CITRIS People and Robots

CITRIS and the Banatao Institute - CITRIS People and Robots CPAR

CITRIS People and Robots focuses on theory, benchmarks, software, and approaches that address challenges in the interest of society.

About CITRIS People and Robots (CPAR)

Cloud Robotics, Deep Learning, Human-Centric Automation, and Bio-Inspired Robotics are primary research themes for CITRIS People and Robots. Robotics and automation are advancing rapidly due to innovations in sensors, devices, UAVs, networks, optimization, and machine learning, accelerated by corporate and private investment. These systems have enormous potential to reduce drudgery and improve human experience in healthcare, manufacturing, transportation, safety, and a broad range of other applications in the interests of society. Achieving this will require sensitivity to human issues, rigorous theory evaluated on standard benchmarks, and modular systems built on shared software toolkits.

People and robots are not mutually exclusive. Predictions of the “singularity” are a distraction from a more important concept that might be characterized as “multiplicity,” an emerging category of systems where diverse groups of humans work together with diverse groups of machines to solve difficult problems. Multiplicity combines emerging results in collective intelligence and cloud computing, building on research in ensemble learning, big data, and open-source software. Research in psychology, law, ethics, art, and the humanities are essential to provide historical and cultural context and develop appropriate methods for system and policy design that address human issues such as inclusion, privacy, and alienation. Robotics can also enhance education, inspiring interest in STEM topics for students of all ages.

Dex-Net 4.0 – Learning Ambidextrous Robot Grasping

Vestri the robot imagines how to perform tasks
Surgical Robotic Cutting and Debridement

Multidisciplinary research is needed to investigate the basic and applied science for design of systems and robust performance, addressing the inherent uncertainty in sensing, modeling, and actuation used for control, learning, and systems identification. Cloud Computing can provide access to large datasets and clusters of remote processors to filter, model, optimize, and share data across systems to improve performance over time.

CPAR catalyzes new research by faculty and students from the four CITRIS campuses, building on 40 years of research that has produced significant results, a network of alumni, and many active labs and projects. CPAR also catalyze new research with software, datasets, seminars and collaborations with industry, labs, and public outreach.

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