) is proposed to integrate behaviors in two stages: prioritization and weighted averaging. In addition, SB architecture integrates voluntary movements by prioritization and integrates involuntary and reflex movements by weighted averaging, thereby generating robot behaviors that immediately respond to events that occur around the robot. What advantages SB architecture has are that it can easily generate various behaviors by combining multiple behaviors and that it is possible to propose a simple design for robot behavior. Furthermore, since behavior occurs in response to sensors, the robot's behaviors are reactive to the surrounding environment and events. In particular, if a robot performs the behavior necessary for communication with humans, such as changing its gaze and gestures, it is possible to ensure that the robot possesses liveness to promote communication with humans. In addition, since SB architecture has a simple structure to facilitate the design of robots, it is possible to automatically set parameters by optimizing the parameters using pairs of sensor information and ideal behaviors. The optimization of the parameters leads to generating behaviors characterized with liveness by appropriately combining behaviors.