In the last decade we have seen more robotics innovation becoming real products and companies than in the entire history of robotics.
Furthermore, the greater Silicon Valley and San Francisco Bay Area is at the center of this ‘Cambrian Explosion in Robotics’ as Dr Gill Pratt, Director of Robotics at Toyota Research Institute described it. In fact, two of the very first robots were developed right here.
In 1969 at Stanford, Vic Sheinman designed the first electric robot arm able to be computer controlled. After successful pilots and interest from General Motors, Unimation acquired the concept and released the PUMA or Programmable Universal Machine for Assembly. Unimation was eventually acquired by Staubli, and the PUMA became one of the most successful industrial robots of all time.
Shakey was the first mobile robot able to perceive and reason. Also called the world’s first electronic person by Time Magazine in 1972. Shakey was developed at SRI International from 1966 to 1972 and pioneered many advances in computer vision and path planning and control systems that are still in use today.
These companies have been at the heart of Silicon Valley Robotics, the regional robotics ecosystem/association, but we have also seen enormous growth in new robotics companies and startups in the last decade.
And all of them are hiring.
This volume serves as a guide to students who are interested in studying the field of robotics in any way. Robotics jobs range from service technician, electrical or mechanical engineer, control systems and computer science, to interaction or experience designer, human factors and industrial design.
All these skills are in great demand in robotics companies around the world, and people with experience in robotics are in great demand everywhere. Robotics is a complex multidisciplinary field, which provides opportunities for you to develop problem solving skills and a holistic approach.
The robotics industry also requires people with skill sets in growing businesses, not just robotics, but product and project management, human resources, sales, marketing, operations.
Get involved in robotics – the industry of the 21st century.
Source: OpenAI’s DALL·E 2 with prompt “a hyperrealistic picture of a robot reading the news on a laptop at a coffee shop”
Welcome to the third edition of Robo-Insight, a biweekly robotics news update! In this post, we are excited to share a range of new advancements in the field and highlight progress in areas like motion, unfamiliar navigation, dynamic control, digging, agriculture, surgery, and food sorting.
In a world of constant motion, a newly developed robot named M4 (Multi-Modal Mobility Morphobot) has demonstrated the ability to switch between eight different modes of motion, including rolling, flying, and walking. Designed by researchers from Caltech’s Center for Autonomous Systems and Technologies (CAST) and Northeastern University, the robot can autonomously adapt its movement strategy based on its environment. Created by engineers Mory Gharib and Alireza Ramezani, the M4 project aims to enhance robot locomotion by utilizing a combination of adaptable components and artificial intelligence. The potential applications of this innovation range from medical transport to planetary exploration.
The robot switches from its driving to its walking state. Source.
Speaking of movement, researchers from the Hamburg University of Applied Sciences have presented an innovative navigation algorithm for a mobile robot assistance system based on OpenStreetMap data. The algorithm addresses the challenges faced by visually impaired individuals in navigating unfamiliar routes. By employing a three-stage process involving map verification, augmentation, and generation of a navigable graph, the algorithm optimizes navigation for this user group. The study highlights the potential of OpenStreetMap data to enhance navigation applications for visually impaired individuals, carrying implications for the advancement of robotics solutions that can cater to specific user requirements through data verification and augmentation.
This autonomous vehicle aims to guide visually impaired individuals. Source.
Along the same lines as new environments, researchers from MIT and Stanford University have developed a novel machine-learning technique that enhances the control of robots, such as drones and autonomous vehicles, in rapidly changing environments. The approach leverages insights from control theory to create effective control strategies for complex dynamics, like wind impacts on flying vehicles. This technique holds potential for a range of applications, from enabling autonomous vehicles to adapt to slippery road conditions to improving the performance of drones in challenging wind conditions. By integrating learned dynamics and control-oriented structures, the researchers’ approach offers a more efficient and effective method for controlling robots, with implications for various types of dynamical systems in robotics.
Robot that could have improved control in different environments. Source.
Robots have been improving in areas above ground for a while but are now also advancing in underground spaces, researchers from the University of California Berkeley and the University of California Santa Cruz have unveiled a new robotics approach that utilizes origami-inspired foldable feet to navigate granular environments. Drawing inspiration from biological systems and their anisotropic forces, this approach harnesses reciprocating burrowing techniques for precise directional motion. By employing simple linear actuators and leveraging passive anisotropic force responses, this study paves the way for streamlined robotic burrowing, shedding light on the prospect of simplified yet effective underground exploration and navigation. This innovative integration of origami principles into robotics opens the door to enhanced subterranean applications.
The prototype for the foot and its method for fabrication. Source.
In the world of agriculture, a researcher from Carnegie Mellon University recently explored the synergy between scientific phenotyping and agricultural robotics in a Master’s Thesis. Their study delved into the vital role of accurate plant trait measurement in developing improved plant varieties, while also highlighting the promising realm of robotic plant manipulation in agriculture. Envisioning advanced farming practices, the researcher emphasizes tasks like pruning, pollination, and harvesting carried out by robots. By proposing innovative methods such as 3D cloud assessment for seed counting and vine segmentation, the study aims to streamline data collection for agricultural robotics. Additionally, the creation and use of 3D skeletal vine models exhibit the potential for optimizing grape quality and yield, paving the way for more efficient agricultural practices.
A Robotic data capture platform that was introduced. Source.
Shifting our focus to surgery, a team of mechanical engineers and medical researchers from the University of Maryland, Johns Hopkins University, and the University of Maryland Medical School has developed a pneumatically actuated soft robotic catheter system to enhance control during minimally invasive surgeries. The system allows surgeons to insert and bend the catheter tip with high accuracy simultaneously, potentially improving outcomes in procedures that require navigating narrow and complex body spaces. The researchers’ approach simplifies the mechanical and control architecture through pneumatic actuation, enabling intuitive control of both bending and insertion without manual channel pressurization. The system has shown promise in accurately reaching cylindrical targets in tests, benefiting both novice and skilled surgeons.
Figure showing manufacturing and operation of soft robotic catheter tip using printing process for actuator and pneumatic pressurization to control catheter bending. Source.
Finally, in the food world, researchers have introduced an innovative robotic system designed to efficiently pick and place deformable poultry pieces from cluttered bins. The architecture integrates multiple modules, enabling precise manipulation of delicate poultry items. A comprehensive evaluation approach is proposed to assess the system’s performance across various modules, shedding light on successes and challenges. This advancement holds the potential to revolutionize meat processing and the broader food industry, addressing demands for increased automation.
An experimental setup. Source.
This array of recent developments spanning various fields shows the versatile and ever-evolving character of robotics technology, unveiling fresh avenues for its integration across different sectors. The steady evolution in robotics exemplifies the ongoing endeavors and the potential ramifications these advancements could have in the times ahead.
Sources:
Getting a leg up from mobile robots comes down to getting a bunch of legs. Georgia Institute of Technology
By Baxi Chong (Postdoctoral Fellow, School of Physics, Georgia Institute of Technology)
Adding legs to robots that have minimal awareness of the environment around them can help the robots operate more effectively in difficult terrain, my colleagues and I found.
We were inspired by mathematician and engineer Claude Shannon’s communication theory about how to transmit signals over distance. Instead of spending a huge amount of money to build the perfect wire, Shannon illustrated that it is good enough to use redundancy to reliably convey information over noisy communication channels. We wondered if we could do the same thing for transporting cargo via robots. That is, if we want to transport cargo over “noisy” terrain, say fallen trees and large rocks, in a reasonable amount of time, could we do it by just adding legs to the robot carrying the cargo and do so without sensors and cameras on the robot?
Most mobile robots use inertial sensors to gain an awareness of how they are moving through space. Our key idea is to forget about inertia and replace it with the simple function of repeatedly making steps. In doing so, our theoretical analysis confirms our hypothesis of reliable and predictable robot locomotion – and hence cargo transport – without additional sensing and control.
To verify our hypothesis, we built robots inspired by centipedes. We discovered that the more legs we added, the better the robot could move across uneven surfaces without any additional sensing or control technology. Specifically, we conducted a series of experiments where we built terrain to mimic an inconsistent natural environment. We evaluated the robot locomotion performance by gradually increasing the number of legs in increments of two, beginning with six legs and eventually reaching a total of 16 legs.
Navigating rough terrain can be as simple as taking it a step at a time, at least if you have a lot of legs.
As the number of legs increased, we observed that the robot exhibited enhanced agility in traversing the terrain, even in the absence of sensors. To further assess its capabilities, we conducted outdoor tests on real terrain to evaluate its performance in more realistic conditions, where it performed just as well. There is potential to use many-legged robots for agriculture, space exploration and search and rescue.
Transporting things – food, fuel, building materials, medical supplies – is essential to modern societies, and effective goods exchange is the cornerstone of commercial activity. For centuries, transporting material on land has required building roads and tracks. However, roads and tracks are not available everywhere. Places such as hilly countryside have had limited access to cargo. Robots might be a way to transport payloads in these regions.
Other researchers have been developing humanoid robots and robot dogs, which have become increasingly agile in recent years. These robots rely on accurate sensors to know where they are and what is in front of them, and then make decisions on how to navigate.
However, their strong dependence on environmental awareness limits them in unpredictable environments. For example, in search-and-rescue tasks, sensors can be damaged and environments can change.
My colleagues and I have taken valuable insights from our research and applied them to the field of crop farming. We have founded a company that uses these robots to efficiently weed farmland. As we continue to advance this technology, we are focused on refining the robot’s design and functionality.
While we understand the functional aspects of the centipede robot framework, our ongoing efforts are aimed at determining the optimal number of legs required for motion without relying on external sensing. Our goal is to strike a balance between cost-effectiveness and retaining the benefits of the system. Currently, we have shown that 12 is the minimum number of legs for these robots to be effective, but we are still investigating the ideal number.
The Research Brief is a short take on interesting academic work.
The authors has received funding from NSF-Simons Southeast Center for Mathematics and Biology (Simons Foundation SFARI 594594), Georgia Research Alliance (GRA.VL22.B12), Army Research Office (ARO) MURI program, Army Research Office Grant W911NF-11-1-0514 and a Dunn Family Professorship.
The author and his colleagues have one or more pending patent applications related to the research covered in this article.
The author and his colleagues have established a start-up company, Ground Control Robotics, Inc., partially based on this work.
This article is republished from The Conversation under a Creative Commons license. Read the original article.