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CLARI: CU Boulder’s Squishable Robot Can Squeeze Through Gaps

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Here is a tiny robot that can change its shape to squeeze through narrow gaps. CLARI, also known as Compliant Legged Articulated Robotic Insect, is inspired by bugs. It can transform its shape from square to long and slender when in tight spaces. It has a modular design and 4 legs. The below video shows it in action:

CLARI: The incredible, squishable robot

[where to get it]

Tail STAR Double Joint Tail Sprawling Robot for Search & Rescue

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This is the Tail STAR: a double joint tail sprawling robot that can overcome a variety of obstacles. It can cross over gaps and climb over stairs. This robot was developed by Matan Coronel and David Zarrouk. Its tail enables the robot to move its center of mass forwards or backwards and extend its length to achieve more surface contact points.

LightStrike+ UV Robot for Healthcare Facilities

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Meet the LightStrike+ UV Robot: a smart robot that helps keep healthcare facilities free of germs. This FDA authorized device uses high intensity light for fast microbial reduction. It is smart enough to detect motion and stop. It has customizable room types and positions.

The LightStrike+ robot reduces pathogens on non-porous, high-touch surfaces.

[HT]

Ecoppia H4 Solar Panel Cleaning Robot

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This is the Ecoppia H4: an autonomous robotic cleaning solution for fixed tilt and single axis trackers. It moves horizontally but cleans vertically. The H4 is cloud based and can be remotely managed from anywhere. It features bidirectional cleaning. The below video shows what makes this solar cleaner special:

Next Gen Hadrian X Bricklaying Robot with 32m Telescoping Boom

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This is the next generation Hadrian X: a construction and bricklaying robot with a 32m telescoping boom that can handle blocks up to 60cm x 40cm x 30cm. It can work outdoors in uncontrolled environments. It can build structures from a 3D CAD model.

Next-Gen Hadrian X® completes first outdoor test build | FBR

This robot can build the walls of a house in as little as a day. It has a special software that turns wall sketches into block positions.

[HT]

Midea V12 5000PA Sweeping & Mopping Robot

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Robotic vacuums are getting more powerful all the time. The Midea V12 is a 5000Pa vacuum cleaning robot with 3D obstacle detection technology. It has pinpoint accurate LiDAR functionality. The Midea V12 also serves as a mop with 200RPM scrubbing to get rid of stubborn stains.

The base scrubs and rinses away all debris. It has a 3L dustbag to hold up to 60days worth of dust.

[HT]

Eureka E10S Voice Controlled Robotic Vacuum with Bagless Multi-cyclonic Station

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Meet the Eureka E10S: a voice controlled robotic vacuum with a bagless multi-cyclonic station for easy cleaning and maintenance. It comes with 4000pa suction power to get the job done. It relies on LiDAR and position sensitive detectors for obstacle avoidance and navigation.

UR20 Heavy Payload Cobot Used for Welding

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Meet the UR20 from Universal Robots: a heavy payload cobot that can automate many applications, including welding. It has a compact design and small footprint. This robot has a reach of 1750mm with payload capacity of 44.1lbs. It is IP65 rated.

DreameBot L20 Ultra 7000Pa Robotic Vacuum with AI-driven MopExtend

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Meet the DreameBot L20 Ultra: an app connected robotic vacuum with 7000pa suction power that cleans your home efficiently. It is smart enough to operate in complex living environments. Its mop can rise up to 10.5mm to clean low-pile carpets. The L20 Ultra has position sensitive detectors to identify corners and edges.

Swift: AI Racing Drone Beats Human World Champions

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FPV drone racing can be a lot of fun but takes a lot of practice to master. In the future, pilots will be able to race against the AI. Swift is an autonomous system that can race against humans at the level of of a world champion. It uses deep reinforcement learning with real world data. Swift competed against 3 human champions recently and won multiple races. It also demonstrated the fastest recorded race time.

Champion-level Drone Racing using Deep Reinforcement Learning (Nature, 2023)

As the researchers explain, this drone used an on-board computer, camera, and an inertial sensor.

[HT] [Credit: Elia Kaufmann, Leonard Bauersfeld, Antonio Loquercio, Matthias Müller, Vladlen Koltun, Davide Scaramuzza]

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