Collaborative Robotics & Adaptive Machines Lab

Located at Kaufman Hall 116

Discover Our Focus

MAE Group Pic

The Collaborative Robotics and Adaptive Machines Laboratory (CRAMlab) aims to make fundamental advances in the science and engineering of robotics with diverse applications in autonomous systems, advanced manufacturing, and healthcare. Ongoing projects include the development of novel underwater robotic platforms for ocean exploration tasks, swarming of aerial drones, bio-inspired jumping robotics for locomotion in lunar environments, robotic micro-drilling for manufacturing and medical applications, hand-held robots for specimen retrieval in minimally invasive surgery, and development of muscle-like actuators for applications in soft robotics.

Our research interests are:

  • 聽Collaborative Robotics
  • 聽Autonomous Systems
  • 聽Swarm Intelligence
  • 聽Bio-inspired Robotics
  • 聽Medical Robotics

Explore Our Research

  • Book published in the area of swarm intelligence-based optimization. K. N. Kaipa and D. Ghose. Glowworm Swarm Optimization: Theory, Algorithms, and Applications, Studies in Computational Intelligence, Vol. 698, Springer-Verlag, 2017. ISBN: 978-3-319-51594-6 (Print) 978-3-319-51595-3 (Online).
  • Best Paper Award.聽ASME Computer-Aided Product and Process Development Technical Committee's Prakash Krishnaswamy Best Paper Award,聽ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE), Cleveland, Ohio, USA, 2017.
  • Outstanding Teaching Award.聽For the graduate course,聽Planning for Autonomous Robots, taught at the University of Maryland in spring 2016.

  1. K. N. Kaipa, A. S. Kankanhalli-Nagendra, N. B. Kumbla, S. Shriyam, S. S. Thevendria-Karthic, J. A. Marvel, and S. K. Gupta (2016). Addressing perception uncertainty induced failure modes in robotic bin-picking.聽Robotics and Computer Integrated Manufacturing聽42(1), 17-38.
  2. C. W. Morato, K. N. Kaipa, and S. K. Gupta (2014). Toward safe human-robot collaboration by using multiple Kinects based real-time human tracking.聽ASME Journal of Computing and Information Science in Engineering,聽14(1): 011006.
  3. C. W. Morato, K. N. Kaipa, and S. K. Gupta (2013). Improving assembly precedence constraint generation by utilizing motion planning and part interaction clusters,聽Computer-Aided Design, 45 (11): 1349-1364.
  4. K. N. Kaipa, J. C. Bongard, and A. N. Meltzoff (2010). Self-discovery enables robot social cognition: Are you my teacher?聽Neural Networks, Special Issue on Social Cognition: Babies to Robots, 23(8-9): 1113-1124.
  5. K. N. Kaipa and D. Ghose (2009). Glowworm swarm optimization for simultaneous capture of multiple local optima of multimodal functions. Swarm Intelligence, 3(2): 87-124.

Professor & Assistant Dean Engineering Technology
Professor & Chair Engineering Technology
Assoc Dean For Diversity, Equity, Inclusion & Access Engineering & Technology
Master Lecturer Department of Teaching & Learning
Associate Professor Mechanical & Aerospace Engineering
Associate Professor Mechanical & Aerospace Engineering

  • Kuka LBR iiwa Robot
  • NAO Social Robot
  • object 30 Prime 3D Printer
  • GoScan 3D Scanner
Kuka Robot
NAO Robot
3D Printer
3D Scanner

A significant thrust in the CRAMlab is to pursue experimental robotics research with a strong belief that research of this nature immensely benefits from a rich mix of in-house robotics platforms designed/manufactured from scratch and customization of commercially available robots. To realize this dream, the CRAMlab is equipped with state-of-the-art equipment including the KUKA LBR IIWA collaborative robot, the Sawyer collaborative robot, the Dobot collaborative robot, the Nao social robot, Object 30 Prime 3D printer, Bamboo Labs 3D printer, Go-Scan 3D Scanner, Turtlebot mobile robots, Sphero robots, Festo鈥檚 Bionics4Education kits, and Hummingbird robotics kits.

  • MAE 336 Electromechanical Systems
  • 聽MAE 431 Mechanisms鈥擠esign and Analysis
  • 聽MAE 434W Senior Design Project - I
  • 聽MAE 435 Senior Design Project - II
  • 聽MAE 436 Systems鈥擠ynamics and Control
  • 聽MAE 495 Bio-inspired Robotics
  • 聽MAE 740 Autonomous & Robotic Systems鈥擜nalysis and Control

"It was very fun," Takhvar said. "I built a robot that did not walk very well, to be honest, but I learned that engineering is more than just one discipline. It's a combination of multiple skills from different fields that you need to utilize to complete a job." - Navy Veteran Davis Takhvar

Robotics Videos

Contact

Interested in the Collaborate Robotics & Adaptive Machines Lab? Contact Dr.聽Krishnanand Kaipa.