Walking and Flying Robots for Challenging Environments

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Shaping the future Walking and Flying Robots for Challenging Environments Roland Siegwart, ETH Zurich www.asl.ethz.ch www.wysszurich.ch Lisbon, Portugal, July 29, 2016 Roland Siegwart 29.07.2016 1

Content Introduction The next generation of robots Robot Design Examples from ASL at ETH Zurich Mobile Robot Navigation from perception to autonomous navigation Application Fields Roland Siegwart 29.07.2016 2

Robotics today (Changan-Ford China ) https://www.youtube.com/watch?v=seioqy0oxji Roland Siegwart 29.07.2016 17

Next generation of Robots mobile, smart, connected, adaptive and closer to humans Industrial Robots Service and Personal Robots Cyborgs Roland Siegwart 29.07.2016 20

Robotics Key Directions Robots that can dealing with uncertain and partially available information Robots that see, feel and understand their environment Robots with torque and force control for tactile interaction ( soft robots ) Robots with intuitive human-machine interfaces Robots that learn and adapt every day Roland Siegwart 29.07.2016 31

@ ETH Institute of Robotics and Intelligent Systems Prof. Dr. Roland Siegwart Mission and Dedication To create intelligent robots and systems that operate autonomously in complex and dynamic environments. Research Focus ~ 40 researcher (PhDs, Postdocs, ) ~ 60 master students ~ 10 startups Design Navigation Novel robot concepts that are best adapted for ground, air, or water based applications. New algorithms for perception, localization, abstraction, mapping, and path planning that will enable autonomous operation in challenging environments. Roland Siegwart 29.07.2016 39

Research Fields Autonomous Cars Visual navigation and autonomous operation in city environments Unmanned Aerial Vehicles Design, control and fully autonomous operation and interaction in complex environments Solar Airplanes Continuous flight for long-term environment monitoring All Terrain Robots Design and collaborative navigation of flying and ground robots Mobile Manipulation Object handling for manufacturing, logistics, and e-commerce Service Robots Navigation and transportation in our daily environment Roland Siegwart 29.07.2016 41

Robotics Start with the Design Rolling, Swimming, Walking and Flying Robots Roland Siegwart 29.07.2016 42

Ultimate Rolling Robots designed by students rezero (2010) the ball balancing robot https://www.youtube.com/watch?v=acohrh64yks BeachBot (2014, with Disney) the beach artist https://www.youtube.com/watch?v=ebrrqbptdak Vertigo (2015 with Disney) the ultimate wall climber https://www.youtube.com/watch?v=kryt2kybgo4 Scalevo (2015) the stair-climbing wheelchair https://www.youtube.com/watch?v=3lb_8nmy90c Roland Siegwart 29.07.2016 51

Underwater Robots designed by students Naro (2009) the tuna robot https://www.youtube.com/watch?v=l61o2cmzcc4 Taratuga (2012) the turtle robot https://www.youtube.com/watch?v=pqy_nshcgls Sepios (2014, with Disney) the Kalmar robot https://www.youtube.com/watch?v=gecll2rwv1c Scubo (2016, with Disney) the agile underwater robot https://www.youtube.com/watch?v=-g2o8e1j3fw Roland Siegwart 29.07.2016 52

Walking Robots serial elastic actuation ALOF (2008) the versatile walker https://www.youtube.com/watch?v=f5hsfyirhzi StarlETH (2010) the quadruped with serial elastic actuation https://www.youtube.com/watch?v=7qj65ta7tle AnyBot (2015) the ultimate quadruped https://www.youtube.com/watch?v=ei1zbtypxw0 Prof. Marco Hutter Roland Siegwart 29.07.2016 60

Efficient Walking and Running serial elastic actuation https://www.youtube.com/watch?v=6ignzivtbxu Roland Siegwart 29.07.2016 62

StarlETH Leg Design for Dynamic Walking High fidelity DCmotors with harmonic drives Leaf springs Planar 3-DoF guiding unit Chain drive reduces leg inertia High resolution encoders to register forces damper Modular foot design Nonlinear spring for knee Roland Siegwart 29.07.2016 63

ANYmal an electrically actuated dog for real-world scenarios Prof. Marco Hutter High mobility to go where today only humans can go 10 kg of payload 2 h of continuous operations https://www.youtube.com/watch?v=ei1zbtypxw0 Roland Siegwart 29.07.2016 68

Flying Robots new ways of flying OS4 (2003) pioneering quadrotors https://www.youtube.com/watch?v=vsvte6_74tu&index=34&list=pljol3sa8g75rnj0valyl0bbftnuhwwe1g Reely (2009 with Disney) the flying reel https://www.youtube.com/watch?v=rf6oykkmrx8 Skye (2012 with Disney) the omnidirectional blimp https://www.youtube.com/watch?v=qxvl3ank3w0 PacFlyer/wingtra (2013) the VTOL UAV https://www.youtube.com/watch?v=qadvpdwtgfu Roland Siegwart 29.07.2016 71

Flying Robots fixed wing Skysailor (2008) pioneering continuous flights 3.2 m, 2.3 kg https://www.youtube.com/watch?v=iu4boefoeki (2012) robust and versatile solar plane 3 m, 3.8 kg (2015) 81 hours non-stop in summer 2015 5.64 m, 6.2 kg https://www.youtube.com/watch?v=8m4_nptqn0e Roland Siegwart 29.07.2016 76

? Mobile Robot Navigation Localization, Mapping and Planning Roland Siegwart 29.07.2016 77

OKVIS Open Keyframe-based Visual-Inertial SLAM (tight coupling of vision and IMU) Cost Reprojection errors (weighted) IMU terms i: camera index; k: camera frame index; j: landmark index. Roland Siegwart 29.07.2016 122

OKVIS Open Keyframe-based Visual-Inertial SLAM (tight coupling of vision and IMU) motion of an assembly of Inertial Measurement Units (IMU) and N cameras to reconstructs the scene sparsely Roland Siegwart 29.07.2016 124

Seeing Visual-Inertial Motion Estimation https://www.youtube.com/watch?v=yvgprznp4so Roland Siegwart 29.07.2016 127

LL-VSLAM Localization performance comparison Global localization error for different levels of map summarization processing of odometry and localization landmarks: VIL SWL tightly coupled (proposed method) loosely coupled approach The proposed visual-inertial localization algorithm performs well with heavily summarized maps Roland Siegwart 29.07.2016 133

ROVIO Robust Visual Inertial Odometry robo-centric representation EKF based IMU-Vision fuses projected intensity errors (instead of reprojection errors) Procedure feature detection & image patch is extracted Derivation of an intensity based error terms dimension reduction of error term by QR-decomposition directly used as Kalman filter innovation Roland Siegwart 29.07.2016 141

ROVIO Robust Visual Inertial Odometry https://www.youtube.com/watch?v=zmaisvy-6ao&list=pljol3sa8g75rnj0valyl0bbftnuhwwe1g&index=2 [M. Bloesch et al (2015). Robust Visual Inertial Odometry Using a Direct EKF-Based Approach, IROS] Roland Siegwart 29.07.2016 144

V-Charge Automated Valet Parking and Charging for e-mobility Close-to-market sensor systems vision, stereo vision, ultrasonic etc. Online localization and mapping Situation assessment Street, pedestrians Path Planning Global & local (collision avoidance) Highly adaptive and predictive dynamic obstacles and their potential trajectory. Roland Siegwart 29.07.2016 152

V-Charge autonomous car using close-to-market sensors Wheel encoders ultrasound cameras Roland Siegwart 29.07.2016 153 11.11.2015

V-Charge Vision and Results https://www.youtube.com/watch?v=7xqfktatynu Roland Siegwart 29.07.2016 157

Flying Robots EU-Projects Roland Siegwart 29.07.2016 172

UAV vision only navigation Vision-inertial navigation (one camera and IMU, GPS denied) Fully autonomous with on-board computing Scale estimation Feature-based visual SLAM robust against lighting changes and large scale changes www.sfly.ethz.ch/ https://www.youtube.com/watch?v=vhpw8zc7-jq Proto 2 Proto 1 Proto 3 Roland Siegwart 29.07.2016 175

UAV collision avoidance and path planning Real time 3D mapping (on-board) optimal path planning considering localization uncertainties Proto 2 https://www.youtube.com/watch?v=95xgves9its Proto 1 Proto 3 Roland Siegwart 29.07.2016 176 https://www.youtube.com/watch?v=95xgves9its https://www.youtube.com/watch?v=d6uvejymea4 https://www.youtube.com/watch?v=-cm-hkti8vw

Omnidirectional 3D visual obstacle detection and avoidance https://www.youtube.com/watch?v=0qedc2mwifi Roland Siegwart 29.07.2016 179

Flying Manipulation tree cavity inspection 3DOF robot arm Roland Siegwart 29.07.2016 183

Autonomous Exploration Path-Planning next best view planner On the current octomap knowledge expand an RRT with depth N NBVP. Compute the Additive Information Gain of all possible paths of depth N NBVP. Select the Next-Best-Viewing-Path Execute only the first step Repeat with on the updated octomap Roland Siegwart 29.07.2016 186

Autonomous Exploration Path-Planning next best view planner Roland Siegwart 29.07.2016 187

Collaborative Visual-Inertial Navigation in collaboration with https://www.youtube.com/watch?v=9pprndikraw Prof. Marco Hutter https://www.youtube.com/watch?v=9pprndikraw Roland Siegwart 29.07.2016 190

Opportunities / Markets Industrial transportation Cleaning Medical robotics Entertainment / edutainment YuMi Logistics Autonomous Cars The coffee servant Nesspresso / Bluebotics, Switzerland Industrial inspection Surveillance and rescue Construction and mining Agriculture Health and elderly care Personal / services robots Roland Siegwart 29.07.2016 193

Zurich Area a melting pot for robotics technology Initiatives Spin-offs (*ASL) Industrial Collaborations (ASL) * * Center for Learning Systems EU-Projects ASL * * * * Roland Siegwart 29.07.2016 202

ASL Team Industrial Partners Funding Agencies Current and former ASL Members Roland Siegwart 29.07.2016 212