Our research centers on digital manufacturing, 3D printing and computer graphics, as well as computational photography and displays, and virtual humans and robotics.
To design mathematical models that accurately represent and predict physical properties of real world materials, we construct acquisition devices to measure properties of real world materials and then derive accurate data-driven models from these measurements. The main challenge in computational photography is how to combine the hardware, algorithms, and representations for images and video. We have been developing application-specific systems that demonstrate exceptional capabilities by blending custom hardware and novel algorithms. In particular, we have been working on three-dimensional TV, which we expect to be a significant next step in digital communications. In creating realistic virtual humans we have developed algorithms for computing image-based and polyhedral visual hulls to capture human shape and appearance in real-time. We have improved these systems by using high-quality templates or multi-view normal maps. In order to capture motions outside of a special studio, we have designed wearable systems that combine miniature ultrasonic and inertial sensors.
This work presents a differentiable cloth simulator that extends a state-of-the-art cloth simulator based on Projective Dynamics (PD) and with dry frictional contact. A novel back-propagation technique is proposed to accelerate gradient computation. We demonstrate the effectiveness of the simulator through inverse tasks including system identification, trajectory optimization for assisted dressing, closed-loop control, inverse design.
Knitting is the new 3d printing. It has become popular again with the widespread availability of patterns and templates, together with the maker movements. Lower-cost industrial knitting machines are starting to emerge, but we are still missing the corresponding design tools. Our goal is to fill this gap.
Our goal is to develop new applications and algorithms that leverage the skills of distributed crowdworkers, notably for image and video processing applications.
Adaptive smart glove from MIT CSAIL researchers can send tactile feedback to teach users new skills, guide robots with more precise manipulation, and help train surgeons and pilots.
MIT CSAIL's innovative AI system melds simulations and physical testing to forge materials with newfound durability and flexibility for diverse engineering uses.
Scientists created a rapid design and fabrication tool for soft pneumatic actuators for integrated sensing, which can power personalized healthcare, smart homes, and gaming.
“Evolution Gym” is a large-scale benchmark for co-optimizing the design and control of soft robots that takes inspiration from nature and evolutionary processes
While 3-D movies continue to be popular in theaters, they haven’t made the leap to our homes just yet — and the reason rests largely on the ridge of your nose.
