| 1. |
- Almeida, Diogo, 1991-, et al.
(författare)
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Asymmetric Dual-Arm Task Execution Using an Extended Relative Jacobian
- 2022
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Ingår i: Springer Proceedings in Advanced Robotics. - Cham : Springer International Publishing. - 2511-1264 .- 2511-1256. ; 20 SPAR, s. 18-34, s. 18-34
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Konferensbidrag (refereegranskat)abstract
- Coordinated dual-arm manipulation tasks can be broadly characterized as possessing absolute and relative motion components. Relative motion tasks, in particular, are inherently redundant in the way they can be distributed between end-effectors. In this work, we analyse cooperative manipulation in terms of the asymmetric resolution of relative motion tasks. We discuss how existing approaches enable the asymmetric execution of a relative motion task, and show how an asymmetric relative motion space can be defined. We leverage this result to propose an extended relative Jacobian to model the cooperative system, which allows a user to set a concrete degree of asymmetry in the task execution. This is achieved without the need for prescribing an absolute motion target. Instead, the absolute motion remains available as a functional redundancy to the system. We illustrate the properties of our proposed Jacobian through numerical simulations of a novel differential Inverse Kinematics algorithm.
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| 2. |
- Rodrigues, Vinayvivian, et al.
(författare)
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Kinetostatic Analysis for 6RUS Parallel Continuum Robot Using Cosserat Rod Theory
- 2024
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Ingår i: Springer Proceedings in Advanced Robotics. - 2511-1264 .- 2511-1256. ; 31 SPAR, s. 426-434
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Konferensbidrag (refereegranskat)abstract
- Parallel Continuum Robots (PCR) are closed-loop mechanisms but use elastic kinematic links connected in parallel between the end-effector (EE) and the base platform. PCRs are actuated primarily through large deflections of the interconnected elastic links unlike by rigid joints in rigid parallel mechanisms. In this paper, Cosserat rod theory-based forward and inverse kinetostatic models of a 6-RUS PCR are proposed. A set of simulations is performed to analyze the proposed PCR structure, including workspace analysis, maneuverability in three-dimensional space through trajectory following, assessment of inverse kinetostatic solutions for both the xy planar rotation, and evaluation of the force response at the EE platform along the z-axis.
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| 3. |
- Krishnan, S., et al.
(författare)
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SWIRL : A SequentialWindowed Inverse Reinforcement Learning Algorithm for Robot Tasks With Delayed Rewards
- 2020
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Ingår i: Springer Proceedings in Advanced Robotics. - Cham : Springer Nature. - 2511-1256. ; 13, s. 672-687
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Tidskriftsartikel (refereegranskat)abstract
- Inverse Reinforcement Learning (IRL) allows a robot to generalize from demonstrations to previously unseen scenarios by learning the demonstrator’s reward function. However, in multi-step tasks, the learned rewards might be delayed and hard to directly optimize. We present Sequential Windowed Inverse Reinforcement Learning (SWIRL), a three-phase algorithm that partitions a complex task into shorter-horizon subtasks based on linear dynamics transitions that occur consistently across demonstrations. SWIRL then learns a sequence of local reward functions that describe the motion between transitions. Once these reward functions are learned, SWIRL applies Q-learning to compute a policy that maximizes the rewards. We compare SWIRL (demonstrations to segments to rewards) with Supervised Policy Learning (SPL - demonstrations to policies) and Maximum Entropy IRL (MaxEnt-IRL demonstrations to rewards) on standard Reinforcement Learning benchmarks: Parallel Parking with noisy dynamics, Two-Link acrobot, and a 2D GridWorld. We find that SWIRL converges to a policy with similar success rates (60%) in 3x fewer time-steps than MaxEnt-IRL, and requires 5x fewer demonstrations than SPL. In physical experiments using the da Vinci surgical robot, we evaluate the extent to which SWIRL generalizes from linear cutting demonstrations to cutting sequences of curved paths.
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| 4. |
- Mahler, J., et al.
(författare)
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Synthesis of Energy-Bounded Planar Caging Grasps using Persistent Homology
- 2020
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Ingår i: Springer Proceedings in Advanced Robotics. - Cham : Springer Nature. - 2511-1256. ; 13, s. 416-431
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Tidskriftsartikel (refereegranskat)abstract
- Caging grasps restrict object motion without requiring complete immobilization, providing a robust alternative to force- and formclosure grasps. Energy-bounded cages are a new class of caging grasps that relax the requirement of complete caging in the presence of external forces such as gravity. In this paper, we address the problem of synthesizing energy-bounded cages by identifying optimal gripper and force-direction configurations that require the largest increases in potential energy for the object to escape. We present Energy-Bounded-Cage- Synthesis-2D (EBCS-2D), a sampling-based algorithm that uses persistent homology, a recently-developed multiscale approach for topological analysis, to efficiently compute candidate rigid configurations of obstacles that form energy-bounded cages of an object from an-shape approximation to the configuration space. We also show that constant velocity pushing in the horizontal plane generates an energy field analogous to gravity in the vertical plane that can be analyzed with our algorithm. EBCS-2D runs in time where s is the number of samples and n is the total number of object and obstacle vertices, where typically. We observe runtimes closer to O(s) for fixed n. We implement EBCS-2D using the Persistent Homology Algorithms Toolbox (PHAT) and study performance on a set of seven planar objects and four gripper types. Experiments suggest that EBCS-2D takes 2-3 minutes on a 6 core processor with 200,000 pose samples. We also confirm that an RRT* motion planner is unable to find escape paths with lower energy. Physical experiments suggest that push grasps synthesized by EBCS-2D are robust to perturbations. Additional proofs, data, and code are available at http://berkeleyautomation.github.io/caging/.
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| 5. |
- Varava, Anastasiia, et al.
(författare)
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Free Space of Rigid Objects : Caging, Path Non-existence, and Narrow Passage Detection
- 2020
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Ingår i: Springer Proceedings in Advanced Robotics. - Cham : Springer Science and Business Media B.V.. - 2511-1256. ; 14, s. 19-35
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we present an approach towards approximating configuration spaces of 2D and 3D rigid objects. The approximation can be used to identify caging configurations and establish path non-existence between given pairs of configurations. We prove correctness and analyse completeness of our approach. Using dual diagrams of unions of balls and uniform grids on SO(3), we provide a way to approximate a 6D configuration space of a rigid object. Depending on the desired level of guaranteed approximation accuracy, the experiments with our single core implementation show runtime between 5–21 s and 463–1558 s. Finally, we establish a connection between robotic caging and molecular caging from organic chemistry, and demonstrate that our approach is applicable to 3D molecular models. The supplementary material for this paper can be found at https://anvarava.github.io/publications/wafr-2018-supplementary-material.pdf.
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