An MPC Framework for Online Motion Planning in Human-Robot Collaborative Tasks

Mechanism and Machine Theory

Beschi

Visioli

et al. 2021

Self Cite

Robotized assembly and manufacturing often require to modify the robot motion at runtime. When the primary constraint is to preserve the geometrical path as much as possible, it is convenient to scale the nominal trajectory in time to meet the robot constraints. Look-ahead techniques are computationally heavy, while non-look-ahead ones usually show poor performance in critical circumstances. This paper proposes a novel technique that can be embedded in non-look-ahead scaling algorithms to improve their performance. The proposed method takes into account the robot velocity, acceleration, and torque limits and modifies the velocity profile based on an approximated look-ahead criterion. To do this, it considers only the last point of a look-ahead window and, by linearizing the problem, it computes the maximum admissible robot velocity. The technique can be applied to existing trajectory scaling algorithms to confer look-ahead properties on them. Simulation and experimental results on a 6-degree-of-freedom manipulator show that the proposed method significantly reduces path-following errors.

Section: Related Workmentioning

confidence: 99%

“…The trajectory scaling algorithms used in these works trace back to those described in the aforementioned approaches. In particular, [25] and [26] use non-look-ahead methods; [27] uses the look-ahead MPC-based approach described in [23].…”

Section: Related Workmentioning

confidence: 99%

A real-time trajectory planning method for enhanced path-tracking performance of serial manipulators

Mechanism and Machine Theory

Beschi

Visioli

et al. 2021

Self Cite

“…Several approaches have been proposed in the literature, including feedback techniques [4], [5], look-ahead methods [6], [7], and methods specific for redundant robots [8], [9]. Safety-oriented applications for HRC were proposed in [10], [11], [12]. All the aforementioned methods have pros and cons:…”

Section: A Related Workmentioning

confidence: 99%

Real-time trajectory scaling for robot manipulators

2020 17th International Conference on Ubiquitous Robots (UR)

Pagani

Legnani

2020

Self Cite

Recent developments in industrial robotics use real-time trajectory modification to improve throughput and safety in automatic processes. Online trajectory scaling is often used to this purpose. In this paper, we propose a feedback trajectory scaling approach that is able to recover from the delay introduced by the speed modulation and improves the path-following performance thanks to an additional inner control loop. Simulation and experimental results on an industrial 6-degree-of-freedom robot show the effectiveness of the proposed approach compared to standard algorithms.

“…Extra degrees of freedom can be exploited to endow the robot with desired secondary behaviors. To name a few examples, the redundancy can be exploited to: maximize the manipulability along selected axis [1], [2], keep the joint configuration far from the mechanical limits [3], mimic anthropomorphic motion [4], activate the least number of actuators [5], avoid collisions [6], [7], or maximize the distance from obstacles [8].…”

Section: Introductionmentioning

confidence: 99%

Inverse Kinematics of Redundant Manipulators With Dynamic Bounds on Joint Movements

IEEE Robot. Autom. Lett.

Beschi

Pedrocchi

2020

Self Cite

Redundant manipulators are usually required to perform tasks in the operational space, but collision-free path planning is computed in the configuration space. Limiting the deviation with respect to the collision-free configuration-space trajectory may allow the robot to avoid collisions without modifying the primary task. This paper proposes a method to guarantee that the solution of the inverse kinematic problem deviates from the nominal joint-space trajectory less than a desired threshold. The excursion limitation is ensured by means of linear constraints and the automatic regulation of the weights of secondary tasks. Numerical and experimental results prove the validness of the proposed approach.