Team RoboSimian: Semi-autonomous Mobile Manipulation at the 2015 DARPA Robotics Challenge Finals

Karumanchi, Sisir; Edelberg, Kyle; Baldwin, Ian; Nash, Jeremy; Satzinger, Brian; Reid, John E.; Bergh, Charles F.; Lau, Chelsea; Leichty, John; Carpenter, Kalind; Shekels, Matthew; Gildner, Matthew; Newill-Smith, David; Carlton, Jason; Koehler, John; Dobreva, Tatyana; Frost, Matthew; Borders, James; Ma, Jie; Douillard, Bertrand; Shankar, Krishna; Byl, Katie; Burdick, Joel W.; Backes, Paul; Kennedy, Brett

doi:10.1007/978-3-319-74666-1_6

Cited by 26 publications

(36 citation statements)

References 33 publications

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“…The JPL Team details their hardware design, algorithms, and system for ROBOSIMIAN in [2] and [13]. Their semiautonomous system utilizes a behavior planner and stored motion primitives along with nonlinear trajectory optimization and review and approval of candidate plans by a human supervisor, with the operator also assisting in object fitting.…”

Section: A Backgroundmentioning

confidence: 99%

“…Email: wolfgang.merkt@ed.ac.uk. 2 Oxford Robotics Institute, University of Oxford (Felstead House, 23 Banbury Road, Oxford, OX2 6NN, United Kingdom). Fig.…”

Section: Introductionmentioning

confidence: 99%

“…Robotics Challenge (DRC) Finals in July 2015 for controlled, mostly static environments ("high-level repeatable and lowlevel adaptable", [2]). However, more or fully autonomous systems are challenging in dynamic and unpredictable environments with clutter due to the sheer complexity of dealing with rare events.…”

Section: Introductionmentioning

confidence: 99%

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Robust shared autonomy for mobile manipulation with continuous scene monitoring

Merkt

Yang

Stouraitis

et al. 2017

2017 13th IEEE Conference on Automation Science and Engineering (CASE)

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This work presents a fully integrated system for reliable grasping and manipulation using dense visual mapping, collision-free motion planning, and shared autonomy. The particular motion sequences are composed automatically based on high-level objectives provided by a human operator, with continuous scene monitoring during execution automatically detecting and adapting to dynamic changes of the environment. The system is able to automatically recover from a variety of disturbances and fall back to the operator if stuck or if it cannot otherwise guarantee safety. Furthermore, the operator can take control at any time and then resume autonomous operation. Our system is flexible to be adapted to new robotic systems, and we demonstrate our work on two real-world platformsfixed and floating base -in shared workspace scenarios.To the best of our knowledge, this work is also the first to employ the inverse Dynamic Reachability Map for realtime, optimized mobile base positioning to maximize workspace manipulability reducing cycle time and increasing planning and autonomy robustness.

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Section: A Backgroundmentioning

confidence: 99%

“…Email: wolfgang.merkt@ed.ac.uk. 2 Oxford Robotics Institute, University of Oxford (Felstead House, 23 Banbury Road, Oxford, OX2 6NN, United Kingdom). Fig.…”

Section: Introductionmentioning

confidence: 99%

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Robust shared autonomy for mobile manipulation with continuous scene monitoring

Merkt

Yang

Stouraitis

et al. 2017

2017 13th IEEE Conference on Automation Science and Engineering (CASE)

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“…When these connections become latent or otherwise poor, the role of the human operator must necessarily be reduced. The most common method for accommodating poor communications is to increase autonomous functions, either in the robotic system, in the user interfaces, or both [7,8]. As autonomous functionalities take on more decision making roles for a task, the control mode transitions from teleoperation to supervisory control.…”

Section: Introductionmentioning

confidence: 99%

Supervisory control of a humanoid robot in microgravity for manipulation tasks

Farrell

Strawser

Hambuchen

et al. 2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-Teleoperation is the dominant form of dexterous robotic tasks in the field. However, there are many use cases in which direct teleoperation is not feasible such as disaster areas with poor communication as posed in the DARPA Robotics Challenge, or robot operations on spacecraft a large distance from Earth with long communication delays. Presented is a solution that combines the Affordance Template Framework for object interaction with TaskForce for supervisory control in order to accomplish high level task objectives with basic autonomous behavior from the robot. TaskForce, is a new commanding infrastructure that allows for optimal development of task execution, clear feedback to the user to aid in off-nominal situations, and the capability to add autonomous verification and corrective actions. This framework has allowed the robot to take corrective actions before requesting assistance from the user. This framework is demonstrated with Robonaut 2 removing a Cargo Transfer Bag from a simulated logistics resupply vehicle for spaceflight using a single operator command. This was executed with 80% success with no human involvement, and 95% success with limited human interaction. This technology sets the stage to do any number of high level tasks using a similar framework, allowing the robot to accomplish tasks with minimal to no human interaction.

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“…For instance, Schaft as one more DoF on its legs on the sagittal plane. More generally in the context of the DARPA Robotics Challenge (DRC) [11], RO-BOSIMIAN from JPL [36] and CHIMP [60] from CMU are ape-like robots which allow to perform more extended locomotion modes than bipedal ones. S-One has highly redundant arms which permit to avoid singularities and kinematic limits.…”

Section: Robot Skeletonmentioning

confidence: 99%