A Dynamic Programming Framework for Optimal Planning of Redundant Robots Along Prescribed Paths With Kineto-Dynamic Constraints

Off-line optimal planning of trajectories for redundant robots along prescribed task space paths is usually broken down into two consecutive processes: first, the task space path is inverted to obtain a joint-space path, then, the latter is parametrized with a time law. If the two processes are separated, they cannot optimize the same objective function, ultimately providing sub-optimal results. In this paper, a unified approach is presented where dynamic programming is the underlying optimization technique. Its flexibility allows accommodating arbitrary constraints and objective functions, thus providing a generic framework for optimal planning of real systems. To demonstrate its applicability to a real world scenario, the framework is instantiated for time-optimality. Compared to numerical solvers, the proposed methodology provides visibility of the underlying resolution process, allowing for further analyses beyond the computation of the optimal trajectory. The effectiveness of the framework is demonstrated on a real 7-degrees-of-freedom serial chain. The issues associated with the execution of optimal trajectories on a real controller are also discussed and addressed. The experiments show that the proposed framework is able to effectively exploit kinematic redundancy to optimize the performance index defined at planning level and generate feasible trajectories that can be executed on real hardware with satisfactory results

Application of Fractional Calculus in the Dynamical Analysis and Control of Mechanical Manipulators

Mathematics Subject Classification: 26A33, 93C83, 93C85, 68T40Fractional Calculus (FC) goes back to the beginning of the theory of differential calculus. Nevertheless, the application of FC just emerged in the last two decades. In the field of dynamical systems theory some work has been carried out but the proposed models and algorithms are still in a preliminary stage of establishment. This article illustrates several applications of fractional calculus in robot manipulator path planning and control

Mechatronics versus Robotics

In Bolton, mechatronics is defined as the integration of electronics, control engineering, and mechanical engineering, thus recognizing the fundamental role of control in joining electronics and mechanics. A robot is commonly considered as a typical mechatronic system, which integrates software, control, electronics, and mechanical designs in a synergistic manner. Robotics can be considered as a part of mechatronics; i.e., all robots are mechatronic systems, but not all mechatronic systems are robots. Advanced robots usually plan their actions by combining an assigned functional task with the knowledge about the environment in which they operate. By using a simplified approach, advanced robots could be defined as mechatronic devices governed by a smart brain, placed at a higher hierarchical level. Actuators are building blocks of any mechatronic system. Such systems, however, have a huge application span, ranging from low-cost consumer applications to high-end, high-precision industrial manufacturing equipment

Toward on-line robot vibratory modes estimation

International audienceThis paper is concerned with preliminary results on robot vibratory modes on-line estimation. The dominating oscillatory mode of the robot arm is isolated by comparing the robot position given by the motors encoders and an external measure at the tool-tip of the robot arm. In this article the external measurement is provided by a laser tracker. The isolation of the oscillation permits to identify the vibratory mode, \textit{i.e.} the natural frequency and the damping ratio of the undesired phenomena. Here we propose a comparison between the algebraic method and the sliding modes for the parameter identification. This comparison is motivated by the fact that both methods provide finite time convergence. Experimental identifications are proposed on a 6 degrees of freedom (DOF) manipulator robot, Stäubli RX-170B

Optimization of Generalized S-curve Trajectories for Residual Vibration Suppression and Compliance with Kinematic Bounds

This paper proposes a new optimization algorithm that assures the minimum possible duration of generalized S-curve trajectories compliant with kinematic limitations and capable of suppressing residual vibrations when tracked by a resonant plant. Thanks to the possibility of generating such kind of trajectories with a chain of filters, called smoothers, each one characterized by a single parameter, i.e. the duration Ti of its impulse response, the optimization process aims at minimizing the order of the trajectory, and accordingly the number of smoothers in the chain, and leads to rest-to-rest trajectories that, under the given specifications, cannot be made shorter in time. Therefore, the structure of the trajectory is not predetermined but is the outcome of the proposed algorithm together with the optimal parameters defining it. The effectiveness of the proposed approach is proven by applying the designed trajectories to an experimental setup based on a flexible link

An approach of optimising S-curve trajectory for a better energy consumption

In today's manufacturing industry, higher productivity and sustainability should go hand-in-hand. This practice is motivated by governmental regulations as well as customers' awareness. For the current time, one of the inexpensive solutions is motion planning for an improved energy consumption. This paper introduces a general approach that is valid for testing and optimising energy consumption of the input motion profile. The Particle Swarm Optimisation method (PSO) is used because of its mathematical simplicity and quick convergence. Being commonly used, s-curve motion profile is reconstructed and optimised for a better energy consumption. The results show potential energy reduction and better positioning for the system configured according to the optimised s-curve

Smooth Spline-based Trajectory Planning for Semi-Rigid Multi-Robot Formations

This paper presents an approach for smooth trajectory planning in semi-rigid nonholonomic mobile robot formations using Bezier-splines. Unlike most existing approaches, the focus is on maintaining a semi-rigid formation, as required in many scenarios such as object transport, handling or assembly. We use a Relaxed A* planner to create an optimal collision-free global path and then smooth this path using splines. The smoothed global path serves to create target paths for every robot in the formation. From these paths, we then calculate the trajectories for each robot. In an iterative process, we match the velocities of the robots so that all trajectories are synchronized, and the dynamic limits of all robots are maintained. We provide experimental validation, which confirms no violation of the dynamic limits and shows an excellent control performance for a system of three robots moving at 0.3 m/s

Towards Autonomous Selective Harvesting: A Review of Robot Perception, Robot Design, Motion Planning and Control

This paper provides an overview of the current state-of-the-art in selective harvesting robots (SHRs) and their potential for addressing the challenges of global food production. SHRs have the potential to increase productivity, reduce labour costs, and minimise food waste by selectively harvesting only ripe fruits and vegetables. The paper discusses the main components of SHRs, including perception, grasping, cutting, motion planning, and control. It also highlights the challenges in developing SHR technologies, particularly in the areas of robot design, motion planning and control. The paper also discusses the potential benefits of integrating AI and soft robots and data-driven methods to enhance the performance and robustness of SHR systems. Finally, the paper identifies several open research questions in the field and highlights the need for further research and development efforts to advance SHR technologies to meet the challenges of global food production. Overall, this paper provides a starting point for researchers and practitioners interested in developing SHRs and highlights the need for more research in this field.Comment: Preprint: to be appeared in Journal of Field Robotic

Survey on model-based manipulation planning of deformable objects

A systematic overview on the subject of model-based manipulation planning of deformable objects is presented. Existing modelling techniques of volumetric, planar and linear deformable objects are described, emphasizing the different types of deformation. Planning strategies are categorized according to the type of manipulation goal: path planning, folding/unfolding, topology modifications and assembly. Most current contributions fit naturally into these categories, and thus the presented algorithms constitute an adequate basis for future developments.Preprin