Mobile manipulation tasks are one of the key challenges in the field of search and rescue (SAR) robotics requiring robots with flexible locomotion and manipulation abilities. Since the tasks are mostly unknown in advance, the robot has to adapt to a wide variety of terrains and workspaces during a mission. The centaur-like robot Centauro has a hybrid legged-wheeled base and an anthropomorphic upper body to carry out complex tasks in environments too dangerous for humans. Due to its high number of degrees of freedom, controlling the robot with direct teleoperation approaches is challenging and exhausting. Supervised autonomy approaches are promising to increase quality and speed of control while keeping the flexibility to solve unknown tasks. We developed a set of operator assistance functionalities with different levels of autonomy to control the robot for challenging locomotion and manipulation tasks. The integrated system was evaluated in disaster response scenarios and showed promising performance.
RoboSimian @cite_17 is a quadrupedal robot with four generalized limbs, developed for the DRC. Each limb ends in an under-actuated hand which allows for solving both stepping locomotion and manipulation tasks. Furthermore, RoboSimian has two active wheels at its trunk and two caster wheels at its limbs which allow for driving on even terrain. The operator interface is a standard laptop from which the operator can design, parametrize, and sequence predefined behaviors. The DRC winner robot DRC-HUBO @cite_9 and the third placed platform CHIMP @cite_18 both have roughly anthropomorphic bodies. Both are capable of walking and driving via additional wheels tracks on their body. Both robots have two arms which end in hands with three fingers. Operation of DRC-HUBO is apportioned among three operators with different tasks which control the robot by selecting and adapting predefined poses while CHIMP is operated through task-specific motions which are configured through wizards by the operator before their execution.
@cite_9 @cite_18 @cite_17
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We present a general system with a focus on addressing three events of the 2013 DARPA Robotics Challenge DRC trials: debris clearing, door opening, and wall breaking. Our hardware platform is DRC-HUBO, a redesigned model of the HUBO2+ humanoid robot developed by KAIST and Rainbow, Inc. Our system allowed a trio of operators to coordinate a 32 degree-of-freedom robot on a variety of complex mobile manipulation tasks using a single, unified approach. In addition to descriptions of the hardware and software, and results as deployed on the DRC-HUBO platform, we present some qualitative analysis of lessons learned from this demanding and difficult challenge. We have developed the CHIMP CMU Highly Intelligent Mobile Platform robot as a platform for executing complex tasks in dangerous, degraded, human-engineered environments. CHIMP has a near-human form factor, work-envelope, strength, and dexterity to work effectively in these environments. It avoids the need for complex control by maintaining static rather than dynamic stability. Utilizing various sensors embedded in the robot's head, CHIMP generates full three-dimensional representations of its environment and transmits these models to a human operator to achieve latency-free situational awareness. This awareness is used to visualize the robot within its environment and preview candidate free-space motions. Operators using CHIMP are able to select between task, workspace, and joint space control modes to trade between speed and generality. Thus, they are able to perform remote tasks quickly, confidently, and reliably, due to the overall design of the robot and software. CHIMP's hardware was designed, built, and tested over 15i¾?months leading up to the DARPA Robotics Challenge. The software was developed in parallel using surrogate hardware and simulation tools. Over a six-week span prior to the DRC Trials, the software was ported to the robot, the system was debugged, and the tasks were practiced continuously. Given the aggressive schedule leading to the DRC Trials, development of CHIMP focused primarily on manipulation tasks. Nonetheless, our team finished 3rd out of 16. With an upcoming year to develop new software for CHIMP, we look forward to improving the robot's capability and increasing its speed to compete in the DRC Finals. This article presents the hardware design and software algorithms of RoboSimian, a statically stable quadrupedal robot capable of both dexterous manipulation and versatile mobility in difficult terrain. The robot has generalized limbs and hands capable of mobility and manipulation, along with almost fully hemispherical three-dimensional sensing with passive stereo cameras. The system is semiautonomous, enabling low-bandwidth, high latency control operated from a standard laptop. Because limbs are used for mobility and manipulation, a single unified mobile manipulation planner is used to generate autonomous behaviors, including walking, sitting, climbing, grasping, and manipulating. The remote operator interface is optimized to designate, parametrize, sequence, and preview behaviors, which are then executed by the robot. RoboSimian placed fifth in the DARPA Robotics Challenge Trials, demonstrating its ability to perform disaster recovery tasks in degraded human environments.