IROS 2015 论文列表

Exploiting interaction with the environment is a promising and powerful way to enhance stability of humanoid robots and robustness while executing locomotion and manipulation tasks. Recently some works have started to show advances in this direction considering humanoid locomotion with multi-contacts, but to be able to fully develop such abilities in a more autonomous way, we need to first understand and classify the variety of possible poses a humanoid robot can achieve to balance. To this end, we propose the adaptation of a successful idea widely used in the field of robot grasping to the field of humanoid balance with multi-contacts: a whole-body pose taxonomy classifying the set of whole-body robot configurations that use the environment to enhance stability. We have revised criteria of classification used to develop grasping taxonomies, focusing on structuring and simplifying the large number of possible poses the human body can adopt. We propose a taxonomy with 46 poses, containing three main categories, considering number and type of supports as well as possible transitions between poses. The taxonomy induces a classification of motion primitives based on the pose used for support, and a set of rules to store and generate new motions. We present preliminary results that apply known segmentation techniques to motion data from the KIT whole-body motion database. Using motion capture data with multi-contacts, we can identify support poses providing a segmentation that can distinguish between locomotion and manipulation parts of an action.

Safety is one of the most important issues in walking support robots. We have proposed a walking support robot equipped with velocity and torque-based mechanical safety devices. The velocity-based safety device and the torque-based safety device are attached to each drive-shaft of the robot. If the velocity-based safety device detects an unexpected high angular velocity of the drive-shaft, it stops the robot. If the torque-based safety device detects an unexpected high torque of the drive-shaft, it cuts off the torque transmission and switches off all of the robot's motors. This paper proposes a new walking support robot equipped with not only the velocity-based and torque-based safety devices but also contact force-based safety devices. The contact force-based safety device stops the robot if it detects an unexpected large contact force between the robot and the environment (e.g. humans). These safety devices will work even when the computer breaks down, because they consist of only passive mechanical components without actuators, controllers, or batteries. Firstly, we describe the walking support robot with the safety devices. Secondly, we show the prototype walking support robot which we developed. Finally, we verify the effectiveness of the safety devices by experiments.

In many applications, robots have to bear large loads while moving slowly and also have to move quickly through the air with almost no load. This leads to conflicting requirements for their actuators. Multiple gear ratios, like in a powertrain, address this issue by allowing an effective use of power over a wide range of output speed. However in robotics, as opposed to powertrains, the controlled load is not always inertial and acting as a low-pass filter; hence gear shifting is a more challenging issue in a robotics context. In this paper, it is proposed to address this problem using a dual-speed dual-motor architecture to maintain full control of the output during gear shifting. A dynamic model is developed and a controller using the redundancy of motors is proposed to enable fast seamless gear shifting even when interacting with unknown dynamic environments. Results are demonstrated with a proof-of-concept linear actuator.

In this paper, we present a novel wheeled robot that transforms from a circled configuration to a spoke-like legged configuration. Wheeled mobile robots are able to quickly and efficiently move on flat surfaces. However they may sink into a terrain with dynamic surface such as snow, sand, dirt, moss, and small gravel. The transformable wheel robot presented in this paper is able to overcome obstacles and navigate these dynamics surfaces, yet can still move quickly over flat ground. The wheel is comprised of five spokes or legs, four of which are actively driven by a motor via four slider-crank linkages. The last one is designed be passive in order to significantly decrease the actuation force of the transformer mechanism. Analysis shows that the maximum driving force required to actuate the passive leg design is 1/187.5 times that of the active leg design. Experiments demonstrate that the passive leg design allows the mobile robot to open the transformation mechanism with a maximum external loading of 1.809 times the original robot weight. The diameter of the legged configuration wheel is 1.576 times that of the circled configuration.

This paper describes a novel foot for biped robots designed to provide a reliable and low-cost solution for sensing the Center of Pressure (CoP) on flat and uneven surfaces. The foot uses a new method for detecting contact forces based on measuring the deflection of three flexural toes using Hall-effect magnetic field sensors. We experimentally compare five mathematical models for calculating the CoP coordinates from the sensor data. Results confirm that with the proposed method it is possible to obtain the same level of accuracy and reliability as with standard force sensing resistors, but without some the drawbacks of that approach.

Tendon-driven continuum robots offer increased dexterity and manipulability in comparison to conventional rigid link serial manipulators. Being able to conform to complex curves in 3D space, continuum robots are in particular useful for applications in restricted and hardly accessible environments. The workspace of a tendon-driven continuum robot depends on the number of sections, as well as the length of each section and its range of bending radii. Common tendon-driven robot designs have fixed section lengths such that deployment along a tortuous paths requires additional linear translation of the whole robot. In this paper, we propose a novel tendon-driven continuum robot with extensible sections. A telescoping backbone allows control of the section length during operation in addition to bending through tendon actuation. Thus, the arc length of a section can vary and the range of bending radii is enlarged. As a result, the novel robot design inherently allows for deployment along tortuous paths in a follow-the-leader fashion. We suggest the use of spacer disks equipped with permanent magnets with alternating pole orientation. The magnetic repulsion forces enable equidistant spacing of the disks at any lengths of a robot section. We prove the concepts of our novel design with experiments using a first prototype.

Bio-inspired legged robots with compliant actuation can potentially achieve motion properties in real world scenarios which are superior to conventionally actuated robots. In this paper, a methodology is presented to systematically design and tailor passive and active control elements for elastically actuated robots. It is based on a formal specification of requirements derived from the main design principles for embodied agents as proposed by Pfeifer et al. which are transfered to dynamic model based multi objective optimization problems. The proposed approach is demonstrated and applied for the design of a biomechanically inspired, musculoskeletal bipedal robot to achieve walking and human-like jogging.

This paper presents a systematic approach for experimental identification and assessment of mechanical effects on the dynamics of elastic actuators. The variable torsion stiffness (VTS) actuator is used as an example. As a basis for parameter identification, a flexible joint robot model considering friction and damping is used. To identify and assess occurring effects, a component-wise experimental investigation of the VTS drive train is performed. In this, influences of friction and inertia are examined using numerical least-squares regression to identify link inertia, friction in bearings, stiffness and damping in the elastic element, and the friction of gear box and actuator based on measured data. Comparing simulations to measured data, allows an evaluation of the obtained particular parameters and an assessment of their impact on overall system dynamics. Hence, the component-wise procedure enables to decide if those should be considered. This approach can be generalized to other elastic actuators by adapting model structure and/or performed experiments.

Rapid separation and transfer of target cells from heterogeneous mixture to desired region have become a key issue in many biomedical applications. In this paper, we propose an approach to high speed cell transfer for sorting rare cells from a small population of samples accurately using a robotic manipulation system equipped with optical tweezers. A novel switching geometrical model is established first for modeling high speed cell transfer, optical laser trapping, and obstacle avoidance based on the dynamics analysis. A normalized constraint function is designed to formulate how the trapped cell is maintained within the optical trap while avoiding obstacles. Then, a potential field based switching controller is developed, which can achieve automated cell trapping, high speed cell transfer, optical trap maintenance, and obstacle avoidance simultaneously. Finally, experiments of transferring cancer cells are performed to demonstrate the effectiveness of the proposed approach.

The use of parallel robots has been demonstrated to be an interesting alternative when high accuracy and/or high speed is required. However, in order to achieve these goals, model based controllers are required. This work presents a new model based control approach, the stable Extended CTC, that uses extra data from additional sensors introduced in the passive joints of parallel robot in the controller. The proposed controller guarantees asymptotic stability, which is an important contribution over the previously presented approaches. The use of redundant information increases controller robustness and performance, allowing to reduce tracking error with respect to traditional CTC approaches. The effectiveness of the proposed control law is demonstrated by implementing it in a Delta robot which has been modeled in ADAMS multibody software.

This paper presents a novel approach to achieving aerial pitch righting in a mobile robot, inspired by the draglines used by jumping spiders. We developed and simulated a mathematical model of the spider during the aerial phase of its jump to gain further insight into the factors affecting the pitch response. The results demonstrate that the dragline could also potentially function as a brake, slowing the spider down before landing. Subsequently, we developed a small robotic platform to demonstrate dragline-based aerial pitch righting on a robot experimentally. Lastly, the possible size and weight advantages over other pitch righting methods are discussed.

We introduce a new problem in the area of scheduling and route planning operations called the service agent transport problem (SATP). Within the SATP, autonomous service agents must perform tasks at a number of locations. The agents are free to move between locations, however, the agents may also be transported throughout the region by a limited number of faster-moving transport agents. The goal of the SATP is to plan a schedule of service agent and transport agent actions such that all locations are serviced in the shortest amount of time. We pose the problem using a mixed-integer linear programming optimization framework, and compare several complexity reduction heuristics to the full optimization.

We present a fiber reinforced soft pneumatic actuator with integrated strain and pressure sensors. We demonstrate that combining these sensors into the same actuator enables proprioception of both actuator curvature and environmental contact forces. We describe the manufacture and integration of a simple liquid metal strain sensor, a pressure sensor, and electrical circuits used for the sensors. We derive a constant curvature model for the actuator which predicts actuator curvature from the air pressure, and other constants of manufacture. The utility of the sensor integration is demonstrated by using the actuator to distinguish successful grasps amongst a set of common cylindrical objects with varying diameter. The grasp radius is estimated from the relationship between the sensor pair. Contact forces with the environment (touch) may be inferred from sensor readings which deviate from unconstrained motion.

Soft-bodied robots are designed to work in the physical world with a high compliance, while most of them lack in highly dynamic motion. In this paper, we present a soft-bodied jumping robot, which leverages its body's elasticity to achieve a highly dynamic passive bouncing motion after an active jumping motion. This robot has a cubic shape. It is covered by silicone foam, and each of its six faces has an opening to allow for jumping actuation. By winding up and releasing an elastic strip, the robot can jump in two directions at any orientation. We present the design, and fabrication process, and experimental results. By comparing this robot with a rigid version of the robot, we show that this soft-bodied robot can use a single jump to travel longer forward than its rigid counterpart.

This paper presents a sensorimotor contingencies (SMC) based method to fully autonomously learn to perform hand-eye coordination. We divide the task into two visuomotor subtasks, visual fixation and reaching, and implement these on a PR2 robot assuming no prior information on its kinematic model. Our contributions are three-fold: i) grounding a robot in the environment by exploiting SMCs in the action planning system, which eliminates the need for prior knowledge of the kinematic or dynamic models of the robot; ii) using a forward model to search for proper actions to solve the task by minimizing a cost function, instead of training a separate inverse model, to speed up training; iii) encoding 3D spatial positions of a target object based on the robot's joint positions, thus avoiding calibration with respect to an external coordinate system. The method is capable of learning the task of hand-eye coordination from scratch by less than 20 sensory-motor pairs that are iteratively generated at real-time speed. In order to examine the robustness of the method while dealing with nonlinear image distortions, we apply a so-called retinal mapping image deformation to the input images. Experimental results show the successfulness of the method even under considerable image deformations.

We propose a sensor-driver integrated muscle module by integrating necessarily components for tendon-driven robot which is likely to complicate. The module has abilities of high-tension measurability and flexible tension control. In order to achieve flexible tension control, we developed the new tension measurement mechanism with high-tension measurability and the new motor driver which enables current based motor control. We demonstrate the tension control ability of the module by several experiments. Furthermore, utilizing the module advantage of design facilitation, we made two types of tendon-driven robots and confirmed effectiveness of the module.

Two leading qualities of skeletal muscle that produce good performance in uncertain environments are damage tolerance and the ability to modulate impedance. For this reason, robotics researchers are greatly interested in discovering the key characteristics of muscles that give them these properties and replicating them in actuators for robotic devices. This paper describes a method to harness the redundancy present in muscle-like actuation systems composed of multiple motor units and shows that they have these same two qualities. By carefully choosing which motor units are recruited, the impedance viewed from the environment can be modulated while maintaining the same overall activation level. The degree to which the impedance can be controlled varies with total activation level and actuator length. Discretizing the actuation effort into multiple parts that work together, inspired by the way muscle fibers work in the human body, produces damage-tolerant behavior. This paper shows that this not only produces reasonably good resolutions without inordinate numbers of units, but gives the control system the ability to set the impedance along with the drive effort to the load.

It is well known that a real-time visual servoing task which employs a Visual Tracking Algorithm (VTA) imposes high computational cost to robotic system, which consequently results in higher energy consumption and lower autonomy. Motivated by this fact, this paper presents a novel Image Based Visual Servoing-Model Predictive Control (IBVS-MPC) scheme which is combined with a mechanism that decides when the VTA needs to be triggered and new control inputs must be calculated. Between two consecutive triggering instants, the control input trajectory is applied to the robot in an openloop fashion, i.e, no visual measurements and calculation of the control inputs are required during that period. This results in the reduction of the computational effort, energy consumption and increases the autonomy of the system. These factors are of utmost importance in the case of small autonomous robotic systems which perform vision based tasks, such as surveillance and inspection of indoors and outdoors environments. The visibility and inputs constraints, optimality rate of the MPC, as well as the external disturbances, are being considered during the control design. The efficiency of the proposed scheme is demonstrated through a set of real-time experiments using an eye-in-hand mobile robotic system.

This paper presents a nonlinear control approach for quadrotor Micro Aerial Vehicles (MAVs), which combines a backstepping-like regulator based on the solution of a certain class of global output regulation problems for the rigid body equations on SO(3), a robust controller for the system with bounded disturbances, as well as a trajectory generator using a model predictive control method. The proposed algorithm is endowed with strong convergence properties so that it allows the quadrotor MAVs to reach almost all the desired attitudes. The control approach is implemented on a high-payload-capable quadcopter with unstructured dynamics and unknown disturbances. The performance of our algorithm is demonstrated through a series of experimental evaluations and comparisons with another control method on normal and aggressive trajectory tracking tasks.