In the eye-in-hand robot configuration, hand-eye calibration plays a vital role in completing the link between the robot and camera coordinate systems. Calibration algorithms are mature and provide accurate transforma...
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In the eye-in-hand robot configuration, hand-eye calibration plays a vital role in completing the link between the robot and camera coordinate systems. Calibration algorithms are mature and provide accurate transformation estimations for an effective camera-robot link but rely on a sufficiently wide range of calibration data to avoid errors and degenerate configurations. This can be difficult in the context of keyhole surgical robots because they are mechanically constrained to move around a remote centre of motion (RCM) which is located at the trocar port. The trocar limits the range of feasible calibration poses that can be obtained and results in ill-conditioned hand-eye constraints. In this letter, we propose a new approach to deal with this problem by incorporating the RCM constraints into the hand-eye formulation. We show that this not only avoids ill-conditioned constraints but is also more accurate than classic hand-eye calibration with a free 6DoF motion, due to solving simpler equations that take advantage of the reduced DoF. We validate our method using simulation to test numerical stability and a physical implementation on an RCM constrained KUKA LBR iiwa 14 R820 equipped with a NanEye stereo camera.
This letter addresses the problem of vehicle path planning in the presence of obstacles and uncertainties, a fundamental robotics problem. While several path planning algorithms have been proposed over the years, many...
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This letter addresses the problem of vehicle path planning in the presence of obstacles and uncertainties, a fundamental robotics problem. While several path planning algorithms have been proposed over the years, many of them have dealt with only deterministic environments orwith only open-loop uncertainty, i.e., the uncertainty of the system state is not controlled and, typically, increases with time because of exogenous disturbances. This may lead to potentially conservative nominal paths. The typical approach to deal with disturbances and reduce uncertainty is to use a lower level feedback controller. We advocate the premise that, if a path planner can consider the closed-loop evolution of the system uncertainty, it can lead to less conservative, but still feasible, paths. To this end, in this letter, we develop an approach that is based on optimal covariance steering, which explicitly steers the state covariance for stochastic linear systems. We verify the proposed framework using extensive numerical simulations.
When robotic manipulators perform high-level tasks in the presence of another agent, e.g., a human, they must have a strategy that considers possible interferences in order to guarantee task completion and efficient r...
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When robotic manipulators perform high-level tasks in the presence of another agent, e.g., a human, they must have a strategy that considers possible interferences in order to guarantee task completion and efficient resource usage. One approach to generate such strategies is called reactive synthesis. Reactive synthesis requires an abstraction, which is a discrete structure that captures the domain in which the robot and other agents operate. Existing works discuss the construction of abstractions for mobile robots through space decomposition;however, they cannot be applied to manipulation domains due to the curse of dimensionality caused by the manipulator and the objects. In this work, we present the first algorithm for automatic abstraction construction for reactive synthesis of manipulation tasks. We focus on tasks that involve picking and placing objects with possible extensions to other types of actions. The abstraction also provides an upper bound on path-based costs for robot actions. We combine this abstraction algorithm with our reactive synthesis planner to construct correct-by-construction plans. We demonstrate the power of the framework on aUR5robot, completing complex tasks in face of interferences by a human.
In this letter, we propose methods to perform swarm behavior analysis with a novel swarm signal temporal logic (SwarmSTL). We define generalized moments to describe swarm features and propose a logical proposition to ...
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In this letter, we propose methods to perform swarm behavior analysis with a novel swarm signal temporal logic (SwarmSTL). We define generalized moments to describe swarm features and propose a logical proposition to represent an event, where the Boolean value of the logical proposition at a certain time is known a priori. We develop methods for SwarmSTI, monitoring and inference. As the swarm size can be large, we also propose methods to perform the above tasks by sampling. The methods are applied to three case studies that aim to monitor swarm "maneuver" behavior, infer a SwarmSTE, formula to describe the cause of split, and explore a SwarmSTL formula to describe "mixed-species foraging flock" of birds.
Smooth position and orientation interpolation has a great effect on the performance of robot manipulators. Interpolation between several via positions can be done in a straightforward manner, which is well covered in ...
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Smooth position and orientation interpolation has a great effect on the performance of robot manipulators. Interpolation between several via positions can be done in a straightforward manner, which is well covered in the literature. However, generating a suitable trajectory between several orientations is still an open problem. In this letter, we introduce a novel trajectory generator capable of respecting kinematic limits. We address the problem of generating a singularity-free trajectory for multiple via poses in SE(3), while complying with the requirement of C-4 continuity. To achieve this, a smooth trapezoidal-like velocity profile and unit quaternions are used. A simulation platform in V-REP based on a 7-DOF lightweight robot, including inverse kinematics and dynamics is used to demonstrate the effectiveness of our trajectory generator.
How to build a biomimetic robot fish has always been a divergent question. Most of the existing robot fishes suffer structural complexity and propulsive inefficiency. In this paper, we proposed a method that transfers...
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How to build a biomimetic robot fish has always been a divergent question. Most of the existing robot fishes suffer structural complexity and propulsive inefficiency. In this paper, we proposed a method that transfers the natural actuation properties of fish to the biomimetic robot counterpart. The natural properties were analyzed based on the Lighthill fish swimming model and the actuation function of fish muscles. The analyses shown that the compliant part is feasible in fish propulsion, which means nonactuated/compliant part is also feasible to achieve an effective propulsion on robot fish, and an example of this type of robot fish and its general kinematic model are presented. This transform method not only can demonstrate the actuation features of fish, but also can reduce the motors in building robot fish. The method has also been extended to apply on different swimming modes, offering a general guidance to build efficient biomimetic robot fishes with fewer motors.
This letter presents a path planning algorithm for generating a cost-efficient path that satisfies mission requirements specified in linear temporal logic (LTL). We assume that a cost function is defined over the conf...
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This letter presents a path planning algorithm for generating a cost-efficient path that satisfies mission requirements specified in linear temporal logic (LTL). We assume that a cost function is defined over the configuration space. Examples of a cost function include hazard levels, wireless connectivity, and energy consumption, to name a few. The proposed method consists of two parts: sampling-based cost-aware path planning considering the vehicle dynamics based on rapidly-exploring random trees (RRT*), and a high-level logic which determines how to extend the RRT tree based on spatiotemporal specifications of an LTL formula. In order to find a low-cost trajectory with computational efficiency, the proposed method expands the RRT tree with long extensions using cross entropy, while the rewiring step of RRT* is used to preserve the asymptotic optimality. In simulation and experiments, we show that the proposed method performs favorably compared to existing methods.
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