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Navigation and obstacle avoidance are essential for mobile robots. In the dynamic environment, the obstacles may move with varying velocities. It is thus crucial to develop an effective scheme for moving obstacle avoidance. Motivated by this, in this paper, we propose such a scheme based on parametric trajectory planning. With the conditions for collision avoidance formulated as the constraints, a...
Mobile manipulators and humanoid robots should be able to utilize their manipulation capabilities to move obstacles out of their way. This concept is captured within the domain of Navigation Among Movable Obstacles (NAMO). While a variety of NAMO algorithms exists, they typically assume full world knowledge. In contrast, real robot systems only have limited sensor range and partial environment knowledge...
In multi-robot systems, efficiently navigating in a a partially-known environment is an ubiquitous but challenging task, as each robot must account for the uncertainty introduced, for example, by other moving robots. This uncertainty makes pre-computed plans not always applicable, and often hinders the desired efficient use of the robot's resources. In this work, we present a local anytime approach...
We consider cognitive factories with multiple teams of heterogenous robots, and address two key challenges of these domains, hybrid reasoning for each team and finding an optimal global plan (with minimum makespan) for multiple teams. For hybrid reasoning, we propose (i) modeling each team's workspace taking into account capabilities of heterogeneous robots, (ii) embedding continuous external computations...
Minimum time optimization trajectory planning problem which can generate smooth trajectory of joints of robot is still complex and difficult to solve. A novel hybrid cubic B-spline and convex optimization method was presented for trajectory planning of robotic manipulator in this paper. First, the first and second derivatives of path trajectory coordinates s, called pseudo-velocity and pseudo-acceleration...
Sampling based algorithms provide efficient methods of solving robot motion planning problem. The advantage of these approaches is the ease of their implementation and their computational efficiency. These algorithms are probabilistically complete i.e. they will find a solution if one exists, given a suitable run time. The drawback of sampling based planners is that there is no guarantee of the quality...
This paper presents a new method to synthesize full body motion for controlling humanoid robots in highly constrained environments. Given a reference motion of the robot and the corresponding environment configuration, the spatial relationships between the robot body parts and the environment objects are extracted as a representation called the Interaction Mesh. Such a representation is then used...
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...
Motion planning is a fundamental aspect of every robotic system. The objective is to generate an efficient and collision-free path for the robot to reach a certain number of reference points. This paper presents a method to define a near-optimal sequence of target positions for a robot executing a multiple goal task. In the described context, optimal means that the robot reaches its target positions...
A navigation and stabilization scheme for 3D heterogeneous (UAVs and UGVs) formations acting under a hawk-eye like relative localization is presented in this paper. We formulate a novel Model Predictive Control (MPC) based concept for formation driving in a leader-follower constellation into a required target region. The formation to target region problem in 3D is solved using the MPC methodology...
In this paper, a path planning approach for finding an optimal path is proposed to reduce the expected-time in target search by robot. This approach employs a heuristic algorithm to generate a basic path and minimize the expected-time. Considering different direction may lead to different expected-time in a same loop, a direction choosing method is presented to improve the performance of this heuristic...
In the few years, lots of scholars employ many methods to optimize the trajectory planning and control for industrial robots. However, these methods are difficult to gain the trajectory planning results with high accuracy. Thus, trajectory planning theory and method of industrial robot is presented in the paper. Firstly, trajectory planning theory of industrial robot is introduced and then trajectory...
This paper presents a motion-planning approach for coordinating multiple mobile robots in moving along specified paths. The robots are required to fulfill formation requirements while meeting velocity/acceleration constraints and avoiding collisions. Coordination is achieved by planning robot velocities along the paths through a velocity-optimization process. An objective function for minimizing formation...
Robots that operate in natural human environments must be capable of handling uncertain dynamics and underspecified goals. Current solutions for robot motion planning are split between graph-search methods, such as RRT and PRM which offer solutions to high-dimensional problems, and Reinforcement Learning methods, which relieve the need to specify explicit goals and action dynamics. This paper addresses...
In this paper we solve the static-equilibrium constrained inverse kinematics problem for a system made of multiple humanoid robots and manipulated objects given a set of contacts between any surfaces of the robots, any surfaces of the manipulated objects, and any surfaces of the environment. In particular, inter-robots contacts are possible. The contacts considered here are neither necessarily coplanar,...
This paper presents a motion planning approach to coordinating multiple mobile robots in moving along specified paths. The robots are required to fulfill formation requirements while meeting velocity/acceleration constraints and avoiding collisions. Coordination is achieved by planning robot velocities along the paths through a velocity optimization process. An objective function for minimizing formation...
This paper explores the Navigation Among Movable Obstacles (NAMO) problem in an unknown environment. We consider the realistic scenario in which the robot has to navigate to a goal position in an unknown environment consisting of static and movable objects. The robot may move objects if the goal can not be reached otherwise or if moving the object may significantly shorten the path to the goal. We...
This paper presents a novel optimization based path planner that can simultaneously plan multiple contingency paths to account for the uncertain actions of dynamic obstacles. This planner addresses the particular problem of collision avoidance for autonomous road vehicles which are required to safely interact with other vehicles with unknown intentions. The presented path planner utilizes an efficient...
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 an approach to coordinating a group of mobile robots that move along the designed paths. Subject to the constraints of velocity/acceleration bounds and collision avoidance, the robots are required to maintain the formation relationship while moving. The coordination is realized by posing the coordination problem as a velocity optimization problem in motion planning and then properly...
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