Tag Archives: climb

#437130 SQuad: A miniature robot that can walk ...

Researchers at Bilkent University in Turkey have recently created a small quadruped robot called SQuad, which is made of soft structural materials. This unique robot, presented in a paper published in IEEE Robotics and Automation Letters, is more flexible than existing miniature robots and is thus better at climbing or circumventing obstacles in its surroundings. Continue reading

Posted in Human Robots

#436470 Retail Robots Are on the Rise—at Every ...

The robots are coming! The robots are coming! On our sidewalks, in our skies, in our every store… Over the next decade, robots will enter the mainstream of retail.

As countless robots work behind the scenes to stock shelves, serve customers, and deliver products to our doorstep, the speed of retail will accelerate.

These changes are already underway. In this blog, we’ll elaborate on how robots are entering the retail ecosystem.

Let’s dive in.

Robot Delivery
On August 3rd, 2016, Domino’s Pizza introduced the Domino’s Robotic Unit, or “DRU” for short. The first home delivery pizza robot, the DRU looks like a cross between R2-D2 and an oversized microwave.

LIDAR and GPS sensors help it navigate, while temperature sensors keep hot food hot and cold food cold. Already, it’s been rolled out in ten countries, including New Zealand, France, and Germany, but its August 2016 debut was critical—as it was the first time we’d seen robotic home delivery.

And it won’t be the last.

A dozen or so different delivery bots are fast entering the market. Starship Technologies, for instance, a startup created by Skype founders Janus Friis and Ahti Heinla, has a general-purpose home delivery robot. Right now, the system is an array of cameras and GPS sensors, but upcoming models will include microphones, speakers, and even the ability—via AI-driven natural language processing—to communicate with customers. Since 2016, Starship has already carried out 50,000 deliveries in over 100 cities across 20 countries.

Along similar lines, Nuro—co-founded by Jiajun Zhu, one of the engineers who helped develop Google’s self-driving car—has a miniature self-driving car of its own. Half the size of a sedan, the Nuro looks like a toaster on wheels, except with a mission. This toaster has been designed to carry cargo—about 12 bags of groceries (version 2.0 will carry 20)—which it’s been doing for select Kroger stores since 2018. Domino’s also partnered with Nuro in 2019.

As these delivery bots take to our streets, others are streaking across the sky.

Back in 2016, Amazon came first, announcing Prime Air—the e-commerce giant’s promise of drone delivery in 30 minutes or less. Almost immediately, companies ranging from 7-Eleven and Walmart to Google and Alibaba jumped on the bandwagon.

While critics remain doubtful, the head of the FAA’s drone integration department recently said that drone deliveries may be “a lot closer than […] the skeptics think. [Companies are] getting ready for full-blown operations. We’re processing their applications. I would like to move as quickly as I can.”

In-Store Robots
While delivery bots start to spare us trips to the store, those who prefer shopping the old-fashioned way—i.e., in person—also have plenty of human-robot interaction in store. In fact, these robotics solutions have been around for a while.

In 2010, SoftBank introduced Pepper, a humanoid robot capable of understanding human emotion. Pepper is cute: 4 feet tall, with a white plastic body, two black eyes, a dark slash of a mouth, and a base shaped like a mermaid’s tail. Across her chest is a touch screen to aid in communication. And there’s been a lot of communication. Pepper’s cuteness is intentional, as it matches its mission: help humans enjoy life as much as possible.

Over 12,000 Peppers have been sold. She serves ice cream in Japan, greets diners at a Pizza Hut in Singapore, and dances with customers at a Palo Alto electronics store. More importantly, Pepper’s got company.

Walmart uses shelf-stocking robots for inventory control. Best Buy uses a robo-cashier, allowing select locations to operate 24-7. And Lowe’s Home Improvement employs the LoweBot—a giant iPad on wheels—to help customers find the items they need while tracking inventory along the way.

Warehouse Bots
Yet the biggest benefit robots provide might be in-warehouse logistics.

In 2012, when Amazon dished out $775 million for Kiva Systems, few could predict that just 6 years later, 45,000 Kiva robots would be deployed at all of their fulfillment centers, helping process a whopping 306 items per second during the Christmas season.

And many other retailers are following suit.

Order jeans from the Gap, and soon they’ll be sorted, packed, and shipped with the help of a Kindred robot. Remember the old arcade game where you picked up teddy bears with a giant claw? That’s Kindred, only her claw picks up T-shirts, pants, and the like, placing them in designated drop-off zones that resemble tiny mailboxes (for further sorting or shipping).

The big deal here is democratization. Kindred’s robot is cheap and easy to deploy, allowing smaller companies to compete with giants like Amazon.

Final Thoughts
For retailers interested in staying in business, there doesn’t appear to be much choice in the way of robotics.

By 2024, the US minimum wage is projected to be $15 an hour (the House of Representatives has already passed the bill, but the wage hike is meant to unfold gradually between now and 2025), and many consider that number far too low.

Yet, as human labor costs continue to climb, robots won’t just be coming, they’ll be here, there, and everywhere. It’s going to become increasingly difficult for store owners to justify human workers who call in sick, show up late, and can easily get injured. Robots work 24-7. They never take a day off, never need a bathroom break, health insurance, or parental leave.

Going forward, this spells a growing challenge of technological unemployment (a blog topic I will cover in the coming month). But in retail, robotics usher in tremendous benefits for companies and customers alike.

And while professional re-tooling initiatives and the transition of human capital from retail logistics to a booming experience economy take hold, robotic retail interaction and last-mile delivery will fundamentally transform our relationship with commerce.

This blog comes from The Future is Faster Than You Think—my upcoming book, to be released Jan 28th, 2020. To get an early copy and access up to $800 worth of pre-launch giveaways, sign up here!

Join Me
(1) A360 Executive Mastermind: If you’re an exponentially and abundance-minded entrepreneur who would like coaching directly from me, consider joining my Abundance 360 Mastermind, a highly selective community of 360 CEOs and entrepreneurs who I coach for 3 days every January in Beverly Hills, Ca. Through A360, I provide my members with context and clarity about how converging exponential technologies will transform every industry. I’m committed to running A360 for the course of an ongoing 25-year journey as a “countdown to the Singularity.”

If you’d like to learn more and consider joining our 2020 membership, apply here.

(2) Abundance-Digital Online Community: I’ve also created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital. Abundance-Digital is Singularity University’s ‘onramp’ for exponential entrepreneurs — those who want to get involved and play at a higher level. Click here to learn more.

(Both A360 and Abundance-Digital are part of Singularity University — your participation opens you to a global community.)

Image Credit: Image by imjanuary from Pixabay Continue reading

Posted in Human Robots

#436220 How Boston Dynamics Is Redefining Robot ...

Gif: Bob O’Connor/IEEE Spectrum

With their jaw-dropping agility and animal-like reflexes, Boston Dynamics’ bioinspired robots have always seemed to have no equal. But that preeminence hasn’t stopped the company from pushing its technology to new heights, sometimes literally. Its latest crop of legged machines can trudge up and down hills, clamber over obstacles, and even leap into the air like a gymnast. There’s no denying their appeal: Every time Boston Dynamics uploads a new video to YouTube, it quickly racks up millions of views. These are probably the first robots you could call Internet stars.

Spot

Photo: Bob O’Connor

84 cm HEIGHT

25 kg WEIGHT

5.76 km/h SPEED

SENSING: Stereo cameras, inertial measurement unit, position/force sensors

ACTUATION: 12 DC motors

POWER: Battery (90 minutes per charge)

Boston Dynamics, once owned by Google’s parent company, Alphabet, and now by the Japanese conglomerate SoftBank, has long been secretive about its designs. Few publications have been granted access to its Waltham, Mass., headquarters, near Boston. But one morning this past August, IEEE Spectrum got in. We were given permission to do a unique kind of photo shoot that day. We set out to capture the company’s robots in action—running, climbing, jumping—by using high-speed cameras coupled with powerful strobes. The results you see on this page: freeze-frames of pure robotic agility.

We also used the photos to create interactive views, which you can explore online on our Robots Guide. These interactives let you spin the robots 360 degrees, or make them walk and jump on your screen.

Boston Dynamics has amassed a minizoo of robotic beasts over the years, with names like BigDog, SandFlea, and WildCat. When we visited, we focused on the two most advanced machines the company has ever built: Spot, a nimble quadruped, and Atlas, an adult-size humanoid.

Spot can navigate almost any kind of terrain while sensing its environment. Boston Dynamics recently made it available for lease, with plans to manufacture something like a thousand units per year. It envisions Spot, or even packs of them, inspecting industrial sites, carrying out hazmat missions, and delivering packages. And its YouTube fame has not gone unnoticed: Even entertainment is a possibility, with Cirque du Soleil auditioning Spot as a potential new troupe member.

“It’s really a milestone for us going from robots that work in the lab to these that are hardened for work out in the field,” Boston Dynamics CEO Marc Raibert says in an interview.

Atlas

Photo: Bob O’Connor

150 cm HEIGHT

80 kg WEIGHT

5.4 km/h SPEED

SENSING: Lidar and stereo vision

ACTUATION: 28 hydraulic actuators

POWER: Battery

Our other photographic subject, Atlas, is Boston Dynamics’ biggest celebrity. This 150-centimeter-tall (4-foot-11-inch-tall) humanoid is capable of impressive athletic feats. Its actuators are driven by a compact yet powerful hydraulic system that the company engineered from scratch. The unique system gives the 80-kilogram (176-pound) robot the explosive strength needed to perform acrobatic leaps and flips that don’t seem possible for such a large humanoid to do. Atlas has inspired a string of parody videos on YouTube and more than a few jokes about a robot takeover.

While Boston Dynamics excels at making robots, it has yet to prove that it can sell them. Ever since its founding in 1992 as a spin-off from MIT, the company has been an R&D-centric operation, with most of its early funding coming from U.S. military programs. The emphasis on commercialization seems to have intensified after the acquisition by SoftBank, in 2017. SoftBank’s founder and CEO, Masayoshi Son, is known to love robots—and profits.

The launch of Spot is a significant step for Boston Dynamics as it seeks to “productize” its creations. Still, Raibert says his long-term goals have remained the same: He wants to build machines that interact with the world dynamically, just as animals and humans do. Has anything changed at all? Yes, one thing, he adds with a grin. In his early career as a roboticist, he used to write papers and count his citations. Now he counts YouTube views.

In the Spotlight

Photo: Bob O’Connor

Boston Dynamics designed Spot as a versatile mobile machine suitable for a variety of applications. The company has not announced how much Spot will cost, saying only that it is being made available to select customers, which will be able to lease the robot. A payload bay lets you add up to 14 kilograms of extra hardware to the robot’s back. One of the accessories that Boston Dynamics plans to offer is a 6-degrees-of-freedom arm, which will allow Spot to grasp objects and open doors.

Super Senses

Photo: Bob O’Connor

Spot’s hardware is almost entirely custom-designed. It includes powerful processing boards for control as well as sensor modules for perception. The ­sensors are located on the front, rear, and sides of the robot’s body. Each module consists of a pair of stereo cameras, a wide-angle camera, and a texture projector, which enhances 3D sensing in low light. The sensors allow the robot to use the navigation method known as SLAM, or simultaneous localization and mapping, to get around autonomously.

Stepping Up

Photo: Bob O’Connor

In addition to its autonomous behaviors, Spot can also be steered by a remote operator with a game-style controller. But even when in manual mode, the robot still exhibits a high degree of autonomy. If there’s an obstacle ahead, Spot will go around it. If there are stairs, Spot will climb them. The robot goes into these operating modes and then performs the related actions completely on its own, without any input from the operator. To go down a flight of stairs, Spot walks backward, an approach Boston Dynamics says provides greater stability.

Funky Feet

Gif: Bob O’Connor/IEEE Spectrum

Spot’s legs are powered by 12 custom DC motors, each geared down to provide high torque. The robot can walk forward, sideways, and backward, and trot at a top speed of 1.6 meters per second. It can also turn in place. Other gaits include crawling and pacing. In one wildly popular YouTube video, Spot shows off its fancy footwork by dancing to the pop hit “Uptown Funk.”

Robot Blood

Photo: Bob O’Connor

Atlas is powered by a hydraulic system consisting of 28 actuators. These actuators are basically cylinders filled with pressurized fluid that can drive a piston with great force. Their high performance is due in part to custom servo valves that are significantly smaller and lighter than the aerospace models that Boston Dynamics had been using in earlier designs. Though not visible from the outside, the innards of an Atlas are filled with these hydraulic actuators as well as the lines of fluid that connect them. When one of those lines ruptures, Atlas bleeds the hydraulic fluid, which happens to be red.

Next Generation

Gif: Bob O’Connor/IEEE Spectrum

The current version of Atlas is a thorough upgrade of the original model, which was built for the DARPA Robotics Challenge in 2015. The newest robot is lighter and more agile. Boston Dynamics used industrial-grade 3D printers to make key structural parts, giving the robot greater strength-to-weight ratio than earlier designs. The next-gen Atlas can also do something that its predecessor, famously, could not: It can get up after a fall.

Walk This Way

Photo: Bob O’Connor

To control Atlas, an operator provides general steering via a manual controller while the robot uses its stereo cameras and lidar to adjust to changes in the environment. Atlas can also perform certain tasks autonomously. For example, if you add special bar-code-type tags to cardboard boxes, Atlas can pick them up and stack them or place them on shelves.

Biologically Inspired

Photos: Bob O’Connor

Atlas’s control software doesn’t explicitly tell the robot how to move its joints, but rather it employs mathematical models of the underlying physics of the robot’s body and how it interacts with the environment. Atlas relies on its whole body to balance and move. When jumping over an obstacle or doing acrobatic stunts, the robot uses not only its legs but also its upper body, swinging its arms to propel itself just as an athlete would.

This article appears in the December 2019 print issue as “By Leaps and Bounds.” Continue reading

Posted in Human Robots

#436186 Video Friday: Invasion of the Mini ...

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!):

DARPA SubT Urban Circuit – February 18-27, 2020 – Olympia, Wash., USA
Let us know if you have suggestions for next week, and enjoy today’s videos.

There will be a Mini-Cheetah Workshop (sponsored by Naver Labs) a year from now at IROS 2020 in Las Vegas. Mini-Cheetahs for everyone!

That’s just a rendering, of course, but this isn’t:

[ MCW ]

I was like 95 percent sure that the Urban Circuit of the DARPA SubT Challenge was going to be in something very subway station-y. Oops!

In the Subterranean (SubT) Challenge, teams deploy autonomous ground and aerial systems to attempt to map, identify, and report artifacts along competition courses in underground environments. The artifacts represent items a first responder or service member may encounter in unknown underground sites. This video provides a preview of the Urban Circuit event location. The Urban Circuit is scheduled for February 18-27, 2020, at Satsop Business Park west of Olympia, Washington.

[ SubT ]

Researchers at SEAS and the Wyss Institute for Biologically Inspired Engineering have developed a resilient RoboBee powered by soft artificial muscles that can crash into walls, fall onto the floor, and collide with other RoboBees without being damaged. It is the first microrobot powered by soft actuators to achieve controlled flight.

To solve the problem of power density, the researchers built upon the electrically-driven soft actuators developed in the lab of David Clarke, the Extended Tarr Family Professor of Materials. These soft actuators are made using dielectric elastomers, soft materials with good insulating properties, that deform when an electric field is applied. By improving the electrode conductivity, the researchers were able to operate the actuator at 500 Hertz, on par with the rigid actuators used previously in similar robots.

Next, the researchers aim to increase the efficiency of the soft-powered robot, which still lags far behind more traditional flying robots.

[ Harvard ]

We present a system for fast and robust handovers with a robot character, together with a user study investigating the effect of robot speed and reaction time on perceived interaction quality. The system can match and exceed human speeds and confirms that users prefer human-level timing.

In a 3×3 user study, we vary the speed of the robot and add variable sensorimotor delays. We evaluate the social perception of the robot using the Robot Social Attribute Scale (RoSAS). Inclusion of a small delay, mimicking the delay of the human sensorimotor system, leads to an improvement in perceived qualities over both no delay and long delay conditions. Specifically, with no delay the robot is perceived as more discomforting and with a long delay, it is perceived as less warm.

[ Disney Research ]

When cars are autonomous, they’re not going to be able to pump themselves full of gas. Or, more likely, electrons. Kuka has the solution.

[ Kuka ]

This looks like fun, right?

[ Robocoaster ]

NASA is leading the way in the use of On-orbit Servicing, Assembly, and Manufacturing to enable large, persistent, upgradable, and maintainable spacecraft. This video was developed by the Advanced Concepts Lab (ACL) at NASA Langley Research Center.

[ NASA ]

The noisiest workshop by far at Humanoids last month (by far) was Musical Interactions With Humanoids, the end result of which was this:

[ Workshop ]

IROS is an IEEE event, and in furthering the IEEE mission to benefit humanity through technological innovation, IROS is doing a great job. But don’t take it from us – we are joined by IEEE President-Elect Professor Toshio Fukuda to find out a bit more about the impact events like IROS can have, as well as examine some of the issues around intelligent robotics and systems – from privacy to transparency of the systems at play.

[ IROS ]

Speaking of IROS, we hope you’ve been enjoying our coverage. We have already featured Harvard’s strange sea-urchin-inspired robot and a Japanese quadruped that can climb vertical ladders, with more stories to come over the next several weeks.

In the mean time, enjoy these 10 videos from the conference (as usual, we’re including the title, authors, and abstract for each—if you’d like more details about any of these projects, let us know and we’ll find out more for you).

“A Passive Closing, Tendon Driven, Adaptive Robot Hand for Ultra-Fast, Aerial Grasping and Perching,” by Andrew McLaren, Zak Fitzgerald, Geng Gao, and Minas Liarokapis from the University of Auckland, New Zealand.

Current grasping methods for aerial vehicles are slow, inaccurate and they cannot adapt to any target object. Thus, they do not allow for on-the-fly, ultra-fast grasping. In this paper, we present a passive closing, adaptive robot hand design that offers ultra-fast, aerial grasping for a wide range of everyday objects. We investigate alternative uses of structural compliance for the development of simple, adaptive robot grippers and hands and we propose an appropriate quick release mechanism that facilitates an instantaneous grasping execution. The quick release mechanism is triggered by a simple distance sensor. The proposed hand utilizes only two actuators to control multiple degrees of freedom over three fingers and it retains the superior grasping capabilities of adaptive grasping mechanisms, even under significant object pose or other environmental uncertainties. The hand achieves a grasping time of 96 ms, a maximum grasping force of 56 N and it is able to secure objects of various shapes at high speeds. The proposed hand can serve as the end-effector of grasping capable Unmanned Aerial Vehicle (UAV) platforms and it can offer perching capabilities, facilitating autonomous docking.

“Unstructured Terrain Navigation and Topographic Mapping With a Low-Cost Mobile Cuboid Robot,” by Andrew S. Morgan, Robert L. Baines, Hayley McClintock, and Brian Scassellati from Yale University, USA.

Current robotic terrain mapping techniques require expensive sensor suites to construct an environmental representation. In this work, we present a cube-shaped robot that can roll through unstructured terrain and construct a detailed topographic map of the surface that it traverses in real time with low computational and monetary expense. Our approach devolves many of the complexities of locomotion and mapping to passive mechanical features. Namely, rolling movement is achieved by sequentially inflating latex bladders that are located on four sides of the robot to destabilize and tip it. Sensing is achieved via arrays of fine plastic pins that passively conform to the geometry of underlying terrain, retracting into the cube. We developed a topography by shade algorithm to process images of the displaced pins to reconstruct terrain contours and elevation. We experimentally validated the efficacy of the proposed robot through object mapping and terrain locomotion tasks.

“Toward a Ballbot for Physically Leading People: A Human-Centered Approach,” by Zhongyu Li and Ralph Hollis from Carnegie Mellon University, USA.

This work presents a new human-centered method for indoor service robots to provide people with physical assistance and active guidance while traveling through congested and narrow spaces. As most previous work is robot-centered, this paper develops an end-to-end framework which includes a feedback path of the measured human positions. The framework combines a planning algorithm and a human-robot interaction module to guide the led person to a specified planned position. The approach is deployed on a person-size dynamically stable mobile robot, the CMU ballbot. Trials were conducted where the ballbot physically led a blindfolded person to safely navigate in a cluttered environment.

“Achievement of Online Agile Manipulation Task for Aerial Transformable Multilink Robot,” by Fan Shi, Moju Zhao, Tomoki Anzai, Keita Ito, Xiangyu Chen, Kei Okada, and Masayuki Inaba from the University of Tokyo, Japan.

Transformable aerial robots are favorable in aerial manipulation tasks for their flexible ability to change configuration during the flight. By assuming robot keeping in the mild motion, the previous researches sacrifice aerial agility to simplify the complex non-linear system into a single rigid body with a linear controller. In this paper, we present a framework towards agile swing motion for the transformable multi-links aerial robot. We introduce a computational-efficient non-linear model predictive controller and joints motion primitive frame-work to achieve agile transforming motions and validate with a novel robot named HYRURS-X. Finally, we implement our framework under a table tennis task to validate the online and agile performance.

“Small-Scale Compliant Dual Arm With Tail for Winged Aerial Robots,” by Alejandro Suarez, Manuel Perez, Guillermo Heredia, and Anibal Ollero from the University of Seville, Spain.

Winged aerial robots represent an evolution of aerial manipulation robots, replacing the multirotor vehicles by fixed or flapping wing platforms. The development of this morphology is motivated in terms of efficiency, endurance and safety in some inspection operations where multirotor platforms may not be suitable. This paper presents a first prototype of compliant dual arm as preliminary step towards the realization of a winged aerial robot capable of perching and manipulating with the wings folded. The dual arm provides 6 DOF (degrees of freedom) for end effector positioning in a human-like kinematic configuration, with a reach of 25 cm (half-scale w.r.t. the human arm), and 0.2 kg weight. The prototype is built with micro metal gear motors, measuring the joint angles and the deflection with small potentiometers. The paper covers the design, electronics, modeling and control of the arms. Experimental results in test-bench validate the developed prototype and its functionalities, including joint position and torque control, bimanual grasping, the dynamic equilibrium with the tail, and the generation of 3D maps with laser sensors attached at the arms.

“A Novel Small-Scale Turtle-inspired Amphibious Spherical Robot,” by Huiming Xing, Shuxiang Guo, Liwei Shi, Xihuan Hou, Yu Liu, Huikang Liu, Yao Hu, Debin Xia, and Zan Li from Beijing Institute of Technology, China.

This paper describes a novel small-scale turtle-inspired Amphibious Spherical Robot (ASRobot) to accomplish exploration tasks in the restricted environment, such as amphibious areas and narrow underwater cave. A Legged, Multi-Vectored Water-Jet Composite Propulsion Mechanism (LMVWCPM) is designed with four legs, one of which contains three connecting rod parts, one water-jet thruster and three joints driven by digital servos. Using this mechanism, the robot is able to walk like amphibious turtles on various terrains and swim flexibly in submarine environment. A simplified kinematic model is established to analyze crawling gaits. With simulation of the crawling gait, the driving torques of different joints contributed to the choice of servos and the size of links of legs. Then we also modeled the robot in water and proposed several underwater locomotion. In order to assess the performance of the proposed robot, a series of experiments were carried out in the lab pool and on flat ground using the prototype robot. Experiments results verified the effectiveness of LMVWCPM and the amphibious control approaches.

“Advanced Autonomy on a Low-Cost Educational Drone Platform,” by Luke Eller, Theo Guerin, Baichuan Huang, Garrett Warren, Sophie Yang, Josh Roy, and Stefanie Tellex from Brown University, USA.

PiDrone is a quadrotor platform created to accompany an introductory robotics course. Students build an autonomous flying robot from scratch and learn to program it through assignments and projects. Existing educational robots do not have significant autonomous capabilities, such as high-level planning and mapping. We present a hardware and software framework for an autonomous aerial robot, in which all software for autonomy can run onboard the drone, implemented in Python. We present an Unscented Kalman Filter (UKF) for accurate state estimation. Next, we present an implementation of Monte Carlo (MC) Localization and Fast-SLAM for Simultaneous Localization and Mapping (SLAM). The performance of UKF, localization, and SLAM is tested and compared to ground truth, provided by a motion-capture system. Our evaluation demonstrates that our autonomous educational framework runs quickly and accurately on a Raspberry Pi in Python, making it ideal for use in educational settings.

“FlightGoggles: Photorealistic Sensor Simulation for Perception-driven Robotics using Photogrammetry and Virtual Reality,” by Winter Guerra, Ezra Tal, Varun Murali, Gilhyun Ryou and Sertac Karaman from the Massachusetts Institute of Technology, USA.

FlightGoggles is a photorealistic sensor simulator for perception-driven robotic vehicles. The key contributions of FlightGoggles are twofold. First, FlightGoggles provides photorealistic exteroceptive sensor simulation using graphics assets generated with photogrammetry. Second, it provides the ability to combine (i) synthetic exteroceptive measurements generated in silico in real time and (ii) vehicle dynamics and proprioceptive measurements generated in motio by vehicle(s) in flight in a motion-capture facility. FlightGoggles is capable of simulating a virtual-reality environment around autonomous vehicle(s) in flight. While a vehicle is in flight in the FlightGoggles virtual reality environment, exteroceptive sensors are rendered synthetically in real time while all complex dynamics are generated organically through natural interactions of the vehicle. The FlightGoggles framework allows for researchers to accelerate development by circumventing the need to estimate complex and hard-to-model interactions such as aerodynamics, motor mechanics, battery electrochemistry, and behavior of other agents. The ability to perform vehicle-in-the-loop experiments with photorealistic exteroceptive sensor simulation facilitates novel research directions involving, e.g., fast and agile autonomous flight in obstacle-rich environments, safe human interaction, and flexible sensor selection. FlightGoggles has been utilized as the main test for selecting nine teams that will advance in the AlphaPilot autonomous drone racing challenge. We survey approaches and results from the top AlphaPilot teams, which may be of independent interest. FlightGoggles is distributed as open-source software along with the photorealistic graphics assets for several simulation environments, under the MIT license at http://flightgoggles.mit.edu.

“An Autonomous Quadrotor System for Robust High-Speed Flight Through Cluttered Environments Without GPS,” by Marc Rigter, Benjamin Morrell, Robert G. Reid, Gene B. Merewether, Theodore Tzanetos, Vinay Rajur, KC Wong, and Larry H. Matthies from University of Sydney, Australia; NASA Jet Propulsion Laboratory, California Institute of Technology, USA; and Georgia Institute of Technology, USA.

Robust autonomous flight without GPS is key to many emerging drone applications, such as delivery, search and rescue, and warehouse inspection. These and other appli- cations require accurate trajectory tracking through cluttered static environments, where GPS can be unreliable, while high- speed, agile, flight can increase efficiency. We describe the hardware and software of a quadrotor system that meets these requirements with onboard processing: a custom 300 mm wide quadrotor that uses two wide-field-of-view cameras for visual- inertial motion tracking and relocalization to a prior map. Collision-free trajectories are planned offline and tracked online with a custom tracking controller. This controller includes compensation for drag and variability in propeller performance, enabling accurate trajectory tracking, even at high speeds where aerodynamic effects are significant. We describe a system identification approach that identifies quadrotor-specific parameters via maximum likelihood estimation from flight data. Results from flight experiments are presented, which 1) validate the system identification method, 2) show that our controller with aerodynamic compensation reduces tracking error by more than 50% in both horizontal flights at up to 8.5 m/s and vertical flights at up to 3.1 m/s compared to the state-of-the-art, and 3) demonstrate our system tracking complex, aggressive, trajectories.

“Morphing Structure for Changing Hydrodynamic Characteristics of a Soft Underwater Walking Robot,” by Michael Ishida, Dylan Drotman, Benjamin Shih, Mark Hermes, Mitul Luhar, and Michael T. Tolley from the University of California, San Diego (UCSD) and University of Southern California, USA.

Existing platforms for underwater exploration and inspection are often limited to traversing open water and must expend large amounts of energy to maintain a position in flow for long periods of time. Many benthic animals overcome these limitations using legged locomotion and have different hydrodynamic profiles dictated by different body morphologies. This work presents an underwater legged robot with soft legs and a soft inflatable morphing body that can change shape to influence its hydrodynamic characteristics. Flow over the morphing body separates behind the trailing edge of the inflated shape, so whether the protrusion is at the front, center, or back of the robot influences the amount of drag and lift. When the legged robot (2.87 N underwater weight) needs to remain stationary in flow, an asymmetrically inflated body resists sliding by reducing lift on the body by 40% (from 0.52 N to 0.31 N) at the highest flow rate tested while only increasing drag by 5.5% (from 1.75 N to 1.85 N). When the legged robot needs to walk with flow, a large inflated body is pushed along by the flow, causing the robot to walk 16% faster than it would with an uninflated body. The body shape significantly affects the ability of the robot to walk against flow as it is able to walk against 0.09 m/s flow with the uninflated body, but is pushed backwards with a large inflated body. We demonstrate that the robot can detect changes in flow velocity with a commercial force sensor and respond by morphing into a hydrodynamically preferable shape. Continue reading

Posted in Human Robots

#436042 Video Friday: Caltech’s Drone With ...

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!):

ISRR 2019 – October 6-10, 2019 – Hanoi, Vietnam
Ro-Man 2019 – October 14-18, 2019 – New Delhi, India
Humanoids 2019 – October 15-17, 2019 – Toronto, Canada
ARSO 2019 – October 31-1, 2019 – Beijing, China
ROSCon 2019 – October 31-1, 2019 – Macau
IROS 2019 – November 4-8, 2019 – Macau
Let us know if you have suggestions for next week, and enjoy today’s videos.

Caltech has been making progress on LEONARDO (LEg ON Aerial Robotic DrOne), their leggy thruster powered humanoid-thing. It can now balance and walk, which is quite impressive to see.

We’ll circle back again when they’ve got it jumping and floating around.

[ Caltech ]

Turn the subtitles on to learn how robots became experts at slicing bubbly, melty, delicious cheese.

These robots learned how to do the traditional Swiss raclette from demonstration. The Robot Learning & Interaction group at the Idiap Research Institute has developed an imitation learning technique allowing the robot to acquire new skills by considering position and force information, with an automatic adaptation to new situations. The range of applications is wide, including industrial robots, service robots, and assistive robots.

[ Idiap ]

Thanks Sylvain!

Some amazing news this week from Skydio, with the announcement of their better in every single way Skydio 2 autonomous drone. Read our full article for details, but here’s a getting started video that gives you an overview of what the drone can do.

The first batch sold out in 36 hours, but you can put down a $100 deposit to reserve the $999 drone for 2020 delivery.

[ Skydio ]

UBTECH is introducing a couple new robot kits for the holidays: ChampBot and FireBot.

$130 each, available on October 20.

[ Ubtech ]

NASA’s InSight lander on Mars is trying to use its robotic arm to get the mission’s heat flow probe, or mole, digging again. InSight team engineer Ashitey Trebbi-Ollennu, based at NASA’s Jet Propulsion Laboratory in Pasadena, California, explains what has been attempted and the game plan for the coming weeks. The next tactic they’ll try will be “pinning” the mole against the hole it’s in.

[ NASA ]

We introduce shape-changing swarm robots. A swarm of self-transformable robots can both individually and collectively change their configuration to display information, actuate objects, act as tangible controllers, visualize data, and provide physical affordances. ShapeBots is a concept prototype of shape-changing swarm robots. Each robot can change its shape by leveraging small linear actuators that are thin (2.5 cm) and highly extendable (up to 20cm) in both horizontal and vertical directions.

[ Ryo Suzuki ]

Robot abuse!

Vision 60 legged robot managing unstructured terrain without vision or force sensors in its legs. Using only high-transparency actuators and 2kHz algorithmic stability control… 4-limbs and 12-motors with only a velocity command.

[ Ghost Robotics ]

We asked real people to bring in real products they needed picked for their application. In MINUTES, we assembled the right tool.

This is a cool idea, but for a real challenge they should try it outside a supermarket. Or a pet store.

[ Soft Robotics ]

Good water quality is important to humans and to nature. In a country with as much water as the Netherlands has, ensuring water quality is a very labour-intensive undertaking. To address this issue, researchers from TU Delft have developed a ‘pelican drone’: a drone capable of taking water samples quickly, in combination with a measuring instrument that immediately analyses the water quality. The drone was tested this week at the new Marker Wadden nature area ‘Living Lab’.

[ MAVLab ]

In an international collaboration led by scientists in Switzerland, three amputees merge with their bionic prosthetic legs as they climb over various obstacles without having to look. The amputees report using and feeling their bionic leg as part of their own body, thanks to sensory feedback from the prosthetic leg that is delivered to nerves in the leg’s stump.

[ EPFL ]

It’s a little hard to see, but this is one way of testing out asteroid imaging spacecraft without actually going into space: a fake asteroid and a 2D microgravity simulator.

[ Caltech ]

Drones can help filmmakers do the kinds of shots that would be otherwise impossible.

[ DJI ]

Two long interviews this week from Lex Fridman’s AI Podcast, and both of them are worth watching: Gary Marcus, and Peter Norvig.

[ AI Podcast ]

This week’s CMU RI Seminar comes from Tucker Hermans at the University of Utah, on “Improving Multi-fingered Robot Manipulation by Unifying Learning and Planning.”

Multi-fingered hands offer autonomous robots increased dexterity, versatility, and stability over simple two-fingered grippers. Naturally, this increased ability comes with increased complexity in planning and executing manipulation actions. As such, I propose combining model-based planning with learned components to improve over purely data-driven or purely-model based approaches to manipulation. This talk examines multi-fingered autonomous manipulation when the robot has only partial knowledge of the object of interest. I will first present results on planning multi-fingered grasps for novel objects using a learned neural network. I will then present our approach to planning in-hand manipulation tasks when dynamic properties of objects are not known. I will conclude with a discussion of our ongoing and future research to further unify these two approaches.

[ CMU RI ] Continue reading

Posted in Human Robots