This paper presents a technical overview of Team DRC-Hubo@UNLV's approach to the 2015 DARPA Robotics Challenge Finals (DRC-Finals). The Finals required a robotic platform that was robust and reliable in both hardware and software to complete tasks in 60 min under degraded communication. With this point of view, Team DRC-Hubo@UNLV integrated methods and algorithms previously verified, validated, and widely used in the robotics community. For the communication aspect, a common shared memory approach that the team adopted to enable efficient data communication under the DARPA controlled network is described. A new perception head design (optimized for the tasks of the Finals) and its data processing are then presented. In the motion planning and control aspect, various techniques, such as wheel-driven navigation, zero-momentpoint (ZMP) -based locomotion, and position-based manipulation and controls, are described in this paper. By introducing strategically critical elements and key lessons learned from DRC-Trials 2013 and the testbed of Charleston, we also illustrate how DRC-Hubo has evolved successfully toward the DRC-Finals. C 2017 Wiley Periodicals, Inc.
Abstract-The upcoming DARPA Robotics Challenge (DRC) presents a demanding set of real-world tasks to be accomplished autonomously by robots. In this paper, we describe the development of a system to control an existing humanoid robot to open a door, one of the many tasks of the DRC. Special emphasis is placed upon generating smooth trajectories which minimize unnecessary motion of the robot. We describe methods for generating and optimizing trajectories for the robot, and present preliminary results demonstrated on the physical robotic platform. To the best of our knowledge, we demonstrate the first large scale application of the CHOMP trajectory optimization in a situation with closed kinematic chain constraints.
Up to now humanoid robots have been designed primarily for walking on flat surfaces. In the future, humanoid robots are required to replace human beings to operate in natural or damaged man-engineered environments. In the 2013 DARPA Robotics Challenge, the robots are required to walk through several type of rough terrains. In this scenario, the robot will be challenged to keep balance and fulfill the tasks while walking. We have developed several balance gaits and associated controllers. The latter collaborate with a computer vision system to enable our humanoid robot DRC-Hubo to walk over rough terrains. Both theoretical and experimental results are presented to verify the approach.
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