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In highly dynamic tasks that involve moving targets, planning is necessary to figure out when, where and how to intercept the target. In robotic table tennis in particular, motion planning can be very challenging due to time constraints, dimension of the search space and modelling uncertainties. To simplify the problem, conventional planning algorithms often rely on a fixed virtual hitting plane to...
Inertial reorientation of airborne articulated bodies has been an active area of research in the robotics community, as this behavior can help guide dynamic robots to a safe landing with minimal damage. The main objective of this work is emulating the aggressive and large angle correction maneuvers, like somersaults, that are performed by human divers. To this end, a planar three link robot, called...
Time-optimal motion planning for robotic manipulators consists of moving the robot along a path in Cartesian space as fast as possible. In contrast to time-optimal path following, small deviations from a predefined path are acceptable and can be exploited to further reduce the overall motion time. In this paper, we present a new method to compute time-optimal motions around a path. By employing an...
This paper addresses the problem of constrained motion for a manipulator performing a task while in contact with the environment, and investigates two force control frameworks, one based on projected inverse dynamics, and one based on optimal control. Firstly, we propose a control method based on projected inverse dynamics, which directly exploits the contact constraints to minimise the instantaneous...
This paper proposes a method to determine the optimal value of design parameters in robots driven by variable-stiffness actuators. The method consists of setting up a nonlinear optimization problem, the solution of which determines the optimal control sequence, and, at the same time, the optimal values of the parameters. As a case study, we analyze a ball-throwing problem for a two-link elbow manipulator...
In this paper, a Lagrangian decomposition scheme for the agent based distributed dynamic optimization of coupled nonlinear continuous-time systems is presented. In contrast to existing decomposition schemes, each agent is augmented with approximate dynamics of the coupled neighbor agents, thus enabling the agent to anticipate the dynamic behavior of his neighbors. The performance of the presented...
This paper aims at combining state of the art developments of path planning and optimal control and to create the algorithmic foundations to tackle optimal control problems in cluttered environments. Our contribution is three-fold: first, we describe a simple method to automatically generate minimum bounding capsules around exact robot body geometries represented by meshes. Second, we use the bounding...
We propose distributed algorithms to automatically deploy a group of robotic agents and provide coverage of a discretized environment represented by a graph. The classic Lloyd approach to coverage optimization involves separate centering and partitioning steps and converges to the set of centroidal Voronoi partitions. In this work we present a novel graph coverage algorithm which achieves better performance...
A new algorithm based on Evolutionary Strategies is proposed for finding a robot manipulation path. Next scenario is considered: Given a learned Manipulation Path in the space of configurations, a real-time optimal path is calculated when mobile robot base is in a different position and orientation near to the original localization. The optimization problem is formulated as the minimization of the...
Online optimal planning of robotic arm movement is addressed. Optimality is inspired by computational models, where a “cost function” is used to describe limb motions according to different criteria. A method is proposed to implement optimal planning in Cartesian space, minimizing some cost function, by means of numerical approximation to a generalized nonlinear model predictive control problem. The...
This paper presents a polar-space optimal kinematic controller design based on ant colony optimization (ACO) computing method for omnidirectional mobile robots with three independent driving wheels equally spaced at 120 degrees from one another. The optimal control parameters are obtained by minimizing the performance index using the proposed ACO computing method. These optimal parameters are used...
This paper presents an optimal kinematic controller design based on ant colony optimization (ACO) computing method for omnidirectional mobile robots with three independent driving wheels equally spaced at 120 degrees from one another. The optimal control parameters are obtained by minimizing the performance index using the proposed ACO computing method. These optimal parameters are used in the ACO-based...
We present successful control strategies for dynamically stable robots that avoid low ceilings and other vertical obstacles in a manner similar to limbo dances. Given the parameters of the mission, including the goal and obstacle dimensions, our method uses a sequential composition of IO-linearized controllers and applies stochastic optimization to automatically compute the best controller gains and...
We present a novel approach to legged locomotion over rough terrain that is thoroughly rooted in optimization. This approach relies on a hierarchy of fast, anytime algorithms to plan a set of footholds, along with the dynamic body motions required to execute them. Components within the planning framework coordinate to exchange plans, cost-to-go estimates, and “certificates” that ensure the output...
The formulation and solution of a minimum time optimal control problem for a formation conformed by nonholonomic car-like mobile robots and a virtual leader reaching a target zone in an environment that includes dynamic and static obstacles with arbitrary shapes, is provided in this paper. The proposed approach for solving the formation to target zone minimum time problem, is formulated using receding...
This work presents a solution to solve industrial cranes kinematic control problem also called automatic travel control (ATC) [10]. Aspects such as optimal trajectory reference calculation considering: process cycle time and distance travelled minimization, improvements in mechanical transmission systems useful life, prohibited areas and obstacles in the crane workspace, etc., and load position control...
This study presents several measures aimed at mathematically quantifying characteristics associated with human performance and wearable robot platform; there will be trials for improving the kinematic performance of the proposed wearable robot system through the optimization methodology. Within constrained conditions, optimal link lengths will be defined for its objectives and purposes. In particular,...
Integrating the feature of the mission and mission region of the multiple robots, taking the total rewards of the group of robots, movement nonholonomic constraints and the survival probability of the threatening area and the collision avoidance between robots into account, a reasonable objective function and constrains are formulated. Cooperative Receding Horizon Control Strategy (CRH) and Genetic...
This article presents a novel on-line optimal control for tracking tasks on redundant robot manipulators for which inverse kinematics is not required. The controller is composed by a stabilization Cartesian PID control plus a joint space optimal control, which is in charge of improving tracking performance. The joint space dynamic optimal control is based on the gradient flow approach with the robot...
The paper presents a multi-objective optimum design procedure to a 3 degrees of freedom (DOF) parallel robot with regards to four optimality criteria: workspace boundary, transmission quality index, stiffness and numerical aspects. Additional objective functions can be used to extend the proposed design procedure to more general but specific design problems. The main aspects of their structure, kinematics,...
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