The Experts below are selected from a list of 74859 Experts worldwide ranked by ideXlab platform
Weidong Chen - One of the best experts on this subject based on the ideXlab platform.
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hybrid vision force control of soft robot based on a deformation model
IEEE Transactions on Control Systems and Technology, 2021Co-Authors: Hesheng Wang, Jingchuan Wang, Weidong ChenAbstract:Soft robots are more safe than rigid robots in tasks with environmental interactions. To implement the interaction control for soft robots, this article proposes a hybrid vision force controller. The control law is based on a deformation model, which describes the deformation and the configuration of the soft robot under the effect of gravity and force applied on the tip. To control the motion of the tip, the Jacobian of soft robots is calculated to describe the actual relationship between actuation and tip motion. Then, the vision and force feedback are used to implement visual servo in motion-free Space and force control in motion-Constraint Space. The stability of the controller is verified both theoretically and experimentally.
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Hybrid Vision/Force Control of Soft Robot Based on a Deformation Model
IEEE Transactions on Control Systems Technology, 2021Co-Authors: Hesheng Wang, Jingchuan Wang, Weidong ChenAbstract:Soft robots are more safe than rigid robots in tasks with environmental interactions. To implement the interaction control for soft robots, this article proposes a hybrid vision force controller. The control law is based on a deformation model, which describes the deformation and the configuration of the soft robot under the effect of gravity and force applied on the tip. To control the motion of the tip, the Jacobian of soft robots is calculated to describe the actual relationship between actuation and tip motion. Then, the vision and force feedback are used to implement visual servo in motion-free Space and force control in motion-Constraint Space. The stability of the controller is verified both theoretically and experimentally.
Hesheng Wang - One of the best experts on this subject based on the ideXlab platform.
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hybrid vision force control of soft robot based on a deformation model
IEEE Transactions on Control Systems and Technology, 2021Co-Authors: Hesheng Wang, Jingchuan Wang, Weidong ChenAbstract:Soft robots are more safe than rigid robots in tasks with environmental interactions. To implement the interaction control for soft robots, this article proposes a hybrid vision force controller. The control law is based on a deformation model, which describes the deformation and the configuration of the soft robot under the effect of gravity and force applied on the tip. To control the motion of the tip, the Jacobian of soft robots is calculated to describe the actual relationship between actuation and tip motion. Then, the vision and force feedback are used to implement visual servo in motion-free Space and force control in motion-Constraint Space. The stability of the controller is verified both theoretically and experimentally.
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Hybrid Vision/Force Control of Soft Robot Based on a Deformation Model
IEEE Transactions on Control Systems Technology, 2021Co-Authors: Hesheng Wang, Jingchuan Wang, Weidong ChenAbstract:Soft robots are more safe than rigid robots in tasks with environmental interactions. To implement the interaction control for soft robots, this article proposes a hybrid vision force controller. The control law is based on a deformation model, which describes the deformation and the configuration of the soft robot under the effect of gravity and force applied on the tip. To control the motion of the tip, the Jacobian of soft robots is calculated to describe the actual relationship between actuation and tip motion. Then, the vision and force feedback are used to implement visual servo in motion-free Space and force control in motion-Constraint Space. The stability of the controller is verified both theoretically and experimentally.
Jingchuan Wang - One of the best experts on this subject based on the ideXlab platform.
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hybrid vision force control of soft robot based on a deformation model
IEEE Transactions on Control Systems and Technology, 2021Co-Authors: Hesheng Wang, Jingchuan Wang, Weidong ChenAbstract:Soft robots are more safe than rigid robots in tasks with environmental interactions. To implement the interaction control for soft robots, this article proposes a hybrid vision force controller. The control law is based on a deformation model, which describes the deformation and the configuration of the soft robot under the effect of gravity and force applied on the tip. To control the motion of the tip, the Jacobian of soft robots is calculated to describe the actual relationship between actuation and tip motion. Then, the vision and force feedback are used to implement visual servo in motion-free Space and force control in motion-Constraint Space. The stability of the controller is verified both theoretically and experimentally.
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Hybrid Vision/Force Control of Soft Robot Based on a Deformation Model
IEEE Transactions on Control Systems Technology, 2021Co-Authors: Hesheng Wang, Jingchuan Wang, Weidong ChenAbstract:Soft robots are more safe than rigid robots in tasks with environmental interactions. To implement the interaction control for soft robots, this article proposes a hybrid vision force controller. The control law is based on a deformation model, which describes the deformation and the configuration of the soft robot under the effect of gravity and force applied on the tip. To control the motion of the tip, the Jacobian of soft robots is calculated to describe the actual relationship between actuation and tip motion. Then, the vision and force feedback are used to implement visual servo in motion-free Space and force control in motion-Constraint Space. The stability of the controller is verified both theoretically and experimentally.
Mike Stilman - One of the best experts on this subject based on the ideXlab platform.
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planning in Constraint Space automated design of functional structures
International Conference on Robotics and Automation, 2013Co-Authors: Can Erdogan, Mike StilmanAbstract:On the path to full autonomy, robotic agents have to learn how to manipulate their environments for their benefit. In particular, the ability to design structures that are functional in overcoming challenges is imperative. The problem of automated design of functional structures (ADFS) addresses the question of whether the objects in the environment can be placed in a useful configuration. In this work, we first make the observation that the ADFS problem represents a class of problems in high dimensional, continuous Spaces that can be broken down into simpler subproblems with semantically meaningful actions. Next, we propose a framework where discrete actions that induce Constraints can partition the solution Space effectively. Subsequently, we solve the original class of problems by searching over the available actions, where the evaluation criteria for the search is the feasibility test of the accumulated Constraints. We prove that with a sound feasibility test, our algorithm is complete. Additionally, we argue that a convexity requirement on the Constraints leads to significant efficiency gains. Finally, we present successful results to the ADFS problem.
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ICRA - Planning in Constraint Space: Automated design of functional structures
2013 IEEE International Conference on Robotics and Automation, 2013Co-Authors: Can Erdogan, Mike StilmanAbstract:On the path to full autonomy, robotic agents have to learn how to manipulate their environments for their benefit. In particular, the ability to design structures that are functional in overcoming challenges is imperative. The problem of automated design of functional structures (ADFS) addresses the question of whether the objects in the environment can be placed in a useful configuration. In this work, we first make the observation that the ADFS problem represents a class of problems in high dimensional, continuous Spaces that can be broken down into simpler subproblems with semantically meaningful actions. Next, we propose a framework where discrete actions that induce Constraints can partition the solution Space effectively. Subsequently, we solve the original class of problems by searching over the available actions, where the evaluation criteria for the search is the feasibility test of the accumulated Constraints. We prove that with a sound feasibility test, our algorithm is complete. Additionally, we argue that a convexity requirement on the Constraints leads to significant efficiency gains. Finally, we present successful results to the ADFS problem.
Alexander Lubotzky - One of the best experts on this subject based on the ideXlab platform.
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STOC - Edge transitive ramanujan graphs and symmetric LDPC good codes
Proceedings of the 44th symposium on Theory of Computing - STOC '12, 2012Co-Authors: Tali Kaufman, Alexander LubotzkyAbstract:We present the first explicit construction of a binary symmetric code with constant rate and constant distance (i.e., good code). Moreover, the code is LDPC and its Constraint Space is generated by the orbit of one constant weight Constraint under the group action. Our construction provides the first symmetric LDPC good codes. In particular, it solves the main open problem raised by Kaufman and Wigderson {8}.
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Edge Transitive Ramanujan Graphs and Highly Symmetric LDPC Good Codes
arXiv: Information Theory, 2011Co-Authors: Tali Kaufman, Alexander LubotzkyAbstract:We present a symmetric LDPC code with constant rate and constant distance (i.e. good LDPC code) that its Constraint Space is generated by the orbit of one constant weight Constraint under a group action. Our construction provides the first symmetric LDPC good codes. This solves the main open problem raised by Kaufman and Wigderson in [4].