Automation is coming to every industry, and nowhere is this more true than in the supply chain. Indeed, coming advances in automation technology could potentially reshape the entire supply chain--and supply chain management software--as we know it. Forward-thinking supply chain players are already preparing themselves for the new landscape. CIOs should be leading this charge to drive the best possible outcomes for their organizations, but it's important to understand the nature of robotics, AI, and automation in the supply chain first. Supply chain automation is a broad term that refers to technology that reduces or eliminates human involvement in supply chain activities.

Drones, robots and self-driving cars could dodge accidents in future thanks to a new sensor inspired by the collision avoidance neurons of swarming locusts. Flying locusts travel in swarms of millions at 2–3 miles an hour -- but are capable of making evasive manoeuvres within just hundreds of milliseconds to avoid collisions. Researchers from the US have developed an electronic version of a special neuron, unique to locusts, that allows them to react rapidly without using much energy. Unlike current collision sensors for self-driving cars -- which tend to be bulky and heavy -- the insect-inspired detector is tiny and can respond in just two seconds. 'We are always looking for animals with unusual abilities, ones that do something better than humans,' said paper author and engineer Saptarshi Das of the Pennsylvania State University.

Carmaker Toyota has unveiled plans for a 2,000-person "city of the future," where it will test autonomous vehicles, smart technology and robot-assisted living. The ambitious project, dubbed Woven City, is set to break ground next year in the foothills of Japan's Mount Fuji, about 60 miles from Tokyo. Announcing the project at the Consumer Electronics Show (CES) in Las Vegas, Toyota's CEO Akio Toyoda described the new city as a "living laboratory" that will allow researchers, scientists and engineers to test emerging technology in a "real-life environment." A digital mock-up shows small autonomous vehicles operating alongside pedestrians. "With people buildings and vehicles all connected and communicating with each other through data and sensors, we will be able to test AI technology, in both the virtual and the physical world, maximizing its potential," he said on stage during Tuesday's unveiling.

One of the biggest challenges in building autonomous vehicles is dealing with the irregularities of physical spaces outdoors: From electric poles to winding roads and bumpy terrain, there are lots of things that can trip up your creation. With that in mind, a team of researchers at Microsoft have built and open sourced a simulation tool to help people train autonomous cars, drones and robots learn how to avoid obstacles just like they would in the real world. It's called the Aerial Informatics and Robotics Platform, or AirSim for short. Available for Linux and Windows, it lets you generate a random environment to train your bot or vehicle, experiment with various models and test in a range of scenarios right in your workshop. It's worth noting that the software isn't designed to entirely replace real-world testing, but rather to complement it by allowing you to simulate a wide range of experiments on demand and as many times as necessary. In addition to creating detailed environments that mimic the real world, AirSim also incorporates realistic physics systems to accurately simulate various lighting conditions and object clusters (such as a bunch of trees) to help train robotic models in understanding how to compute depth, avoid obstacles and deal with shadows and glare when navigating through outdoor spaces.