A Single-Query Manipulation Planner

In manipulation tasks, a robot interacts with movable object(s). The configuration space in manipulation planning is thus the Cartesian product of the configuration space of the robot with those of the movable objects. It is the complex structure of such a "Composite Configuration Space" that makes manipulation planning particularly challenging. Previous works approximate the connectivity of the Composite Configuration Space by means of discretization or by creating random roadmaps. Such approaches involve an extensive pre-processing phase, which furthermore has to be re-done each time the environment changes. In this paper, we propose a high-level Grasp-Placement Table similar to that proposed by Tournassoud et al. (1987), but which does not require any discretization or heavy pre-processing. The table captures the potential connectivity of the Composite Configuration Space while being specific only to the movable object: in particular, it does not require to be re-computed when the environment changes. During the query phase, the table is used to guide a tree-based planner that explores the space systematically. Our simulations and experiments show that the proposed method enables improvements in both running time and trajectory quality as compared to existing approaches.Comment: 8 pages, 7 figures, 1 tabl

A Certified-Complete Bimanual Manipulation Planner

Planning motions for two robot arms to move an object collaboratively is a difficult problem, mainly because of the closed-chain constraint, which arises whenever two robot hands simultaneously grasp a single rigid object. In this paper, we propose a manipulation planning algorithm to bring an object from an initial stable placement (position and orientation of the object on the support surface) towards a goal stable placement. The key specificity of our algorithm is that it is certified-complete: for a given object and a given environment, we provide a certificate that the algorithm will find a solution to any bimanual manipulation query in that environment whenever one exists. Moreover, the certificate is constructive: at run-time, it can be used to quickly find a solution to a given query. The algorithm is tested in software and hardware on a number of large pieces of furniture.Comment: 12 pages, 7 figures, 1 tabl

Planning algorithms for complex manipulation tasks

Solving manipulation tasks requires planning not only robot motions but also various interaction such as grasps (robot-object) and placements (object-environment). This indispensable interaction imparts extra complexity to the problems such that solving complex manipulation tasks, which require a number of regrasping operations, remains elusive. In this thesis, we advance the state of the art by presenting novel unimanual and bimanual manipulation planning algorithms capable of planning manipulation motions with multiple regrasping. First, we introduce a unimanual manipulation planner that explores the composite configuration space efficiently and systematically, thanks to the guidance of the novel high-level grasp-placement graph. Unlike existing methods, the graph construction does not require heavy pre-processing and is specific to only the gripper and the manipulated object. Next, we present two bimanual manipulation planners. The first one addresses specific, yet challenging, cases when bimanual grasps remain the same throughout. With the novel characterization of configuration space with closed-chain constraints, the proposed planner can plan motions across different closed-chain connected components. The second one addresses more general cases when the object can be moved only when grasped by both robots. We present a planner with certified completeness property, which guarantees that when a certificate is available for a given object and environment, the planner will find a solution to any bimanual manipulation query whenever one exists. The hardware experiment demonstrates the planner's capability and is, to the best of our knowledge, the first to illustrate such regrasping capability, solving complex bimanual manipulation task on an actual system. Furthermore, we also present two improvements to motion planning, which indeed is a crucial component in any manipulation planning algorithm. The first improvement is an algorithm for generating time-optimal second-order trajectories subject to velocity, acceleration, and minimum-switch-time constraints. The latter constraint helps prevent concentrated acceleration switching in trajectories. The second improvement is a new bidirectional motion planner called AVP-BiRRT. The integration of the Admissible Velocity Propagation (AVP) algorithm, which enables a geometric path planner to find dynamically feasible paths, into a bidirectional planner is made possible by our newly proposed extension, AVP-Backward.Doctor of Philosophy (MAE

Time-optimal parabolic interpolation with velocity, acceleration, and minimum-switch-time constraints

Time-optimal trajectories with bounded velocities and accelerations are known to be parabolic, i.e. piecewise constant in acceleration. An important characteristic of this class of trajectories is the distribution of the switch points – the time instants when the acceleration of any robot joint changes. When integrating parabolic trajectory generation into a motion planning pipeline, especially one that involves a shortcutting procedure, resulting trajectories usually contain a large number of switch points with a dense distribution. This high frequency acceleration switching intensifies joint motor wear as well as hampers the robot performance. In this paper, we propose an algorithm for planning parabolic trajectories subject to both physical bounds, i.e. joint velocity and acceleration limits, and the minimum-switch-time constraint. The latter constraint ensures that the time duration between any two consecutive switch points is always greater than a given minimum value. Analytic derivations are given, as well as comparisons with other methods to demonstrate the efficiency of our approach.Accepted versio

Departure and conflict management in multi-robot path coordination

This paper addresses the problem of multi-robot path coordination, considering specific features that arise in applications such as automatic aircraft taxiing or driver-less cars coordination. The first feature is departure events: when robots arrive at their destinations (e.g. the runway for takeoff), they can be removed from the coordination diagram. The second feature is the “no-backward-movement” constraint: the robots can only move forward on their assigned paths. These features can interact to give rise to complex conflict situations, which existing planners are unable to solve in practical time. We propose a set of algorithms to efficiently account for these features and validate these algorithms on a realistic model of Charles de Gaulle airport.Civil Aviation Authority of Singapore (CAAS)Accepted versionThis work was partially supported by grant ATMRI:2014-R6-PHAM awarded by NTU and the Civil Aviation Authority of Singapor