soft finger robotic
3544597
On Time Optimization of Centroidal Momentum Dynamics
Recently, the centroidal momentum dynamics has received substantial attention to plan dynamically consistent motions for robots with arms and legs in multi contact scenarios. However, it is also non convex which renders any optimization approach difficult and timing is usually kept fixed in most trajectory optimization techniques to not introduce additional non convexities to the problem. But this can limit the versatility of the algorithms. In our previous work, we proposed a convex relaxation of the problem that allowed to efficiently compute momentum trajectories and contact forces. However, our approach could not minimize a desired angular momentum objective which seriously limited its applicability. Noticing that the non convexity introduced by the time variables is of similar nature as the centroidal dynamics one, we propose two convex relaxations to the problem based on trust regions and soft constraints. The resulting approaches can compute time optimized dynamically consistent trajectories sufficiently fast to make the approach realtime capable. The performance of the algorithm is demonstrated in several multi contact scenarios for a humanoid robot. In particular, we show that the proposed convex relaxation of the original problem finds solutions that are consistent with the original non convex problem and illustrate how timing optimization allows to find motion plans that would be difficult to plan with fixed timing +Implementation details and demos can be found in the source code available at https:/git amd.tuebingen.mpg.de/bponton/timeoptimization.
2018 IEEE International Conference on Robotics and Automation (ICRA)
Brahayam Ponton Alexander Herzog Stefan Schaal Ludovic Righetti
3369782
A cable based series elastic actuator with conduit sensor for wearable exoskeletons
There is currently a scarcity of wearable robotic devices that can practically provide physical assistance in a range of real world activities. Soft wearable exoskeletons, or exosuits, have the potential to be more portable and less restrictive than their rigid counterparts. In this paper, we present the design of an actuation system that has been optimized for use in a soft exosuit for the human arm. The selected design comprises a DC motor and gearbox, a flexible cable conduit transmission, and a custom series elastic force sensor. Placed in series with the transmission conduit, the custom compliant force sensor consists of a translational steel compression spring with a pair of Hall effect sensors for measuring deflection. The custom sensor is validated as an accurate means of measuring cable tension, and it is shown that it can be used in feedback to control the cable tension with high bandwidth. The dynamic effect of the cable conduit transmission on the force felt at the user interface is characterized by backdriving the system as it renders a range of virtual impedances to the user. We conclude with recommendations for the integration of such an actuation system into a full wearable exosuit.
2017 IEEE International Conference on Robotics and Automation (ICRA)
Laura H Blumenschein Craig G Mcdonald Marcia Kilchenman O'Malley
52151069
Rendering of Pressure and Textures Using Wearable Haptics in Immersive VR Environments
Haptic systems have only recently started to be designed with wearability in mind. Compact, unobtrusive, inexpensive, easy to wear, and lightweight haptic devices enable researchers to provide compelling touch sensations to multiple parts of the body, significantly increasing the applicability of haptics in many fields, such as robotics, rehabilitation, gaming, and immersive systems. In this respect, wearable haptics has a great potential in the fields of virtual and augmented reality. Being able to touch virtual objects in a wearable and unobtrusive way may indeed open new exciting avenues for the fields of haptics and VR. This work presents a novel wearable haptic system for immersive virtual reality experiences. It conveys the sensation of touching objects made of different materials, rendering pressure and texture stimuli through a moving platform and a vibrotactile abbrv doi hyperref narrowmotor. The device is composed of two platforms: one placed on the nail side of the finger and one in contact with the finger pad, connected by three cables. One small servomotor controls the length of the cables, moving the platform towards or away from the fingertip. One voice coil actuator, embedded in the platform, provides vibrotactile stimuli to the user.
2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)
Giovanni Spagnoletti Leonardo Meli Tommaso Lisini Baldi Guido Gioioso Claudio Pacchierotti Domenico Prattichizzo
52966213
Design of an Electrohydraulic Hand Orthosis for People with Duchenne Muscular Dystrophy Using Commercially Available Components
People with Duchenne muscular dystrophy are currently in need of assistive robotics to improve their hand function and have a better quality of life. However, none of the available active hand orthoses is able to address to their specific needs. In this study, the use of hydraulic technology is proposed in the design of an active hand orthosis. Commercially available components were used to identify where customization is necessary for a new electrohydraulic hand orthosis. The presented prototype was able to move four finger modules with a single actuator. The finger modules were separable and had a total mass of only 150 g, whereas the valve manifold added another 250 g. Results revealed that the prototype was able to function well with full flexion/extension cycles up to 2 Hz, but with hysteretic losses between 37 81% of the total input energy. Specialized valves and slave cylinders are required to increase efficiency at higher speeds and to obtain more robust sealing performance.
2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)
Ronald A Bos Kostas Nizamis Dick H Plettenburg Just L Herder
53376928
Human Motion Prediction Under Social Grouping Constraints
Accurate long term prediction of human motion in populated spaces is an important but difficult task for mobile robots and intelligent vehicles. What makes this task challenging is that human motion is influenced by a large variety of factors including the person's intention, the presence, attributes, actions, social relations and social norms of other surrounding agents, and the geometry and semantics of the environment. In this paper, we consider the problem of computing human motion predictions that account for such factors. We formulate the task as an MDP planning problem with stochastic policies and propose a weighted random walk algorithm in which each agent is locally influenced by social forces from other nearby agents. The novelty of this paper is that we incorporate social grouping information into the prediction process reflecting the soft formation constraints that groups typically impose to their members' motion. We show that our method makes more accurate predictions than three state of the art methods in terms of probabilistic and geometrical performance metrics.
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Andrey Rudenko Luigi Palmieri Achim J Lilienthal Kai Oliver Arras
173183616
Development of LIDAR sensor systems for autonomous safe landing on planetary bodies
Future NASA exploratory missions to the Moon and Mars will require safe soft landings at the designated sites with a high degree of precision. These sites may include areas of high scientific value with relatively rough terrain with little or no solar illumination and possibly areas near pre deployed assets. The ability of lidar technology to provide three dimensional elevation maps of the terrain, high precision distance to the ground, and approach velocity can enable safe landing of large robotic and manned vehicles with a high degree of precision. Currently, NASA LaRC is developing novel lidar sensors aimed at meeting NASA's objectives for future planetary landing missions under the Autonomous Landing and Hazard Avoidance (ALHAT) project. These lidar sensors are 3 Dimensional Imaging Flash Lidar, Doppler Lidar, and Laser Altimeter. The Flash Lidar is capable of generating elevation maps of the terrain identifying hazardous features such as rocks, craters, and steep slopes. The elevation maps collected during the approach phase between 1000 m to 500 m above the ground can be used to determine the most suitable safe landing site. The Doppler Lidar provides highly accurate ground velocity and distance data allowing for precision navigation to the selected landing site. Prior to the approach phase at altitudes of over 15 km, the Laser Altimeter can provide sufficient data for updating the vehicle position and attitude data from the Inertial Measurement Unit. At these higher altitudes, either the Laser Altimeter or the Flash Lidar can be used for generating a contour map of the terrain below for identifying known surface features such as craters for further reducing the vehicle relative position error.
International Conference on Space Optics
Farzin Amzajerdian Diego Pierrottet Larry B Petway Michael Vanek
49563290
Querying across time to interactively evolve animations
Compositional Pattern Producing Networks (CPPNs) are a generative encoding that has been used to evolve a variety of novel artifacts, such as 2D images, 3D shapes, audio timbres, soft robots, and neural networks. This paper takes systems that generate static 2D images and 3D shapes with CPPNs and introduces a time input, allowing each CPPN to produce a different set of results for each slice of time. Displaying the results in sequence creates smooth animations that can be interactively evolved to suit users' personal aesthetic preferences. A human subject study involving 40 individuals was conducted to demonstrate that people find the dynamic animations more complex than static outputs, and find interactive evolution of animations more enjoyable than evolution of static outputs. The novel idea of indirectly generating artifacts as a function of time could also be useful in other domains.
GECCO
Isabel Tweraser Lauren E Gillespie Jacob Schrum
3440327
Human in the Loop Mixed Initiative Control Under Temporal Tasks
This paper considers the motion control and task planning problem of mobile robots under complex high level tasks and human initiatives. The assigned task is specified as Linear Temporal Logic (LTL) formulas that consist of hard and soft constraints. The human initiative influences the robot autonomy in two explicit ways: with additive terms in the continuous controller and with contingent task assignments. We propose an online coordination scheme that encapsulates (i) a mixed initiative continuous controller that ensures all time safety despite of possible human errors, (ii) a plan adaptation scheme that accommodates new features discovered in the workspace and short term tasks assigned by the operator during run time, and (iii) an iterative inverse reinforcement learning (IRL) algorithm that allows the robot to asymptotically learn the human preference on the parameters during the plan synthesis. The results are demonstrated by both realistic human in the loop simulations and experiments.
2018 IEEE International Conference on Robotics and Automation (ICRA)
Meng Guo Sofie Andersson Dimos V Dimarogonas
49564248
Fusing novelty and surprise for evolving robot morphologies
Traditional evolutionary algorithms tend to converge to a single good solution, which can limit their chance of discovering more diverse and creative outcomes. Divergent search, on the other hand, aims to counter convergence to local optima by avoiding selection pressure towards the objective. Forms of divergent search such as novelty or surprise search have proven to be beneficial for both the efficiency and the variety of the solutions obtained in deceptive tasks. Importantly for this paper, early results in maze navigation have shown that combining novelty and surprise search yields an even more effective search strategy due to their orthogonal nature. Motivated by the largely unexplored potential of coupling novelty and surprise as a search strategy, in this paper we investigate how fusing the two can affect the evolution of soft robot morphologies. We test the capacity of the combined search strategy against objective, novelty, and surprise search, by comparing their efficiency and robustness, and the variety of robots they evolve. Our key results demonstrate that novelty surprise search is generally more efficient and robust across eight different resolutions. Further, surprise search explores the space of robot morphologies more broadly than any other algorithm examined.
GECCO
Daniele Gravina Antonios Liapis Georgios N Yannakakis
53100000
Granular Jamming Based Controllable Organ Design for Abdominal Palpation
Medical manikins play an essential role in the training process of physicians. Currently, most available simulators for abdominal palpation training do not contain controllable organs for dynamic simulations. In this paper, we present a soft robotics controllable liver that can simulate various liver diseases and symptoms for effective and realistic palpation training. The tumors in the liver model are designed based on granular jamming with positive pressure, which converts the fluid like impalpable particles to a solid like tumor state by applying low positive pressure on the membrane. Through inflation, the tumor size, liver stiffness, and liver size can be controlled from normal liver state to various abnormalities including enlarged liver, cirrhotic liver, and multiple cancerous and malignant tumors. Mechanical tests have been conducted in the study to evaluate the liver design and the role of positive pressure granular jamming in tumor simulations.
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Liang He Nicolas Herzig Simon de Lusignan Thrishantha Nanayakkara