- Perceptive Automata: AI understanding of human intent for autonomy - BlinkAI: Imaging AI for autonomy, robotics, sensing - General Radar: High resolution 4D radar for autonomous machines - NextDroid: Autonomously measure & predict self-driving capability - Transit X: Public transit with automated pods on micro-guideways
- Vecna Robotics: Autonomous mobile solutions prioritizing workflows - Akasha Imaging: Vision AI for optically challenging parts - Realtime Robotics: Motion planning for autonomous robots & vehicles - Everactive: Self-powered wireless industrial sensors - Lightelligence: Photonic AI accelerator chip
Total transition to full autonomy in manufacturing is unlikely. While “lights out”, fully-automated factories requiring no input have long been a utopian/dystopian vision for the future, even the most automated electronics or production plants still require a large number of workers to set up, maintain, repair, and spearhead the innovation of equipment. Production systems must constantly adapt to rapidly changing conditions. With current technology and even developments in AI, human presence is often superior at providing that flexibility - which will likely remain the case for years to come.
In this talk, David Mindell, MIT Professor and CEO/Founder of Humatics, will discuss how automation has evolved the manufacturing industry, the critical technologies playing a role in this transformation – including the Humatics microlocation platform, which is driving productivity and safety by providing full visibility into intralogistics vehicle operations – and why full autonomy in manufacturing is a distant, unlikely future.
Tactile sensing plays a privileged role in the manipulation chain: it is in direct contact with the world, potentially offering direct observations of shape, motion and force at contact. This potential, however, is in contrast with today robot's limited tactile reasoning, a long-standing challenge in the robotics research community. After decades of advances in sensing instrumentation and processing power, the basic questions remains: How should robots make effective use of sensed contact information? In this talk I will describe efforts in my group to develop planning and control frameworks that exploit tactile feedback, and demonstrate use cases in automated part picking, part handling, and part assembly.
I will discuss research on the essential recursion that is at the heart of autonomy, from assemblers that assemble assemblers, to machines that make machines, to systems that design systems. And I will explore applications of embodying intelligence in autonomous systems in areas including exponential manufacturing, rapid automation, physical reconfigurability, and personal fabrication.