IROS 2017 Papers

This paper presents an algorithm for localizing an unmanned aerial vehicle (UAV) in GPS denied environments. Localization is performed with respect to a pre-built map of the environment represented using the distance function of a binary mosaic, avoiding the need for extraction and explicit matching of visual features. Edges extracted from images acquired by an on-board camera are projected to the map to compute an error metric that indicates the misalignment between the predicted and true pose of the UAV. A constrained extended Kalman filter (EKF) framework is used to generate an estimate of the full 6-DOF location of the UAV by enforcing the condition that the distance function values are zero when there is no misalignment. Use of an EKF also makes it possible to seamlessly incorporate information from any other system on the UAV, for example, from its auto-pilot, a height sensor or an optical flow sensor. Experiments using a hexarotor UAV both in a simulation environment and in the field are presented to demonstrate the effectiveness of the proposed algorithm.

On novel actuator research in the field of cellular muscle-inspired actuators, skeletal muscles are often used as inspiration due to their modular and compact design and seemingly effortless control. Amongst others, the remaining challenges to tackle are robust designs, energy consumption minimization and control strategies. We have developed a discrete muscle-inspired actuator, in which solenoids can be overpowered and locked to recruit springs in series. This paper describes the spring and electronics design and proposes a binary actuator segmentation for increased resolution. Next, we propose and simulate a control strategy based on a lookup table, to cope with multiple discrete inputs, uni-directional force inputs and solenoid cooling time. Currently, the actuation units and springs are modular and can be tailored easily for specific applications. The resolution is maximized without under utilization of the actuator's capabilities, and our control strategy can currently control 12 motor units in real-time, which can be increased to 30. The experiments confirm the working of the control strategy.

We present a direct visual odometry algorithm for a fisheye-stereo camera. Our algorithm performs simultaneous camera motion estimation and semi-dense reconstruction. The pipeline consists of two threads: a tracking thread and a mapping thread. In the tracking thread, we estimate the camera pose via semi-dense direct image alignment. To have a wider field of view (FoV) which is important for robotic perception, we use fisheye images directly without converting them to conventional pinhole images which come with a limited FoV. To address the epipolar curve problem, plane-sweeping stereo is used for stereo matching and depth initialization. Multiple depth hypotheses are tracked for selected pixels to better capture the uncertainty characteristics of stereo matching. Temporal motion stereo is then used to refine the depth and remove false positive depth hypotheses. Our implementation runs at an average of 20 Hz on a low-end PC. We run experiments in outdoor environments to validate our algorithm, and discuss the experimental results. We experimentally show that we are able to estimate 6D poses with low drift, and at the same time, do semi-dense 3D reconstruction with high accuracy. To the best of our knowledge, there is no other existing semi-dense direct visual odometry algorithm for a fisheye-stereo camera.

In this paper we investigate the application of semi-dense visual Simultaneous Localisation and Mapping (SLAM) to the humanoid robotics domain. Challenges of visual SLAM applied to humanoids include the type of dynamic motion executed by the robot, a lack of features in man-made environments and the presence of dynamics in the scene. Previous research on humanoid SLAM focused mostly on feature-based methods which result in sparse environment reconstructions. Instead, we investigate the application of a modern direct method to obtain a semi-dense visually interpretable map which can be used for collision free motion planning. We tackle the challenge of using direct visual SLAM on a humanoid by proposing a more robust pose tracking method. This is formulated as an optimisation problem over a cost function which combines information from the stereo camera and a low-drift kinematic-inertial motion prior. Extensive experimental demonstrations characterise the performance of our method using the NASA Valkyrie humanoid robot in a laboratory environment equipped with a Vicon motion capture system. Our experiments demonstrate pose tracking robustness to challenges such as sudden view change, motion blur in the image, change in illumination and tracking through sequences of featureless areas in the environment. Finally, we provide a qualitative evaluation of our stereo reconstruction against a LIDAR map.

Direct kinematics (DK) of cable-driven parallel robots (CDPR) based only on cable lengths measurements is a complex issue even with ideal cables and consequently even harder for more realistic cable models such as sagging cable. A natural way to simplify the DK solving is to add sensors. We consider here sensors that give a partial or complete measurement of the cable direction at the anchor points and/or measure the orientation of the platform of CDPR with 2 or 3 cables and we assume that the measurements are exact. We provide a solving procedure and maximal number of DK solutions for an extensive combination of sensors for CDPR with sagging cables. We show that at least two measurements are necessary for the planar 2 cables case while six are necessary for the spatial 3 cables case. For spatial CDPR with n cables we prove that at least 2n additional sensors will be required to get a closed-form solution of the DK.

We propose a direct object manipulation system that a user can manipulate objects constrained to each other by his or her hands. Because there is no haptic feedback to a user, manipulation of constrained objects is much harder than that of a simple rigid body. In addition, many physics simulator usually suffers from instability in handling the constrained objects in a virtual system. We solve the problem by adding another micro simulator which enforce the constraint between the objects, and guarantees that the rendered image of an object and its physics counterpart always satisfy the given constraint. The experiment shows that the proposed method makes a user manipulate constrained objects with no difficulties in the way that he or she manipulates such objects in the real world.

This work presents a study of robot software using the Robot Operating System (ROS), focusing on detecting inconsistencies in physical unit manipulation. We discuss how dimensional analysis, the rules governing how physical quantities are combined, can be used to detect inconsistencies in robot software that are otherwise difficult to detect. Using a corpus of ROS software with 5.9M lines of code, we measure the frequency of these dimensional inconsistencies and find them in 6% (211 / 3,484) of repositories that use ROS. We find that the inconsistency type `Assigning multiple units to a variable' accounts for 75% of inconsistencies in ROS code. We identify the ROS classes and physical units most likely to be involved with dimensional inconsistencies, and find that the ROS Message type geometry_msgs::Twist is involved in over half of all inconsistencies and is used by developers in ways contrary to Twist's intent. We further analyze the frequency of physical units used in ROS programs as a proxy for assessing how developers use ROS, and discuss the practical implications of our results including how to detect and avoid these inconsistencies.

Fluidically actuated soft robots show a great promise for operation in sensitive and unknown environments due to their intrinsic compliance. However, most previous designs use either flow control systems that are noisy, inefficient, sensitive to leaks, and cannot achieve differential pressure (i.e. can only apply either positive or negative pressures with respect to atmospheric), or closed volume control systems that are not adaptable and prohibitively expensive. In this paper, we present a modular, low cost volume control system for differential pressure control of soft actuators. We use this system to actuate three-chamber 3D printed soft robotic modules. For this design, we find a 54% increase in achievable blocked force, and a significant increase in actuator workspace when using differential pressure actuation as compared to the use of only pressure or vacuum. The increased workspace allowed the robot to achieve complex tasks such as writing on a screen with a laser pointer or manipulating fragile objects. Furthermore, we demonstrate a self-healing capability of the combined system by using vacuum to actuate ruptured modules which were no longer responsive to positive pressure.

As the linguistic capabilities of interactive robots advance, it becomes increasingly important to understand how humans will instruct robots through natural language. What is more, with the increased use of teleoperated humanoid robots, it is important to recognize whether any differences between instructions given to humans and to robots are due to the physical embodiment or to the perceived autonomy of the instructee. In this paper, we present the results of a human-subject experiment in which participants interacted in a collaborative, task-based setting with both a human and a suit-based, teleoperated humanoid robot said to be either autonomous or teleoperated. Our results suggest that humans will use politeness strategies equally with human, autonomous robotic, and teleoperated robotic teammates, reinforcing recent findings that autonomous robots must comprehend and appropriately respond to human utterances that follow such strategies. Our results also suggest variations in how different teammates were perceived. Specifically, our results suggest that human-teleoperated robots were perceived as less intelligent than human teammates; a finding with serious implications for human-robot team dynamics.

We propose a method that allows for dexterous manipulation of an object by exploiting contact with an external surface. The technique requires a compliant grasp, enabling the motion of the object in the robot hand while allowing for significant contact forces to be present on the external surface. We show that under this type of grasp it is possible to estimate and control the pose of the object with respect to the surface, leveraging the trade-off between force control and manipulative dexterity. The method is independent of the object geometry, relying only on the assumptions of type of grasp and the existence of a contact with a known surface. Furthermore, by adapting the estimated grasp compliance, the method can handle unmodelled effects. The approach is demonstrated and evaluated with experiments on object pose regulation and pivoting against a rigid surface, where a mechanical spring provides the required compliance.

Developing grasping devices with the capabilities to carry out dexterous tasks similar to human hand are being studied for many decades. To this aim, mathematical analysis such as control of multi-fingered gripper, grasp synthesis algorithms, contact types and their interactions have been explicitly addressed by many researchers. Since human hands are dexterous due to the complex integration of control and numerous sensors, hence they are naturally adaptable to grasp, in-hand manipulation of plurality of object by their construction. On the other hand, artificial grippers require priori knowledge of the payload geometry and configuration to maneuver grasping and manipulation tasks at the very first place. Moreover, theoretical analysis, such as contact kinematics, grasp stability cannot predict the nonholonomic behaviors, and therefore, uncertainties are always present to restrict a maneuver, even though the gripper is kinematically feasible of doing the task. Hence, in general, industrial grippers do exploit simpler mechanisms with least number of fingers and tend to avoid soft materials in the construction primarily to achieve dexterity, reliability, repeatability and speed in the process. However, in-hand manipulation of objects urges certain degrees of flexibility in the gripper design; which is difficult to obtain from a rigid structure and also the use of non-rigid materials reduce speed, accuracy and performance. In this research, a gripper platform named Dexclar (DEXterous reConfigurable moduLAR) is proposed, which addresses the dilemma by combining mechanism and modularity, evaluating payload centric requirements.

Intrinsic problems for legged robots are `low energy efficiency' and `slow speed'. In this paper, we introduce a possible solution achieved through biological observations and developed a robotic leg applying the proposed method. The proposed robotic leg, AiDIN-IV Leg (Artificial DIgitigrade for Natural environment version IV) has high torque density actuators(τpeak = 152Nm, 127rpm), high fidelity force/torque controllability(under 5% torque error) and large energy storing capacity(18J) suitable for high-speed running robot. As a core part, Series Elastic Actuator(SEA), achieve large passive deflection angle(47.6°) for storing the energy as much as possible(maximally 37.9J), and constant joint stiffness coefficient. Additionally, oscillation compensator for rejecting the oscillation of SEA and Harmonic Drive efficiency compensator are introduced and successfully tested in the proposed robotic leg.

This paper addresses online outdoor sound source localization using a microphone array embedded in an unmanned aerial vehicle (UAV). In addition to sound source localization, sound source enhancement and robust communication method are also described. This system is one instance of deployment of our continuously developing open source software for robot audition called HARK (Honda Research Institute Japan Audition for Robots with Kyoto University). To improve the robustness against outdoor acoustic noise, we propose to combine two sound source localization methods based on MUSIC (multiple signal classification) to cope with trade-off between latency and noise robustness. The standard Eigenvalue decomposition based MUSIC (SEVD-MUSIC) has smaller latency but less noise robustness, whereas the incremental generalized singular value decomposition based MUSIC (iGSVD-MUSIC) has higher noise robustness but larger latency. A UAV operator can use an appropriate method according to the situation. A sound enhancement method called online robust principal component analysis (ORPCA) enables the operator to detect a target sound source more easily. To improve the stability of wireless communication, and robustness of the UAV system against weather changes, we developed data compression based on free lossless audio codec (FLAC) extended to support a 16 ch audio data stream via UDP, and developed a water-resistant microphone array. The resulting system successfully worked in an outdoor search and rescue task in ImPACT Tough Robotics Challenge in November 2016.

In this paper, we described a new developed life-size humanoid robot. A purpose of the developed robot is to realize continuous operation for a long time and to improve an action autonomously. we considered three aspects of robustness, mechanical robustness, functional robustness and robustness of an action. Mechanical robustness was confirmed by the experiment that the robot fell down without mechanical failures and continued to work after falling down by using hard points. Functional robustness was designed to use power cable and to wear a suit which can be changed by required functionality. Robustness of an action was achieved as a standing up action using “StateNet”, which realized autonomous error recovery. Finally, we present a methodology to develop a humanoid robot platform which can continue to work in the real world.

In this paper, a new experimental legged robot for inspection and disaster response in social infrastructures designed for humans, such as factories and power plants is presented. The robot has distinctive features to climb up and down ladders with a narrow cage, to pass through narrow environments, to move upon scattered debris at disaster sites and to deal with sudden and unexpected contact. The robot also satisfies environmental requirements related to dust, water, and temperature. To implement environmental resistance to a slim body for movement in a narrow environment, cooling of heat sources such as CPUs is a serious problem. Therefore a new cooling structure for humanoid robots is proposed. The proposed robot experiments on the above features are also shown in this paper.

Bio-inspired underwater robots have several benefits compared to traditional underwater vehicles such as agility, efficiency, and environmentally friendly body. However, bio-inspired underwater robots developed so far have a single swimming mode, which may limit their capability to perform different tasks. This paper presents a re-configurable bio-inspired underwater robot that can change the morphology to enable multiple swimming modes: octopus-mode and fish-mode. The robot is 60 cm long and 50 cm wide, weighing 2.1 kg, and consists of a re-configurable body and 8 compliant arms that are actuated independently by waterproof servomotors. In the robot, the octopus-mode is expected to perform unique tasks such as object manipulation and ground locomotion as demonstrated in literature, while the fish-mode is promising to swim faster and efficiently to travel long distance. With this platform, we investigate the effectiveness of adaptive morphology in bio-inspired underwater robots. For this purpose, we evaluated the robot in terms of the cost of transport and the swimming efficiency of both the morphologies. The fish-mode exhibited a lower cost of transport of 2.2 and higher efficiency of 1.2 % compared to the octopus-mode, illustrating the effect of the multiple swimming modes by adaptive morphology.

This work presents the design and evaluation of a low-cost tri-axial force sensor, that has been developed to regain the sense of touch in minimally invasive surgeries (MIS). The force sensor uses an array of force sensitive resistors (FSR) with a mechanically pre-loaded structure to perform the force sensing. The sensor has a built-in signal conditioning circuitry to provide on-board power regulation, programmable signal amplification and analog to digital conversion. The sensor is inexpensive and highly sensitive to low-amplitude force, critical in surgical applications. We validate the efficacy of the sensor with two surgical applications - robotic palpation for stiffness mapping and obstacle avoidance for a highly articulated robotic probe (HARP). The results show that the sensor is capable of accurately detecting the stiff inclusions embedded in the tissues as well as detecting obstacles and helping HARP safely navigate around them.

This paper presents an adjustable knee mechanism for walking assistance devices for the elderly to provide physical gait assistance. The adjustable knee mechanism can assist in flexion/extension motions of the knee joint and compensate for the transitional movements of the knee in the sagittal plane as well as aligning the frontal plane. In order to compensate for the center of rotation, the proposed adjustable knee mechanism is implemented by connecting several rolling cams with unique and precisely calculated contact geometries. The key idea of the proposed mechanism is to realize linear motion and accurate torque transmission by a pulley method using the rolling joint in which the distance of the center between the rolling cams is changed. The proposed articulated joint can effectively deliver the torque required for assistance while adapting to the joint motion of the wearer. This paper describes the mechanical design of this knee mechanism and its implementation on a wearable robot and in preliminary experiments. The performance of the proposed mechanism was verified by simulations and experiments.

This paper presents the design, development and preliminary evaluation of a soft-inflatable exosuit for knee rehabilitation. Soft-inflatable actuators made of heat-sealable thermoplastic polyurethane (TPU) materials are fabricated in two different beam-like structures (I and O cross-section actuators) and mechanically characterized for their torque performance in knee-extension assistance. The fabrication procedure of both types of actuators is presented as well as their integration into a lightweight, low-cost and body-conforming interface. To detect the activation duration of the device during the gait cycle, a soft-silicone insole with embedded force-sensitive resistors (FSRs) is used. In evaluation studies, the soft-inflatable exosuit device is tested for its ability to reduce muscle activity during the swing phase of the knee. Using sEMG (surface electromyography) sensors, the rectus femoris muscle group of a healthy individual is recorded while walking on a treadmill at a constant speed, with and without the soft device. Preliminary testing presents a promising 7% reduction in muscle activity and demonstrates the applicability of the soft-inflatable exosuit in knee rehabilitation scenarios.