Oliver Brock

TL;DR: RBO Hand 2 is presented, a highly compliant, underactuated, robust, and dexterous anthropomorphic hand that is inexpensive to manufacture and the morphology can easily be adapted to specific applications, and it is demonstrated that complex grasping behavior can be achieved with relatively simple control.

TL;DR: The global dynamic window approach is proposed, which combines methods from motion planning and real-time obstacle avoidance to result in a framework that allows robust execution of high-velocity, goal-directed reactive motion for a mobile robot in unknown and dynamic environments.

TL;DR: The routing protocol MV is introduced, which learns structure in the movement patterns of network participants and uses it to enable informed message passing and the introduction of autonomous agents as additional participants in DTNs.

TL;DR: The need for better evaluation metrics is explained, the importance and unique challenges for deep robotic learning in simulation are highlighted, and the spectrum between purely data-driven and model-driven approaches is explored.

TL;DR: An overview of the inaugural Amazon Picking Challenge is presented along with a summary of a survey conducted among the 26 participating teams, highlighting mechanism design, perception, and motion planning algorithms, as well as software engineering practices that were most successful in solving a simplified order fulfillment task.