Browse Topic: Robotics
There's a well-known video from San Francisco in 1906 that comes up repeatedly in mobility discussions here in the 21st Century. If you haven't seen A Trip Down Market Street, it depicts the absolute bonkers variety of transportation methods used on Market Street back then: cable cars, horsecars, streetcars, pedestrians, automobiles and more. Past is prologue in a world that is adding scooters, delivery robots and other last-minute delivery vehicles to our streets. At the 2026 New York International Auto Show in April, Honda displayed its latest option in the form of the Fastport eQuad Prototype. The eQuad was originally unveiled at Eurobike 2025 and technically comes from Fastport, a micromobility venture from the Honda New Business Innovation Lab that was established to work on projects with global logistics companies. Jamie Davies, chief of operations for Fastport, called the group a kind of startup within Honda. “Three years ago,” Davies told SAE Media in New York, “a small group of Honda associates [came] together and [said], Okay, how can we create a new value for the company, a new business vertical? And so we've run the project in an agile way, working with customers all along the way to understand what their needs are, what the requirements are, and to bring to market something that fits.”
Robot Arm Tracking Control refers to the control of robot end effectors following a prescribed trajectory as their movement in robotic systems. The work presents a combination of Kalman Filter Based Dynamic System Tracking with Reinforcement Learning Based Trajectory Planning. These two aspects of tracking and planning help the robotic manipulator dynamically track a target that is located on an arbitrary moving path. In particular, by using Kalman filtering to estimate the position of a moving target and to compensate for sensor noise and sparse sampling, we take high-precision estimation values of each point’s coordinates along the target trajectory as a reliable basis to build a policy network using reinforcement learning. Based on it, the robot manipulator could produce effective motion planning under its own dynamic capabilities and physical constraint limit. Comprehensive simulation results illustrate advantages of the new algorithm against the classical control method, confirm that the novel technique achieves better performance both in accuracy and computation efficiency. Also, this mixed control system can deal with complex moving path for track target object. Even when meet different obstacle and not sure measurement, it still works well with other moving obstacle in many conditions. This can be strong to face other dynamic obstacle even if have different situation with changing obstacle and uncertain data. It shows that this paper works as an attempt toward optimal solution to combine the model-based technique together with data-driven approach aiming to support real-time, highly accurate, adaptive prediction is based control technique, promising applications into industry and promoting more improved works related.
Soft robot systems demonstrate exceptional load-bearing capacity and spatial compliance during operation, with transformative potential in disaster response scenarios requiring adaptive morphology and hazardous material manipulation. By integrating the complementary advantages of soft robotics and particle jamming mechanisms, this study proposes a real-time variable-stiffness soft actuator, while systematically investigating its mathematical modeling framework and stiffness modulation principles. A deformation model for the variable stiffness soft actuator is established, followed by static analysis of the variable-stiffness members using particle jamming theory, with theoretical investigation of their stress distributions. Subsequently, a variable-stiffness driver was fabricated via additive manufacturing (3D printing), resulting in a flexible mechanical digit capable of stiffness tuning, A soft mechanical hand grasping test platform was built, and grasping experiments of objects of different shapes and sizes were conducted. Experimental validation confirms the influence of actuator dimensions, particle characteristics, and granule size distribution on both stress states and bending angles at the soft robotic digit’s distal segment. The obtained results establish theoretical foundations and advance variable-stiffness soft robotics research and associated stiffness regulation methodologies.
Machina Labs recently closed its latest round of financing with $124 million, enough to develop a facility featuring up to 50 of its RoboCraftsman cells capable of producing thousands of complex structural assemblies for aerospace and defense customers - a list that already includes Lockheed Martin and the U.S. Air Force, among others. Founded in 2019, Machina Labs is a California-based company that seeks to reinvent metal manufacturing with a robot that uses artificial intelligence (AI) to rapidly form and assemble complex military grade structures directly from digital design files. RoboCraftsman is the company's manufacturing robot that leverages its proprietary “RoboForming” process to integrate multiple manufacturing processes - including metal forming, trimming, scanning, and heat treating - into a single containerized machine.
USC Viterbi researcher received Office of Naval Research's Young Investigator Program award with Study on dexterous robotics. University of Southern California, Los Angeles, CA In dynamic, unstructured environments like ship decks and even home kitchens, robots today still struggle to perform precision tasks such as tightening bolts or handling wires. This makes critical ship maintenance tasks difficult. USC researcher, Erdem Bıyık, aims to advance robots' finger manipulation and integrate human feedback to enable real-time learning for robots in an upcoming three-year, $750,000 project funded by the Office of Naval Research (ONR).
As the adoption of electric vehicles continues to accelerate, the demand for their development and testing using chassis dynamometers has also increased significantly. Compared with internal combustion engine vehicles, chassis dynamometer testing for electric vehicles typically requires test durations several to several dozen times longer, resulting in substantially increased labor requirements. In addition, low-temperature testing is often required, further intensifying the workload associated with vehicle testing. To address these challenges, this study developed and evaluated a pedal robot designed to enable unmanned and automated testing. The pedal robot developed in this study weighs only 12 kg and can be installed within a few minutes. It is, to the authors’ knowledge, the world’s first pedal robot that mimics human driving behavior by using a single foot to operate both the accelerator and brake pedals. Unlike conventional driving robots, the actuators of the proposed system do not require direct mechanical attachment to the vehicle pedals, allowing for rapid installation. Furthermore, the robot is mounted on the driver-side floor, eliminating the need for attachment to the seat structure. The pedal robot features three degrees of freedom driven by three motors and employs artificial intelligence to recognize the shape and position of pedals across different vehicle models, thereby enabling automated test initiation without manual adjustment. The performance of the pedal robot was evaluated under UDDS, HWFET, and WLTC driving modes, and the results were analyzed in accordance with the SAE J2951 standard. Comparative evaluations demonstrated that the pedal robot achieved superior speed-tracking performance relative to that of an experienced human test driver. The developed pedal robot is currently being utilized for vehicle certification testing of electric and other vehicles at the Mobile Environment Research Center of the National Institute of Environmental Research in Korea. This paper presents a detailed analysis of the corresponding experimental results.
Imagine a robot about the size of a toaster floating through the tight corridors of the International Space Station, quietly moving supplies or checking for leaks — all without an astronaut at the controls. Such technology could free up valuable time for astronauts and open new opportunities for robotics-based exploration. That sci-fi vision is coming closer to reality now that Stanford researchers have become the first to show that machine-learning-based control can operate aboard the ISS.
During the 2025 Association of the United States Army (AUSA) annual meeting and exhibition, Forterra announced several major defense industry vehicle partnerships and introduced four new integrated modules designed to enable autonomy for military vehicles, communications, and more. Headquartered in Clarksburg, Maryland, Forterra develops autonomous mission systems for specific defense applications, including robotics and self-driving vehicles. The company has a new partnership with BAE Systems that will rapidly prototype an autonomous Armored Multi-Purpose Vehicle (AMPV). Separately, Forterra has also collaborated with Oshkosh Defense and Raytheon to develop the “DeepFires” autonomous vehicle launcher technology.
Multimodal sensors, capable of simultaneously acquiring multiple physical or chemical signals, have shown broad application potential in fields such as health monitoring, soft robotics, and energy systems. However, current multimodal sensors often suffer from complex fabrication processes and signal decoupling challenges, which limit their practical deployment. To address these issues, this work presents a thin-film temperature–strain multimodal sensor (FTSMS) fabricated via laser processing. The temperature-sensing unit, based on the Seebeck effect, achieves a sensitivity of 9.08 μV/°C, while the strain-sensing unit, utilizing BaTiO₃/AlN@PDMS as the sensitive layer, exhibits a gauge factor (GF) of 43.2. By integrating distinct sensing mechanisms (thermovoltage for temperature and capacitance change for strain), the FTSMS enables self-decoupled measurements over 20–90 °C. Applied in LIB monitoring, it successfully captures real-time temperature and strain variations during charge-discharge cycles and provides multidimensional information throughout thermal runaway (TR) processes, enabling early TR warning and supporting safety-oriented battery design.
Penn State UAS Research Lab (PURL) and Autonomous Robotics Competition Club (ARCC)
This paper elucidates the implementation of software-controlled synchronous rectification and dead time configuration for bi-directional controlled DC motors. These motors are extensively utilized in applications such as robotics and automotive systems to prolong their operational lifespan. Synchronous rectification mitigates large current spikes in the H-bridge, reducing conduction losses and improving efficiency [1]. Dead time configuration prevents shoot-through conditions, enhancing motor efficiency and longevity. Experimental results demonstrate significant improvements in motor performance, including reduced thermal stress, decreased power consumption, and increased reliability [2]. The reduction in power consumption helps to minimize thermal stress, thereby enhancing the overall efficiency and longevity of the motor.
It all started when Owen Kent and Todd Roberts became roommates at the University of California Berkeley. Owen has muscular dystrophy and had recently acquired a robotic arm, which he noticed he was using to do range of motion. Todd had come to Berkeley to study mechanical engineering with a focus on biomechanics, and both were enrolled in Designing for the Human Body, a biomechanics course taught by Mechanical Engineering Professor Grace O’Connell.
EPFL researchers have engineered a fiber-based electronic sensor that remains functional even when stretched to over 10 times its original length. The device holds promise for smart textiles, physical rehabilitation devices, and soft robotics.
Bosch Rexroth displayed new battery automation solutions at The Battery Show 2025 in Detroit in October, focusing on making batteries in a more efficient manner. The company's customizable conveyance system can now add the ctrlX Flow HS linear motion system and the ctrlX Flow 6D contactless transport system to move components, promising new options in an era when everyone and their suppliers are looking for ways to make better EVs. Andreas Letsch, director of the Battery Factory Automation Center of Competence at Bosch Rexroth AG, told SAE Media that the new additions can make a modern battery plant more efficient as its footprint shrinks. Used with the company's Cartesian multi-axis systems, the new systems offer improved ways to position components and handle tasks. The multi-axis cobots can effectively shift workspace vertically - they need less floor space than traditional 6-axis robot arms - providing another important factor in an efficient facility.
From sorting objects in a warehouse to navigating furniture while vacuuming, robots today use sensors, software control systems, and moving parts to perform tasks. The harder the task or more complex the environment, the more cumbersome and expensive the electronic components.
Robots may soon have a new way to communicate with people. Not through words or screens, but with light and images projected directly onto the world around them.
Missions to the moon and other planets will require large-scale infrastructure that would benefit from autonomous assembly by robots without on-site human intervention. Modular and reconfigurable structures, such as those built from lattice-based building blocks, are reusable and easy to manufacture. Furthermore, reconfigurable systems have the potential to outperform traditional, fixed infrastructure in applications that require high levels of flexibility in addition to structural strength and rigidity. NASA Ames Research Center has developed a novel and efficient mobile bipedal robot system to construct low-mass, high precision, and largescale infrastructure.
Like octopi squeezing through a tiny sea cave, metatruss robots can adapt to demanding environments by changing their shape. These mighty morphing robots are made of trusses composed of hundreds of beams and joints that rotate and twist, enabling astonishing volumetric transformations.
Researchers at the University of California San Diego have developed a soft robotic skin that enables vine robots that are just a few millimeters wide to navigate convoluted paths and fragile environments. To accomplish this, the researchers integrated a very thin layer of actuators made of liquid crystal elastomer at strategic locations in the soft skin. The robot is steered by controlling the pressure inside its body and temperature of the actuators.
Soft robots, medical devices and implants, and next-generation drug delivery methods could soon be guided with magnetism — thanks to a metal-free magnetic gel developed by researchers at the University of Michigan and the Max Planck Institute for Intelligent Systems in Stuttgart, Germany.
Innovators at NASA Johnson Space Center have developed additively manufactured thermal protection system (AMTPS) comprised of two printable heat shield material formulations. These formulations are directly applied by 3D printer or other robotic extrusion system and bonded to a spacecraft to devise a heat shield suitable for atmospheric entry. This technology could significantly decrease heat shield or thermal protection system (TPS) fabrication cost and time.
In an era where technology increasingly merges with healthcare to enhance patient outcomes, a groundbreaking study conducted by Fuyang Yu and his colleagues introduces an innovative approach to lower limb rehabilitation. Their research, published in Cyborg Bionic Systems, outlines the development of a lower limb rehabilitation robot designed to significantly improve the safety and effectiveness of gait training through a novel method based on human-robot interaction force measurement.
Keshika Warnakula is a Senior Flight Mechanics Engineer at Syos Aerospace Limited and the winner of the 2025 Rising Stars Award Aerospace and Defense category. Syos Aerospace is based in Mount Maunganui, New Zealand, specializing in robotics engineering and the development of autonomous air, land, and sea vehicles. The company also has an office located in Fareham, UK, and was recently named New Zealand's “Hi-Tech Company Of the Year.”
A team of engineers has developed a low-cost, durable, highly-sensitive robotic ‘skin’ that can be added to robotic hands like a glove, enabling robots to detect information about their surroundings in a way that’s similar to humans.
ABB Robotics is enabling faster, safer, and more cost-effective rebuilding in areas devastated by the 2025 Southern Californian wildfires through a collaboration with Cosmic Buildings — a leading construction technology company that uses proprietary mobile robotic microfactories. After the wildfires burned thousands of acres, destroying homes, infrastructure, and natural habitats, this pioneering initiative will deploy the microfactory in Pacific Palisades, CA, to build modular structures onsite, offering a glimpse into the future of affordable housing construction.
At UC Berkeley, researchers in Sergey Levine’s Robotic AI and Learning Lab eyed a table where a tower of 39 Jenga blocks stood perfectly stacked. Then a white-and-black robot, its single limb doubled over like a hunched-over giraffe, zoomed toward the tower, brandishing a black leather whip. Through what might have seemed to a casual viewer like a miracle of physics, the whip struck in precisely the right spot to send a single block flying out from the stack while the rest of the tower remained structurally sound.
Animals like bats, whales, and insects have long used acoustic signals for communication and navigation. Now, an international team of scientists have taken a page from nature’s playbook to model micro-sized robots that use sound waves to coordinate into large swarms that exhibit intelligent-like behavior. The robot groups could one day carry out complex tasks like exploring disaster zones, cleaning up pollution, or performing medical treatments from inside the body, according to team lead Igor Aronson, Huck Chair Professor of Biomedical Engineering, Chemistry, and Mathematics at Penn State.
In an office in Bordeaux, the Pollen Robotics teams are working on an ambitious mission: to imagine and advance useful robotics for humans. Their flagship creation, Reachy, combines accessibility, innovation, and open-source collaboration. But first, let’s go back to where it all started.
Items per page:
50
1 – 50 of 2115