ETH Zurich Algorithm Recovers Quadcopters After Midair Propeller Loss

Quadrocopter failsafe algorithm: recovery after propeller loss — Mark Mueller

Mark Mueller

Software that stabilizes damaged drones via a controlled spin eliminates the need for heavy multi-motor hardware redundancy.

AI-assisted summary of Quadrocopter failsafe algorithm: recovery after propeller loss — original source. Check the original for full context.

Source published:

Key ideas

  • ETH Zurich researchers have demonstrated an autonomous failsafe algorithm that allows a quadrocopter to maintain controlled flight and safely recover after losing a propeller mid-flight. (0:00)
  • Upon detecting propeller detachment, the quadrocopter automatically enters a rapid, controlled spin around its primary axis to compensate for asymmetric thrust and returns to hover at its original position. (0:00)
  • The failsafe operates purely as a software upgrade on standard, off-the-shelf quadrocopter hardware, avoiding the weight and payload penalties of physical redundancy like hexacopters or octocopters. (0:00)
  • The degraded vehicle remains fully controllable throughout the spin state and executes a soft, controlled landing upon operator command. (0:00)

Detailed notes

## Background Published on YouTube by Mark Mueller on December 2, 2013, this video presents robotics research conducted with Raffaello D'Andrea at the Institute for Dynamic Systems and Control (IDSC) at ETH Zurich. The video demonstrates an autonomous failsafe algorithm that allows a standard quadrocopter to survive the loss of a propeller mid-flight and perform a controlled landing without extra redundant hardware.

## TL;DR Inside ETH Zurich's Flying Machine Arena, a quadrocopter hovers with an unbolted propeller that intentionally vibrates loose and detaches mid-air. Rather than tumbling out of control, the drone's autonomous estimation and control system instantly identifies the failure and initiates a rapid, controlled spin around its primary axis to counter asymmetric thrust. The aircraft stabilizes itself, regains its initial hover coordinates, and maintains full maneuverability until executing a smooth, operator-commanded soft landing. This software-only solution allows standard quadcopters to achieve failsafe recovery in safety-critical applications without the payload and weight penalties of adding extra motors.

## Atmosphere & style The presentation is tense and dramatic, heightened by a suspenseful musical score that builds anticipation as the loose rotor blade begins to shake. What initially appears headed for an inevitable catastrophic crash transforms into a mesmerizing display of dynamic control as the vehicle seamlessly transitions into a high-speed stabilization spin. The demonstration feels remarkably focused and high-tech, evoking quiet awe as the violently spinning craft remains steady and gently touches down with complete precision.

## Bulletin - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) ETH Zurich researchers have demonstrated an autonomous failsafe algorithm that allows a quadrocopter to maintain controlled flight and safely recover after losing a propeller mid-flight. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) Upon detecting propeller detachment, the quadrocopter automatically enters a rapid, controlled spin around its primary axis to compensate for asymmetric thrust and returns to hover at its original position. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) The failsafe operates purely as a software upgrade on standard, off-the-shelf quadrocopter hardware, avoiding the weight and payload penalties of physical redundancy like hexacopters or octocopters. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) The degraded vehicle remains fully controllable throughout the spin state and executes a soft, controlled landing upon operator command.

## Key takeaways - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) Catastrophic propeller loss in conventional quadrotors immediately breaks thrust and torque balance, typically resulting in an unrecoverable crash. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) The experiment intentionally induced rotor separation mid-flight by mounting a propeller without a retaining nut, relying on operational vibration to shake it free. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) Onboard estimation and control systems autonomously detect the mechanical failure in real time without human intervention. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) To counter the lost thrust vector, the recovery algorithm initiates a controlled high-speed spin around the vehicle's primary axis. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) While spinning, the vehicle actively stabilizes its altitude and successfully maneuvers back to its original coordinate setpoint. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) The quadrocopter maintains stable degraded flight until receiving a user command, at which point it executes a gentle, controlled touchdown. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) Historically, surviving a motor or propeller failure required hardware redundancy through six- or eight-rotor configurations. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) Hardware redundancy adds substantial structural mass, reducing a multicopter's energy efficiency and usable payload capacity. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) Because the failsafe relies exclusively on standard sensors and motors, it can be deployed as an algorithmic-only upgrade to existing quadrocopters. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) This algorithmic fault tolerance allows quadrocopters to be considered for safety-critical missions where payload efficiency is paramount. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) The underlying spinning control dynamics offer a conceptual blueprint for designing novel vehicle configurations with fewer active actuators. - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) The project was developed by Mark W. Mueller and Raffaello D'Andrea at the ETH Zurich Flying Machine Arena with support from the Swiss National Science Foundation.

## Detailed walkthrough ### [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) Quadrocopter Propeller Loss and Autonomous Failsafe Recovery

The demonstration from the Institute for Dynamic Systems and Control (IDSC) at ETH Zurich's Flying Machine Arena showcases an automated failsafe control algorithm designed to recover a quadrocopter after catastrophic propeller loss. Set against a dramatic, tense musical backdrop, the experiment illustrates a scenario where a quadrocopter rotor blade is deliberately installed without a retaining nut, allowing normal operational vibrations to shake the propeller loose mid-flight. When the blade flies off, conventional quadrotors would immediately lose attitude control and crash due to the sudden loss of torque balance and thrust symmetry.

Instead of crashing, the vehicle's onboard estimation and control system autonomously senses the failure in real time. Upon detecting the lost propeller, the failsafe algorithm takes over: the quadrocopter enters a rapid, controlled spin around its primary axis to compensate for the asymmetric thrust, stabilizes its altitude and orientation, and maneuvers back to its original hover coordinates. The vehicle remains fully controllable in this degraded state until receiving an operator command to execute a smooth, controlled soft landing.

Historically, multirotor aircraft required physical hardware redundancy—such as upgrading to hexacopter or octocopter configurations—to survive the loss of a motor or propeller. The researchers demonstrate that this capability can be achieved purely through control software on existing, off-the-shelf quadrocopter hardware, preserving payload capacity and structural efficiency without the penalty of extra motors and structural weight.

```mermaid flowchart TD accTitle: Quadrocopter Failsafe Recovery Architecture accDescr: Sequence diagram showing propeller detachment, automated detection, recovery spin, and soft landing. subgraph S1["Nominal Flight"] A["Normal Quadrocopter Hover"] --> B["Propeller Vibrates Loose"] end subgraph S2["Failsafe Algorithm"] B --> C["Automatic Failure Detection"] C --> D["Controlled High-Speed Spin"] D --> E["Position Recovery & Stable Hover"] end subgraph S3["Landing Phase"] E --> F["Operator Landing Command"] F --> G["Controlled Soft Touchdown"] end ```

- **Institution and Location**: Institute for Dynamic Systems and Control (IDSC), ETH Zurich, tested inside the Flying Machine Arena. - **Key Researchers**: Mark W. Mueller and Raffaello D'Andrea. - **Hardware Footprint**: Implemented as a pure software upgrade utilizing standard onboard sensors and motors without additional actuators or mechanical redundancy. - **Operational Payoff**: Enables four-rotor vehicles to be deployed in safety-critical operations while retaining optimal payload capacity compared to heavier hexacopters or octocopters. - **Project Support**: Backed by the Swiss National Science Foundation (SNSF) with patent-pending technology.

## Mentioned ETH Zurich, Flying Machine Arena, Institute for Dynamic Systems and Control (IDSC), Mark W. Mueller, Markus Waibel, Max Kriegleder, Raffaello D'Andrea, Swiss National Science Foundation (SNSF)

## Video description Quadrocopter failsafe algorithm -- Institute for Dynamic Systems and Control (IDSC), ETH Zurich, Switzerland - http://www.idsc.ethz.ch/

== UPDATE == Please see this video (http://youtu.be/ek0FrCaogcs) for a demonstration of the flight algorithm without the motion capture system.

The video shows an automatic failsafe algorithm that allows a quadrocopter to gracefully cope with the loss of a propeller. The propeller was mounted without a nut, and thus eventually vibrates itself loose.

The failure is detected automatically by the system, after which the vehicle recovers and returns to its original position. The vehicle finally executes a controlled, soft landing, on a user's command.

The failsafe controller uses only hardware that is readily available on a standard quadrocopter, and could thus be implemented as an algorithmic-only upgrade to existing systems. Until now, the only way a multicopter could survive the loss of a propeller (or motor), is by having redundancy (e.g. hexacopters, octocopters). However, this redundancy comes at the cost of additional structural weight, reducing the vehicle's useful payload. Using this technology, (more efficient) quadrocopters can be used in safety critical applications, because they still have the ability to gracefully recover from a motor/propeller failure.

This control approach can also be applied to design novel flying vehicles, the results of which will be posted soon.

This technology is patent pending.

For more information, please see www.FlyingMachineArena.org

Researchers: Mark W. Mueller and Raffaello D'Andrea

Video: Mark W. Mueller, Markus Waibel, Max Kriegleder, and Raffaello D'Andrea

Location: Flying Machine Arena at ETH Zurich

Acknowledgements This work is supported by and builds upon prior contributions by numerous collaborators in the Flying Machine Arena project. See http://www.flyingmachinearena.org/people . This work was supported by the SNSF (Swiss National Science Foundation).

[Source](https://www.youtube.com/watch?v=bsHryqnvyYA)

中文简报

苏黎世联邦理工学院算法助四旋翼无人机在空中断桨后自主恢复 通过受控旋转稳定受损无人机的软件方案，消除了对笨重多电机硬件冗余的需求。 在苏黎世联邦理工学院的飞行机器竞技场内，一架四旋翼无人机在空中悬停，其未拧紧的螺旋桨故意振动松脱并在半空中脱落。这架无人机并未失控翻滚，其自主估计与控制系统瞬间识别出故障，并启动绕主轴的快速受控旋转以抵消不对称推力。飞行器随即自行稳定，重新回到初始悬停坐标，并保持完整的机动性，直到按照操作员的指令平稳软着陆。这种纯软件解决方案使标准四旋翼无人机能够在安全关键应用中实现故障安全恢复，而无需承受增设额外电机带来的载荷与重量损失。 苏黎世联邦理工学院的研究人员展示了一种自主故障安全算法，使四旋翼无人机在飞行中断桨后仍能保持受控飞行并安全恢复。 (0:00) 在检测到螺旋桨脱落后，四旋翼无人机会自动进入绕其主轴的快速受控自旋，以补偿不对称推力，并返回初始位置悬停。 (0:00) 该故障安全机制纯粹作为标准现成四旋翼无人机硬件上的软件升级运行，避免了六旋翼或八旋翼等物理冗余带来的重量和有效载荷损失。 (0:00) 受损飞行器在整个自旋状态下依然完全可控，并在操作员发出指令后执行平稳的受控着陆。 (0:00)

Reading summary

Researchers at ETH Zurich's Institute for Dynamic Systems and Control have demonstrated an automated failsafe algorithm that allows a quadrocopter to survive mid-flight propeller loss and land safely using software control alone. Autonomous Detection and Rapid Spin Stabilization (0:00) When a rotor blade detaches during flight, standard quadrotors instantly lose attitude control and crash due to the abrupt imbalance in thrust and torque. In the demonstrated test, an unsecured propeller vibrates loose mid-air, prompting the onboard estimation and control system to detect the failure automatically in real time. Rather than failing, the quadrocopter executes a rapid, controlled spin around its primary axis. This motion balances the asymmetric forces, allowing the vehicle to re-stabilize its altitude and orientation, maneuver back to its initial hover coordinates, and perform a controlled soft landing upon operator command. Software Resilience Over Mechanical Redundancy (0:00) Traditionally, achieving fault tolerance against motor or propeller failure required upgrading to multirotor platforms with hardware redundancy, such as hexacopters or octocopters. These additional rotors and structural components introduce weight penalties that reduce operational payload capacity. The demonstration shows that resilience can be achieved on standard, off-the-shelf four-rotor hardware entirely through control software. By eliminating the need for extra mechanical actuators, the approach maintains structural efficiency and full payload potential for safety-critical applications. Developed by Mark W. Mueller and Raffaello D'Andrea and supported by the Swiss National Science Foundation, the patent-pending system proves that four-rotor craft can achieve fault tolerance without physical redundancy, though demonstrations were conducted within the controlled environment of ETH Zurich's Flying Machine Arena.

精炼阅读摘要

苏黎世联邦理工学院（ETH Zurich）研究团队展示了一种故障自愈控制算法，使四旋翼无人机在飞行中发生螺旋桨脱落后，无需依赖额外机械冗余即可通过受控高速自旋维持稳定悬停并安全着陆。 突发失桨后的实时自旋平衡机制 (0:00) 在苏黎世联邦理工学院飞行机动竞技场（Flying Machine Arena）的试验中，测试人员特意未安装固定螺母，使四旋翼在飞行震动中突发单桨脱落。在常规控制下，推力不对称和扭矩失衡会迅速导致机体失控坠毁；而该系统的机载算法能实时感知故障，并在失桨瞬间切换至应急模式，通过驱动机身绕主轴受控高速自旋来抵消推力不对称，从而稳定姿态与飞行高度，并自主调整回原悬停坐标。 以纯软件算法替代传统硬件冗余 (0:00) 多旋翼飞行器以往通常依赖增加旋翼数量（如升级为六旋翼或八旋翼构型）来实现动力失效冗余，但这会增加电机和机身自重，进而缩减有效载荷能力。研究人员证明，仅依靠标准现成四旋翼硬件和现有板载传感器，通过控制算法即可在降级状态下保持可控飞行，直至接收操作员指令平稳软着陆，避免了额外电机与机械结构带来的重量负担。 研发背景与安全关键场景应用 (0:00) 该项目由 Mark W. Mueller 与 Raffaello D'Andrea 主导研发，获得了瑞士国家科学基金会（SNSF）的资助，相关技术目前处于专利申请阶段。该算法保留了四旋翼原有的载荷效率和结构简易度，为四旋翼无人机投入高标准的安全关键型作业提供了可行的容错控制方案。 该研究证实了纯软件控制能够替代传统的动力硬件备份，为四旋翼无人机在遭遇突发机械损坏时的抗坠毁能力与安全回收提供了工程范式。

Detailed notes — zh

## Background 该视频由研究人员 Mark Mueller 于 2013 年 12 月 2 日发布在 YouTube 平台上。视频简介指出，这是瑞士苏黎世联邦理工学院动力系统与控制研究所（ETH Zurich IDSC）的一项研究成果，展示了一种能够在四旋翼无人机意外脱落一个螺旋桨后自动接管、维持姿态并实现受控软着陆的安全故障保护（failsafe）算法。 ## TL;DR 视频记录了在飞行机器竞技场内进行的一场四旋翼飞行器动力失效自愈实验。测试中一个未装螺母的螺旋桨因震动在空中飞脱，机载系统自动检测到推力失效并迅速切入应急控制模式。通过利用剩余三个螺旋桨驱动机身高速自旋以合成反重力推力，无人机不仅遏制了坠落并成功返回原位悬停，最终还在操作员指令下平稳完成受控软着陆。该算法完全基于标准四旋翼硬件实现，打破了以往多旋翼必须依赖六轴或八轴等机械冗余才能应对断桨的局限。 ## Atmosphere & style 整段视频没有人工解说旁白，仅在背景音乐的烘托下客观记录实验全过程，呈现出严谨、克制且高度专注的科研记录风格。从螺旋桨骤然飞脱的瞬间惊险，到机身在高速自旋中奇迹般稳住姿态、自主复位并轻柔触地，观看体验充满了硬核工程技术带来的从容感与视觉震撼。 ## Bulletin - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 苏黎世联邦理工学院动力系统与控制研究所（ETH Zurich IDSC）研发出新型四旋翼故障安全算法，使无人机在空中丢失单个螺旋桨后仍能维持稳定飞行与受控着陆。 - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 该算法无需任何额外传感器或机械硬件冗余，仅凭标准四旋翼无人机现有硬件进行纯软件算法升级即可实现自救生还。 - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 相较于依赖六旋翼或八旋翼等硬件冗余方案，该项技术避免了机身增重和有效载荷削减，大幅提升了安全严苛型应用场景的运行效率。 - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 脱桨故障发生后，机载系统可全自动检测失效状态，通过控制机身进入受控高速自旋重构推力矢量，并能响应操作员指令实现软着陆。 ## Key takeaways - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 实验在 ETH Zurich 的飞行机器竞技场（Flying Machine Arena）进行，由 Mark W. Mueller 和 Raffaello D'Andrea 共同主持开发。 - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 实验中特意不安装螺旋桨固定螺母，使单侧螺旋桨在飞行过程中因震动自然松脱，用于验证无硬件外力干预下的纯自主故障识别。 - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 螺旋桨脱落瞬间四轴平衡被打破，控制算法自动在瞬间识别动力失效并无缝切换至应急控制模式。 - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 应急算法驱动无人机围绕特定轴线进入高速自旋状态，通过动态协调剩余三个电机的推力输出以抵消不平衡力矩。 - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 通过高速旋转合成朝向重力反方向的平均推力矢量，无人机不仅遏制了失速下坠，还自主返回到脱桨前的原空间坐标悬停。 - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 在保持稳定自旋的状态下，无人机接收地面操作员发出的降落指令，完成了平稳且可控的轻柔软着陆。 - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 传统多旋翼抵御动力失效通常依赖六旋翼或八旋翼构型，但物理冗余会带来结构增重和有效载荷压缩的缺点。 - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 该技术证明了标准四旋翼仅需算法层面的更新即可获得等同甚至超越硬件冗余的抗失效容错能力。 - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 该算法突破为物流配送、工业巡检等对安全性要求极高的四旋翼应用场景提供了关键的安全兜底保障。 - [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 此项自适应控制技术已提交专利申请（Patent Pending），并由瑞士国家科学基金会（SNSF）资助支持。 ## Detailed walkthrough ### [00:00](https://www.youtube.com/watch?v=bsHryqnvyYA&t=0s) 四旋翼无人机脱桨故障应急算法与受控降落演示 本段视频记录了瑞士苏黎世联邦理工学院动力系统与控制研究所（IDSC, ETH Zurich）在飞行机器竞技场（Flying Machine Arena）进行的一项自主安全故障保护（failsafe）控制算法实验。该项技术由研究人员马克·W·穆勒（Mark W. Mueller）与拉斐尔·安德烈亚（Raffaello D'Andrea）共同开发。视频本身并未包含人声解说旁白，而是伴随背景音乐完整呈现了四旋翼飞行器在空中遭遇单侧螺旋桨脱落后的自愈响应过程。在实验设计中，研究团队特意未为其中一个螺旋桨安装紧固螺母，飞行器起飞并在空中平稳飞行一段时间后，该螺旋桨因剧烈震动而自行松脱飞离。 在螺旋桨脱落瞬间，四旋翼无人机常规的四轴推力与反扭矩力矩平衡被瞬间打破。机载控制系统依靠内置算法在瞬间自动检测到动力失效故障，并立即切换至应急控制模式。失去一个螺旋桨的飞行器迅速进入高速自旋状态，通过动态协调剩余三个电机的推力矢量输出，将旋转产生的综合平均推力精准指向重力反方向，不仅防止了灾难性的失速坠毁，还平稳制止了下坠，重新爬升并自主返回到脱桨前的空间原始位置进行悬停。随后，在操作人员发出降落指令后，飞行器继续保持自旋并执行了平稳受控的轻柔软着陆。 传统多旋翼无人机若要抵御电机或螺旋桨停转失效，通常必须依赖硬件冗余设计（例如采用六旋翼或八旋翼构型）。然而，增加额外的机臂与电机结构不仅会显著增加机身自重，还会压缩有效载荷空间并降低系统运行效率。该项故障应急控制算法的突破之处在于其完全依赖标准四旋翼无人机既有的机载硬件，无需加装任何额外传感器或机械冗余组件，纯粹依靠算法升级即可使无人机具备在关键动力受损时的自救生还能力，对安全严苛型应用场景（如物流运输、高空巡检及人群上方飞行等）具有重大工程实用价值。 ```mermaid flowchart TD accTitle: 四旋翼脱桨应急控制算法响应流程 accDescr: 展示四旋翼飞行器在螺旋桨松脱后从故障检测、自旋姿态恢复、定点复位到最终软着陆的处理机制。 subgraph S1["故障发生与检测"] A["未固定螺母的螺旋桨震动脱落"] --> B["算法自动检测到单轴推力失效"] end subgraph S2["姿态重构与定位"] B --> C["切换应急控制：利用剩余三桨高速自旋"] C --> D["合成稳定反重力推力矢量并消除位移"] D --> E["自主返回故障发生前原始空间坐标悬停"] end subgraph S3["指令着陆"] E --> F["接收操作员着陆指令"] F --> G["保持自旋稳定下降并执行轻柔软着陆"] end ``` - **研究机构与地点**：瑞士苏黎世联邦理工学院动力系统与控制研究所（ETH Zurich IDSC），实验于飞行机器竞技场（Flying Machine Arena）内完成。 - **研究人员与支持单位**：由 Mark W. Mueller 与 Raffaello D'Andrea 研发，视频制作包括 Markus Waibel 及 Max Kriegleder，该研究项目由瑞士国家科学基金会（SNSF）资助。 - **核心故障机制**：通过不安装固定螺母的方式人为制造螺旋桨空中震脱失效，以验证系统全自动故障识别与接管能力。 - **算法与硬件兼容性**：仅需标准四旋翼飞行器自带的常规硬件，是一项纯算法维度的升级，且该控制技术已提交专利申请（Patent Pending）。 ## Mentioned 马克·W·穆勒 (Mark W. Mueller), 拉斐尔·安德烈亚 (Raffaello D'Andrea), Markus Waibel, Max Kriegleder, 苏黎世联邦理工学院动力系统与控制研究所 (IDSC, ETH Zurich), 飞行机器竞技场 (Flying Machine Arena), 瑞士国家科学基金会 (SNSF), 四旋翼无人机 (Quadrocopter) ## Video description Quadrocopter failsafe algorithm -- Institute for Dynamic Systems and Control (IDSC), ETH Zurich, Switzerland - http://www.idsc.ethz.ch/ == UPDATE == Please see this video (http://youtu.be/ek0FrCaogcs) for a demonstration of the flight algorithm without the motion capture system. The video shows an automatic failsafe algorithm that allows a quadrocopter to gracefully cope with the loss of a propeller. The propeller was mounted without a nut, and thus eventually vibrates itself loose. The failure is detected automatically by the system, after which the vehicle recovers and returns to its original position. The vehicle finally executes a controlled, soft landing, on a user's command. The failsafe controller uses only hardware that is readily available on a standard quadrocopter, and could thus be implemented as an algorithmic-only upgrade to existing systems. Until now, the only way a multicopter could survive the loss of a propeller (or motor), is by having redundancy (e.g. hexacopters, octocopters). However, this redundancy comes at the cost of additional structural weight, reducing the vehicle's useful payload. Using this technology, (more efficient) quadrocopters can be used in safety critical applications, because they still have the ability to gracefully recover from a motor/propeller failure. This control approach can also be applied to design novel flying vehicles, the results of which will be posted soon. This technology is patent pending. For more information, please see www.FlyingMachineArena.org Researchers: Mark W. Mueller and Raffaello D'Andrea Video: Mark W. Mueller, Markus Waibel, Max Kriegleder, and Raffaello D'Andrea Location: Flying Machine Arena at ETH Zurich Acknowledgements This work is supported by and builds upon prior contributions by numerous collaborators in the Flying Machine Arena project. See http://www.flyingmachinearena.org/people . This work was supported by the SNSF (Swiss National Science Foundation). [Source](https://www.youtube.com/watch?v=bsHryqnvyYA)

Original transcript

[0:00] *Painful music* *Painful Music* *Painful Music*