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An Adaptive Landing Gear for Extending the Operational Range of Helicopters

Authors: Stolz, B.; Brödermann, T.; Castiello, E.; Englberger, G.; Erne, D.; Gasser, J.; Hayoz, E.; Müller, S.; Muhlebach, L.; Löw, T.; Scheuer, D.; Vandeventer, L.; Bjelonic, M.; Günther, F.; Kolvenbach, H.; Hopflinger, M.; Hutter, M.

 

Conventional skid or wheel based helicopter landing gears severely limit off-field landing possibilities, which are crucial when operating in scenarios such as mountain rescue. In this context, slopes beyond 8° and small obstacles can already pose a substantial hazard. An adaptive landing gear is proposed to overcome these limitations. It consists of four legs with one degree of freedom each. The total weight was minimized to demonstrate economic practicability. This was achieved by an innovative actuation, composed of a parallel arrangement of motor and brake, which relieves the motor from large impact loads during hard landings. The loads are alleviated by a spring-damper system acting in series to the actuation. Each leg is individually force controlled for optimal load distribution on compliant ground and to avoid tipping. The operation of the legs is fully autonomous during the landing phase. A prototype was designed and successfully tested on an unmanned helicopter with a maximum take-off weight of 78 kg. Finally, the implementation of the landing gear concept on aircraft of various scales was discussed.

Reference

Posted on: April 8, 2019

Aerial-Ground collaborative sensing: Third-Person view for teleoperation

Authors: Gawel, A.; Lin, Y.; Koutros, T.; Siegwart, R.; Cadena, C.

 

Rapid deployment and operation are key requirements in time critical application, such as Search and Rescue (SaR). Efficiently teleoperated ground robots can support first-responders in such situations. However, first-person view teleoperation is sub-optimal in difficult terrains, while a third-person perspective can drastically increase teleoperation performance. Here, we propose a Micro Aerial Vehicle (MAV)-based system that can autonomously provide third-person perspective to ground robots. While our approach is based on local visual servoing, it further leverages the global localization of several ground robots to seamlessly transfer between these ground robots in GPS-denied environments. Therewith one MAV can support multiple ground robots on a demand basis. Furthermore, our system enables different visual detection regimes, and enhanced operability, and return-home functionality. We evaluate our system in real-world SaR scenarios.

Reference

Posted on: April 8, 2019

Advantages of soft subdural implants for the delivery of electrochemical neuromodulation therapies to the spinal cord

Authors: Capogrosso, M.; Gandar, J.; Greiner, N.; Moraud, E. M.; Wenger, N.; Shkorbatova, P.; Musienko, P.; Minev, I.; Lacour, S.; Courtine, C.

 

  • Journal of Neural Engineering, vol. 15, no. 2, pp. 026024, Feb. 2018
Objective. We recently developed soft neural interfaces enabling the delivery of electrical and chemical stimulation to the spinal cord. These stimulations restored locomotion in animal models of paralysis. Soft interfaces can be placed either below or above the dura mater. Theoretically, the subdural location combines many advantages, including increased selectivity of electrical stimulation, lower stimulation thresholds, and targeted chemical stimulation through local drug delivery. However, these advantages have not been documented, nor have their functional impact been studied in silico or in a relevant animal model of neurological disorders using a multimodal neural interface. Approach. We characterized the recruitment properties of subdural interfaces using a realistic computational model of the rat spinal cord that included explicit representation of the spinal roots. We then validated and complemented computer simulations with electrophysiological experiments in rats. We additionally performed behavioral experiments in rats that received a lateral spinal cord hemisection and were implanted with a soft interface. Main results. In silico and in vivo experiments showed that the subdural location decreased stimulation thresholds compared to the epidural location while retaining high specificity. This feature reduces power consumption and risks of long-term damage in the tissues, thus increasing the clinical safety profile of this approach. The hemisection induced a transient paralysis of the leg ipsilateral to the injury. During this period, the delivery of electrical stimulation restricted to the injured side combined with local chemical modulation enabled coordinated locomotor movements of the paralyzed leg without affecting the non-impaired leg in all tested rats. Electrode properties remained stable over time, while anatomical examinations revealed excellent bio-integration properties. Significance. Soft neural interfaces inserted subdurally provide the opportunity to deliver electrical and chemical neuromodulation therapies using a single, bio-compatible and mechanically compliant device that effectively alleviates locomotor deficits after spinal cord injury.

Reference

Posted on: April 8, 2019

Active stabilization of a stiff quadruped robot using local feedback

Authors: Vasconcelos, R.; Hauser, S.; Dzeladini, F.; Mutlu, M.; Horvat, T.; Melo, K.; Oliveira, P.; Ijspeert, A.

 

  • 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Animal locomotion exhibits all the features of complex non linear systems such as multi-stability, critical fluctuation, limit cycle behavior and chaos. Studying these aspects on real robots has been proved difficult and therefore results mostly rely on the use of computer simulation. Simple control approaches – based on phase oscillators – have been proposed and exhibit several of these features. In this work, we compare two types of controllers: (a) an open loop control approach based on phase oscillators and (b) the Tegotae-based closed loop extension of this controller. The first controller has been shown to exhibit synchronization features between the body and the controller when applied to a quadruped robot with compliant leg structures. In this contribution, we apply both controllers to the locomotion of a stiff quadruped structure. We show that the Tegotae-controller exhibits self-organizing behavior, such as spontaneous gait transition and critical fluctuation. Moreover, it exhibits features such as the ability to stabilize both asymmetric and symmetric morphological changes, despite the lack of compliance in the leg.

Reference

Posted on: April 8, 2019

A wireless brain-spine interface alleviating gait deficits after Parkinson’s disease in primates

Authors: Milekovic, T.; Raschella, F.; Schiavone, G.; Capogrosso, M.; Micera, S.; Courtine, G.; Lacour, S.

 

  • Lemanic Neuroscience Annual Meeting
“Levodopa and deep brain stimulation alleviate most of the symptoms associated with Parkinson*s disease. However, axial gait disorders are less responsive to these treatments. These deficits include short and slow steps, balance deficits and freezing of gait that involves episodes during which the affected persons are not capable of initiating locomotion.
Over the past decade, we have established a mechanistic and technological framework that guided the design of electrical spinal cord stimulation protocols engaging extensor and flexor muscle groups. We created an interface between the leg motor cortex activity and these spatially selective stimulation protocols, so as to engineer a brain*spine interface * a neuroprosthetic system that reinforced intended movements. As early as 6 days after spinal cord injury, this brain*spine interface restored weight-bearing locomotor movements of the paralyzed leg in nonhuman primates. Here, we show that the brain- spine interface effectively alleviates axial gait deficits observed in Parkinson*s disease. These experiments were conducted in MPTP-treated Rhesus macaque monkeys, which is the gold model to reproduce Parkinson*s disease symptomatology. After MPTP treatment, a rhesus macaque was implanted with the wireless brain-spine interface. Brain recordings of the left and right leg motor cortex were used to detect neural states related to flexion and extension movements of both legs while the animal walked freely overground or over a horizontal ladder. The detection of these gait events controlled an implanted pulse generator that delivered electrical stimulation through two e-dura electrode array implants that covered the dorsal aspects of the lumbar and sacral spinal cord.”

Reference

  • Date: 2017
Posted on: April 8, 2019

A Scalable and Consistent TSDF-based Dense Mapping Approach

Authors: Millane, A.; Taylor, Z.; Oleynikova, H.; Nieto, J.; Siegwart, R.; Cadena, C.

 

In many applications, maintaining a consistent dense map of the environment is key to enabling robotic platforms to perform higher level decision making. Several works have addressed the challenge of creating precise dense 3D maps. However, during operation over longer missions, reconstructions can easily become inconsistent due to accumulated camera tracking error and delayed loop closure. Without explicitly addressing the problem of map consistency, recovery from such distortions tends to be difficult. We present a novel system for dense 3D mapping which addresses the challenge of building consistent maps while dealing with scalability. Central to our approach is the representation of the environment as a collection of overlapping TSDF subvolumes. These subvolumes are localized through feature-based camera tracking and bundle adjustment. Our main contribution is a pipeline for identifying stable regions in the map, and to fuse the contributing subvolumes. This approach allows us to reduce map growth while still maintaining consistency. We demonstrate the proposed system on a publicly available dataset and simulation engine, and demonstrate the efficacy of the proposed approach for building consistent and scalable maps. Finally we demonstrate our approach running in real-time on-board a lightweight MAV.

Reference

Posted on: April 8, 2019

A multidirectional gravity-assist algorithm that enhances locomotor control in patients with stroke or spinal cord injury

Authors: Mignardot, J-M.; Le Goff, C. G.; van den Brand, R.; Capogrosso, M.;  Fumeaux, N.; Vallery, H.; Anil, S.; Lanini, J.; Fodor, I.; Eberle, G.; Ijspeert, A.; Schurch, B.; Curt, A.; Carda, S.; Bloch, J.; von Zitzewitz, J.; Courtine, G.

 

  • Science Translational Medicine, 9, 399, pp. eaah3621
Gait recovery after neurological disorders requires remastering the interplay between body mechanics and gravitational forces. Despite the importance of gravity-dependent gait interactions and active participation for promoting this learning, these essential components of gait rehabilitation have received comparatively little attention. To address these issues, we developed an adaptive algorithm that personalizes multidirectional forces applied to the trunk based on patient-specific motor deficits. Implementation of this algorithm in a robotic interface reestablished gait dynamics during highly participative locomotion within a large and safe environment. This multidirectional gravity-assist enabled natural walking in nonambulatory individuals with spinal cord injury or stroke and enhanced skilled locomotor control in the less-impaired subjects. A 1-hour training session with multidirectional gravity-assist improved locomotor performance tested without robotic assistance immediately after training, whereas walking the same distance on a treadmill did not ameliorate gait. These results highlight the importance of precise trunk support to deliver gait rehabilitation protocols and establish a practical framework to apply these concepts in clinical routine.

Reference

Posted on: April 8, 2019

A Modular Low-Complexity ECG Delineation Algorithm for Real-Time Embedded Systems

Authors: Bote, J. M.; Recas, J.; Rincon, F.; Atienza, D.; Hermida, R.

 

  • IEEE Journal of Biomedical and Health Informatics, 22(2), pp. 429-441
This work presents a new modular and low-complexity algorithm for the delineation of the different ECG waves (QRS, P and T peaks, onsets, and end). Involving a reduced number of operations per second and having a small memory footprint, this algorithm is intended to perform real-time delineation on resource-constrained embedded systems. The modular design allows the algorithm to automatically adjust the delineation quality in runtime to a wide range of modes and sampling rates, from a ultralow-power mode when no arrhythmia is detected, in which the ECG is sampled at low frequency, to a complete high-accuracy delineation mode, in which the ECG is sampled at high frequency and all the ECG fiducial points are detected, in the case of arrhythmia. The delineation algorithm has been adjusted using the QT database, providing very high sensitivity and positive predictivity, and validated with the MIT database. The errors in the delineation of all the fiducial points are below the tolerances given by the Common Standards for Electrocardiography Committee in the high-accuracy mode, except for the P wave onset, for which the algorithm is above the agreed tolerances by only a fraction of the sample duration. The computational load for the ultralow-power 8-MHz TI MSP430 series microcontroller ranges from 0.2% to 8.5% according to the mode used.

Reference

Posted on: April 8, 2019

A model of artificial emotions for behavior-modulation and implicit coordination in multi-robot systems

Authors: Guzzi, J.; Giusti, A.; Gambardella, L. M.; Di Caro, G. A.

 

  • Proceedings of the Genetic and Evolutionary Computation Conference on – GECCO ’18
We propose a model of artificial emotions for adaptation and implicit coordination in multi-robot systems. Artificial emotions play two roles, which resemble their function in animals and humans: modulators of individual behavior, and means of communication for social coordination. Emotions are modeled as compressed representations of the internal state, and are subject to a dynamics depending on internal and external conditions. Being a compressed representation, they can be efficiently exposed to nearby robots, allowing to achieve local group-level communication. The model is instantiated for a navigation task, with the aim of showing how coordination can effectively emerge by adding artificial emotions on top of an existing navigation framework. We show the positive effects of emotion-mediated group behaviors in a few challenging scenarios that would otherwise require ad hoc strategies: preventing deadlocks in crowded conditions; enabling efficient navigation of agents with time-critical tasks; assisting robots with faulty sensors. Two performance measures, throughput and number of collisions, are used to quantify the contribution of emotions for modulation and coordination.

Reference

Posted on: April 8, 2019

3D Registration of Aerial and Ground Robots for Disaster Response: An Evaluation of Features, Descriptors, and Transformation Estimation

Authors: Gawel, A.; Dubé, R.; Surmann, H.; Nieto, J.; Siegwart, R.; Cadena, C.

 

  • IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)
Global registration of heterogeneous ground and aerial mapping data is a challenging task. This is especially difficult in disaster response scenarios when we have no prior information on the environment and cannot assume the regular order of man-made environments or meaningful semantic cues. In this work we extensively evaluate different approaches to globally register UGV generated 3D point-cloud data from LiDAR sensors with UAV generated point-cloud maps from vision sensors. The approaches are realizations of different selections for: a) local features: key-points or segments; b) descriptors: FPFH, SHOT, or ESF; and c) transformation estimations: RANSAC or FGR. Additionally, we compare the results against standard approaches like applying ICP after a good prior transformation has been given. The evaluation criteria include the distance which a UGV needs to travel to successfully localize, the registration error, and the computational cost. In this context, we report our findings on effectively performing the task on two new Search and Rescue datasets. Our results have the potential to help the community take informed decisions when registering point-cloud maps from ground robots to those from aerial robots.

Reference

Posted on: April 8, 2019