Video Friday: Sweet Bite Ham Ham
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. 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!):
ICRA 2022: 23–27 May 2022, Philadelphia
ERF 2022: 28–30 June 2022, Rotterdam, the Netherlands
CLAWAR 2022: 12–14 September 2022, Açores, Portugal
Let us know if you have suggestions for next week, and enjoy today’s videos.
Meet my new favorite robot of all time, Sweet Bite Ham Ham.
It will be the best $35 you’ve ever spent when it goes on sale on a crowdfunding site next week.
[ Campfire ] via [ RobotStart ]
Venus is home to one of the most extreme environments in the solar system. It is permanently shrouded in dense, toxic clouds and its surface is nearly 900 degrees Fahrenheit. Researchers are working on a concept that could change the way we explore the intense environment of Earth’s closest planetary neighbor. Studying Venus will help us better understand why it harbors such an extreme environment and unlock the mysteries of how planets evolve, including Earth.
[ NASA ]
As workers retire, the construction industry faces increasing difficulty finding operators for heavy machinery. Considering this looming shortage, SRI has developed a robotic solution that automates repetitive actions such as digging and enables intuitive remote operation for more complex actions. This progressive autonomy approach will increase the productivity of remaining workers, create new opportunities for remote workers, and encourage new workers to join the industry by making equipment operation safer and more comfortable.
[ SRI ]
We wrote about this malleable structure robot from Imperial College London a couple years back, and now it’s been upgraded with an augmented reality interface to aid in reconfiguration.
[ Paper ]
Skyline Robotics has achieved what many other companies have attempted but failed to perfect. The Israeli company has succeeded in automating window washing for the world’s skyscrapers – a task that has been done manually for over 100 years.
[ Skyline Robotics ]
We present the Tiercel MAV: a small, agile, light weight and collision-resilient robot powered by a cellphone grade CPU. Our design exploits contact to infer the presence of transparent or reflective obstacles like glass walls, integrating touch with visual perception for SLAM.
[ Paper ]
Welp, now I want to work at Ascento.
[ Ascento ]
Inspired by animal locomotion control, we propose simple yet versatile modular neural control with fast learning for legged robots. This control approach is scalable, analyzable, and robust against sensory faults, and its learning process is faster than state-of-the-art locomotion controllers. Using this approach, a hexapod robot can adaptively climb steps and between two walls, as well as walk on a pipe, through a narrow space, and over uneven terrain.
[ SDU ]
Interesting design for a leg for dynamic bipedal humanoids from University of Illinois at Urbana-Champaign.
[ Paper ]
Dusty’s FieldPrinter lays out all interior trades, not just walls. Hear from Southland Industries’ Jesse Sellers and Prime Electric’s Joe Rogers on how Dusty creates a single source of truth on the project to get everyone on the same page, enabling all trades to work better together.
[ Dusty Robotics ]
I’m not sure how practical they are, but I’ve always been fascinated by ornithopter robots.
[ GRVC ]
We tackle the problem of planning a minimum-time trajectory for a quadrotor over a sequence of specified waypoints in the presence of obstacles while exploiting the full quadrotor dynamics. This problem is crucial for autonomous search-and-rescue and drone-racing scenarios but was, so far, unaddressed by the robotics community in its entirety due to the challenges of minimizing time in the presence of the non-convex constraints posed by collision avoidance. The proposed method is shown to outperform all related baselines in cluttered environments and is further validated in real-world flights at over 60km/h in one of the world’s largest motion capture systems.
Curtis Lucas wrote in to share some projects of his: “I own a commercial janitorial business and have struggled to hire qualified employees and in recent years it is even more difficult. As a partial solution to my problem, I began building my own commercial cleaning robots. I have no formal training in robotics. I now have robots that sweep floors, vacuum carpets and mop floors. At a cost of less than two thousand dollars, they pay for themselves within weeks. The robots operate autonomously communicating and updating staff via a Bluetooth app I created. My current robot is a UVC sterilization robot which I will use to sterilize exam rooms at our medical clients.”
[ YouTube ]
In this paper, we present a real-time whole-body planner for collision-free legged mobile manipulation. We enforce both self-collision and environment-collision avoidance as soft constraints within a Model Predictive Control (MPC) scheme that solves a multi-contact optimal control problem. We validate the effectiveness of our framework through a set of hardware experiments involving dynamic mobile manipulation tasks with potential collisions, such as locomotion balancing with the swinging arm, weight throwing, and autonomous door opening.
[ Paper ]
ARI is now ready to start Phase 4 of the Pilots at Clinica Humana (Mallorca, Spain) as part of SHAPES project, where multiple Digital Solutions from different partners have been integrated onto the robot: face recognition, voice interaction, emotion recognition, and videocall, to name a few.
[ PAL Robotics ]
This has to be one of the least meaningful videos I have ever seen.
[ Sanctuary.ai ]
This video is worth watching for the very lifelike emergency stop on a slippery surface.
[ Paper ]
An upcoming ICRA 2022 paper from the AMBER Lab, “Learning Controller Gains on Bipedal Walking Robots via User Preferences.”
[ AMBER Lab ]
A plenary from the ROBIO 2021 conference by Aude Billard, on “Dexterous Manipulation of Objects.”
[ EPFL ]