Skip to main content
Open Access Publications from the University of California

Cloud-based Methods and Architectures for Robot Grasping

  • Author(s): Kehoe, Benjamin Robert
  • Advisor(s): Goldberg, Ken
  • Hedrick, Karl
  • et al.

The Cloud has the potential to enhance a broad range of robotics and automation systems. Cloud Robotics and Automation systems can be broadly defined as follows: Any robotic or automation system that relies on either data or code from a network to support its operation, i.e., where not all sensing, computation, and memory is integrated into a single standalone system. We identify four potential benefits of Cloud Robotics and Automation: 1) Big Data: access to remote libraries of images, maps, trajectories, and object data, 2) Cloud Computing: access to parallel grid computing on demand for statistical analysis, learning, and motion planning, 3) Collective Robot Learning: robots sharing trajectories, control policies, and outcomes, and 4) Human computation: using crowdsourcing access to remote human expertise for analyzing images, classification, learning, and error recovery.

We present four Cloud Robotics and Automation systems in this dissertation. First, we develop a system for Cloud-based grasping of 2D polygonal objects with uncertainty in shape using an analytic conservative estimate of the probability of force closure. Second, we develop a system for Cloud-based grasping of 2D polygonal objects with uncertainty in pose, using a quasi-static simulation that is less conservative than the approach for the first system. These two systems demonstrate the usefulness of Cloud-based parallelism for handling uncertainty. Third, we develop a system for recognizing and grasping household objects using the Google Object Recognition Engine as a web service and using Cloud storage of object and grasp information. Finally, we develop a system for providing algorithms as web services and integrating datasets with these services. These systems advance the understanding of the benefits the Cloud can provide for Robotics and Automation.

Main Content
Current View