6 accepted papers
Robotic object manipulation requires knowledge of the environment's state. In particular, the object poses of fixed elements in the environment relative to the robot and the in-hand poses of grasped objects are of interest. For insertion tasks with tight tolerances, the accuracy of vision systems to…
Plaster is commonly used in the construction industry to finish walls and ceilings, but the application is labor-intensive and physically strenuous, which motivates the need for automation. We present PLASTR, a receding horizon optimization-based planning algorithm for robotic plaster trowelling. It
Measurement update rules for Bayes filters often contain hand-crafted heuristics to compute observation probabilities for high-dimensional sensor data, like images. In this work, we propose the novel approach Deep Measurement Update (DMU) as a general update rule for a wide range of systems. DMU has
A robotic platform for mobile manipulation needs to satisfy two contradicting requirements for many real-world applications: A compact base is required to navigate through cluttered indoor environments, while the support needs to be large enough to prevent tumbling or tip over, especially during fas
A mobile robot needs to be aware of its environment to interact with it safely. We propose a receding horizon control scheme for mobile manipulators that tracks task space reference trajectories. It uses visual information to avoid obstacles and haptic sensing to control interaction forces. Addition
We present a fully-integrated sensing and control system which enables mobile manipulator robots to execute building tasks with millimeter-scale accuracy on building construction sites. The approach leverages multi-modal sensing capabilities for state estimation, tight integration with digital build…