Collision-free Planning Research Articles

Obstacle Intention Awareness in Automatic Ship Collision Avoidance: Full-Scale Experiments in Confined Waters

In this article, full-scale experiments with a dynamic obstacle intention-aware Collision Avoidance System (CAS) are presented. The CAS consists of the Probabilistic Scenario-Based Model Predictive Control (PSB-MPC) for trajectory planning, dynamic obstacle avoidance, and antigrounding, with a Dynamic Bayesian Network (DBN) used for inferring obstacle intentions online. The novelty of this article lies in the utilization of intention information in deliberate collision-free planning. By inferring multiple different intention states on how and if nearby obstacles adhere to the COLREGS, the PSB-MPC can plan COLREGS-compliant avoidance maneuvers when possible, taking into account its awareness of the situation. The experiments put emphasis on hazardous situations where this intention information is both useful and necessary in order to avoid high collision risk. To the authors’ knowledge, the work is the first field experimental validation of such a probabilistic intention-aware CAS with consideration of multiple intention states. The experimental results demonstrate the validity of the proposed CAS scheme, with adherence to the traffic rules (COLREGS) 7, 8 and 13–17 in a diverse set of situations. The strengths and weaknesses of the proposed CAS are also discussed, giving insights that can be useful for researchers and practitioners in the field. Here, challenges related to detecting obstacle maneuvers and making the intention inference more robust to noise should be addressed as future work to make the scheme better suited for general usage on ships engaged in real traffic.

A Collision-Free Planning and Control Framework for a Biomimetic Underwater Vehicle in Dynamic Environments

A Collision-Free Planning and Control Framework for a Biomimetic Underwater Vehicle in Dynamic Environments

Learning-based collision-free planning on arbitrary optimization criteria in the latent space through cGANs

We propose a new method for collision-free planning using Conditional Generative Adversarial Networks (cGANs) to transform between the robot's joint space and a latent space that captures only collision-free areas of the joint space, conditioned by an obstacle map. Generating multiple plausible trajectories is convenient in applications such as the manipulation of a robot arm by enabling the selection of trajectories that avoids collision with the robot or surrounding environment. In the proposed method, various trajectories that avoid obstacles can be generated by connecting the start and goal state with arbitrary line segments in this generated latent space. Our method provides this collision-free latent space, after which any planner, using any optimization conditions, can be used to generate the most suitable paths on the fly. We successfully verified this method with a simulated and actual UR5e 6-DoF robotic arm. We confirmed that different trajectories could be generated depending on optimization conditions.

Which MAPF Model Works Best for Automated Warehousing?

Multi-Agent Path Finding (MAPF) algorithms and their variants can find high-quality collision-free plans for automated warehousing under simplified assumptions about the robot dynamics. However, these simplifying assumptions pose challenging implementational issues as the robots cannot follow the plans precisely. Various robust execution frameworks, such as the Action Dependency Graph (ADG) framework, have been proposed to enable the real-world execution of MAPF plans. Under such a framework, it is unclear how the simplifying assumptions affect the performance of the robots. In this work, we first argue that the ADG framework provides the same robustness guarantees as the single-agent framework (where plans are generated independently for each robot and collisions are avoided through a reservation table), which is widely used in industry. We then improve the efficiency of the ADG framework by integrating it with the Rolling-Horizon Collision-Resolution framework to solve MAPF problems with a persistent stream of online tasks. Using the integrated framework, we compare the standard MAPF model with many of its more complex variants, such as MAPF with rotation, k-robust MAPF, and continuous-time MAPF (taking robot dynamics into account). We examine their effectiveness in improving throughput through realistic simulations of warehouse settings with the Gazebo simulator.

Collision-free path planning based on new navigation function for an industrial robotic manipulator in human-robot coexistence environments

ABSTRACT This paper presents a method for real-time collision-free path planning that uses a new navigation function for environments in which humans and robots cooperate or coexist, which guarantees the safety of a human operator who works with a collaborative robot. This method follows 10 skeletal joints in a human operator, which are detected using an RGB-D sensor, in order to detect humans. A new navigation function ensures collision-free planning for a robotic manipulator that avoids local minima and generates a shorter path. Simulation results show the effectiveness of the proposed method in comparison to two existing methods. The applicability and practicability of the proposed method are demonstrated by experiments using a 6-DoF industrial manipulator HIWIN RA605 with an RGB-D vision sensor (Kinect V1), a real-time operation system extension (RTX64) and an EtherCAT network protocol.

Optimal Scheduling and Model Predictive Control for Trajectory Planning of Cooperative Robot Manipulators

Abstract A hierarchical control approach for cooperative pick-and-place tasks in a narrow shared workspace is proposed. A scenario with two robot arms performing pick-and-place tasks with moving objects while ensuring collision-free planning and execution of their respective trajectories is specifically addressed. To this end, we consider a hierarchical architecture with two-layer optimization-based control policies involving task scheduling in the top layer and path planning, along with the motion constraints, at the bottom one. On the one hand, for task allocation, a distance minimization algorithm is introduced, leading to an integer optimization problem with linear constraints and a bilinear cost function. On the other hand, we invoke model-based collision-free minimum-time planning of robot trajectories. Hereby, inverse robot dynamics and time scaling appear to be useful tools. The former accounts for the compensation of nonlinear robot dynamics, while the latter converts the trajectory planning to a fixed-time optimization problem, thus enabling synchronous robot task executions.

Shadow Space Modeling and Task Planning for Collision-free Cooperation of Dual Manipulators for Planar Task

Planning the manipulators’ task sequences is necessary for proper execution of specific robotic tasks. With multiple manipulators for cooperative tasks, planning becomes difficult owing to possible collisions between component manipulators. This paper proposes a shadow space approach that utilizes the swept area of a robot during its motion, for collision-free task planning of dual manipulators. A collision can be detected and prevented by computing the intersection of two manipulators’ shadow spaces. Then, a novel genetic algorithm with mutually exclusive chromosomes is proposed to search optimal collision-free task sequences for dual manipulators. For a pragmatic example of placing pemnuts onto the back-chassis of a liquid crystal device (LCD) panel, experiments and simulation show that the proposed method can determine a nearly optimal sequence, which allows two manipulators to move cooperatively without collisions, even though they share a common workspace.

Collision-free planning algorithm of motion path for the robot belt grinding system

Collision may occur during the grinding of a workpiece by a robot sand belt. To solve this problem, a collision-free planning algorithm for the robot motion path is developed based on the collision layer method. Collision-free planning of the robot motion path is studied, and a means to adjust the machining frame on the belt is determined (i.e. moving along the axis of the belt and rotating around the tangent line). The planning curve is rapidly found on the collision layer using neighborhood search and recursive methods, and the amount of collision detection is significantly reduced. The planning curve is transformed into the robot motion path. Simulation and experimentation show that the amount of collision detection required by the proposed algorithm is 3.86% less than that required by a method using a complete collision layer. Moreover, the robot grinds the workpiece without collision. The proposed method is simple, stable, and easy to implement and possesses a good engineering application value.

Closed-Loop Global Motion Planning for Reactive, Collision-Free Execution of Learned Tasks

We present a robot motion planning approach for performing a learned task while reacting to the movement of obstacles and task-relevant objects. We employ a closed-loop, sampling-based motion planner operating multiple times a second that senses obstacles and task-relevant objects and generates collision-free motion plans based on a learned-task model. The task model is learned from expert demonstrations prior to task execution and is represented as a hidden Markov model. During task execution, our motion planner quickly searches in the Cartesian product of the task model and a probabilistic roadmap for a collision-free plan with features most similar to the demonstrations given the current locations of the task-relevant objects. We accelerate replanning using a fast bidirectional search and by biasing the sampling distribution using information from the learned-task model. We show the efficacy of our approach with the Baxter robot performing two tasks.

EP-1769: Collision-free planning of trajectories for conventional radiotherapy

EP-1769: Collision-free planning of trajectories for conventional radiotherapy

Automatic Conflict Solving using Biharmonic Navigation Functions

Automatic conflict solving is an old standing problem within the field of ATM. Proposed algorithms fall into two categories:.•Deterministic ones that have a provable property of collision avoidance. For all known algorithms, trajectories produced are generally not flyable because no bounds on speed and curvature can be imposed.•Stochastic methods that select an optimal sequence of manoeuvres. By design, trajectories are flyable, but no guarantee can be given on the fact that a collision-free planning can be found in finite time.It is highly desirable for a wide social acceptance of automated trajectory planning, even at a strategical level, that the algorithms in use have by-design the collision avoidance property and, at the same time, a mean of keeping the speed within a given interval. Navigation functions are common in the field of robotics but do not have the last property. We present in this paper a new approach based on biharmonic functions yielding a navigation field with constant speed. Such functions have been considered previously, but proof of collision avoidance is lacking: we address this problem in this work as summarized below. Navigation functions produce a speed field by taking the gradient of a potential function: if the obstacles to be avoided are at a higher potential than inner points of the domain (including destination), collision avoidance is guaranteed. If the potential has the Morse property (no critical point is degenerated) then there exists a descent direction at every point of the admissible domain, making the destination reachable. In the framework of biharmonic functions, a tensor field is produced instead of a vector one; the Morse property is no longer relevant. We show here that all benefits of navigation functions can be recovered through the use of the bienergy density τ2, with the ability to get constant speed fields.

Augmented reality for port placement and navigation in robotically assisted minimally invasive cardiovascular surgery

Optimal port placement and intra-operative navigation in robotically assisted minimally invasive cardiovascular surgery are essential for the improvement and success of a teleoperator-based heart operation. A new system incorporating both port placement planning and intra-operative navigation was established. Offline the optimal port placement is planned on a three-dimensional virtual reconstruction of the patient's computed tomography scan. Using this planned data, an accurate in vivo port placement can be performed, which is achieved by augmented reality techniques superimposing virtual models of the thorax and the teleoperator arms on their real world counterparts. A significant reduction of operation time may be obtained by a precise and collision-free planning and placement of teleoperator arms. Collision detection techniques are expected to allow for avoidance of consecutive new port placement by detecting intersections of instruments among each other and with the patient's anatomy. Endoscopic failure or switching to open surgery may be evaded.

Collision-free motion planning of dual-arm reconfigurable robots

Dual-arm reconfigurable robot is a new type of robot. It can adapt to different tasks by changing its different end-effector modules which have standard connectors. Especially, in fast and flexible assembly, it is very important to research the collision-free planning of dual-arm reconfigurable robots. It is to find a continuous, collision-free path in an environment containing obstacles. A new approach to the real-time collision-free motion planning of dual-arm reconfigurable robots is used in the paper. This method is based on configuration space (C-Space). The method of configuration space and the concepts reachable manifold and contact manifold are successfully applied to the collision-free motion planning of dual-arm robot. The complexity of dual-arm robots’ collision-free planning will reduce to a search in a dispersed C-Space. With this algorithm, a real-time optimum path is found. And when the start point and the end point of the dual-arm robot are specified, the algorithm will successfully get the collision-free path real time. A verification of this algorithm is made in the dual-arm horizontal articulated robot SCARATES, and the simulation and experiment ascertain that the algorithm is feasible and effective.

Implementation of a Robot System for Sculptured Surface Cutting. Part 2. Finish Machining

Rapid prototyping plays an important role in product development. There are two ways to realise rapid prototyping: one is to develop new prototyping equipment such as stereolithography apparatus (SLA), selective laser sintering (SLS), etc., and the other is to improve existing CNC techniques. In this work, a robot system for rapid prototyping, which is an enhancement of the CNC based method, is presented. A robot arm holding a milling tool is used to machine the prototype of a solid model drawn using a commercial CAD system. In this paper, Part 1, a strategy using the robot for rough machining is discussed and then an automatic tool-path generation method using a grid height array is presented. This method can generate tool paths for rough machining with different tolerances. As a verification of the proposed algorithm, a number of prototypes have been produced, which have demonstrated the feasibility and advantages of the algorithm. In a companion paper, Part 2, an approach to represent C-space by incorporating possible variations in tooling orientations is proposed. In order to reduce error on complex surfaces resulting from undercut or overcut operations, a curvature-matching algorithm is developed. Finally, experimental work using the collision-free planning strategy and simulation for the curvature matching algorithm is carried out.

A simple algorithm for intelligent manipulator collision-free motion

The collision-free planning of motion is a fundamental problem for artificial intelligence applications in robotics. The ability to compute a continuous safe path for a robot in a given environment will make possible the development of task-level robot planning systems so that the implementation details and the particular robot motion sequence will be ignored by the programmer.

Ｃｏｎｆｉｇｕｒａｔｉｏｎ空間における障害物記述に関する考察

For motion planning of a manipurator, the use of a configuration space is highly efficient. Algorithms of the collision-free planning in static environments have been proposed in many papers. The efficiency of the algorithms depends on the description of obstacles in a configuration space. In general, the complexity of a configuration space map exponentially increases with the number of joints. Therefore, building the configuration space map is a time-consuming process, and the collision-free path can not be searched in real time. In this paper, we illustrate mathematical properties of a new kind of configuration space and propose an approach to parameterizing an obstacle in the configuration space. A spherical obstacle in a work space is transformed into a characteristic subspace in the configuration space. Therefore, we can approximate parameters of a sphere as a set of geometric entities. The transformation of a complex work space into the configuration space is described in terms of integrating the transformation of each element of a set of spheres. A collision-free path in a dynamic environment is found by using a Penalty-Function-Method. The Penalty-Function is modified according to the factors of the velocity along axes in a polar coordinates system.