Smooth path and speed planning for an automated public transport vehicle

An automated parallel parking strategy for a car-like mobile robot is presented. The study considers general cases of parallel parking for a rectangular robot within a rectangular space. The system works in three phases. In scanning phase, the parking environment is detected by ultrasonic sensors mounted on the robot and a parking position and manoeuvring path is produced if the space is sufficient. Then in the positioning phase, the robot reverses to the edge of the parking space avoiding potential collisions. Finally, in manoeuvring phase, the robot moves to the parking position in the parking space in a unified pattern, which may requires backward and forward manoeuvres depending on the dimensions of the parking space. Motion characteristics of this kind of robots are modeled, taking into account the nonholonomic constraints acting on the car-like robot. A collision-free path is planned in reference to the surroundings. The strategy has been integrated into an automated parking system, and implemented in a modified B12 mobile robot, showing capable of safe parking in tight situations.

A sensor guided autonomous parking system for nonholonomic mobile robots

Shell space decomposition based path planning for AUVs operating in a variable environment

We propose an efficient stochastic scheme for minimum-time trajectory planning of a nonholonomic unicycle mobile robot under constraints on path curvature, velocities, and torques. This problem, which is known to be complex, often requires important runtimes, particularly if obstacles are present and if full dynamics is considered. The proposed technique is a fast variant of the random-profile approach recently applied to wheeled-mobile robots. It incorporates a trapezoidal-velocity-profile constraint that helps reduce the number of unknown parameters and that speeds up the calculation steps. Results are presented for two- and three-wheel mobile robots in free/constrained workspaces. A comparison with reference solutions, which were obtained independently, shows that the proposed variant is able to achieve almost the same quality of calculated trajectories while reducing the runtime considerably.

Trajectory Planning of Unicycle Mobile Robots With a Trapezoidal-Velocity Constraint

This paper considers the motion planning problem that arises when a tethered robot descends and ascends steep obstacle-strewn terrain. This work is motivated by the Axel tethered robotic rover designed to provide access to extreme extra-planetary terrains. Motion planning for this type of rover is very different from traditional planning problems because the tether geometry under high loading must be considered during the planning process. Furthermore, only round-trip paths that avoid tether entanglement are viable solutions to the problem. We present an algorithm for tethered robot motion planning on steep terrain that reduces the likelihood that the tether will become entangled during descent and ascent of steep slopes. The algorithm builds upon the notion of the shortest homotopic tether path and its associated sleeve. We provide a simple example for purposes of illustration.

/pdf/motion-planning-on-steep-terrain-for-the-tethered-axel-rover-2e45b8qe5f.pdf

Motion planning on steep terrain for the tethered axel rover

This paper presents a novel time-optimal motion planning strategy for a mobile robot with kinematic constraints. The method works in environments in presence of obstacles, without needing to generate the configuration space for the robot. Further, it derives a minimum time first derivative smooth path, as opposed to a minimum distance path which is commonly given by various present solution techniques. The problem is solved in three stages: (i) A reduced visibility graph for a point object is obtained. (ii) The reduced visibility graph is converted into a feasible reduced visibility graph accounting for the size and kinematic constraints of the robot. (iii) The A* algorithm is used to search the feasible reduced visibility graph with the cost function being the time of travel, to obtain a safe, time-optimal, smooth path. The algorithm runs in polynomial time. The method has been tested in computer simulations and test results are presented

Time-optimal smooth-path motion planning for a mobile robot with kinematic constraints

Abmcf- Presented is a novel motion strategy for a mobile, car like robot that is subject to kinematic constraints. The algorithm operates on the original obstacles, without needing to generate the configuration space obstacles for the dimensioned robot. The path for the dimensioned robot is generated in three stages: (i) the shortest path problem for a point robot is solved; (ii) free space relative to the point robot shortest path is locally evaluated by minimum distance computations; (iii) the point robot shortest path is locally modified to account for the size and kinematic constraints of the mobile robot. If the shortest point robot path fails to be modified into a feasible path for the robot, the process is repeated with a second candidate point robot path, and SO on until a feasible path is generated. Thus the proposed strategy combines a global scheme for point robot path generation with a local scheme for free space evaluation and point robot path modification. The algorithm is computationally efficient, being of computational time O(nk +nlogn) where n is the total number of vertices, including the two ends, and k is the number of obstacles. The algorithm has been tested in computer simulations, demonstrating its ability to automatically generate paths which may include reversals.

A Motion Strategy For A Mobile Robot With Holonomic And Nonholonomic Constraints

This paper presents a new motion planning approach, including reversal manoeuvres, for car-like robots subject to non-holonomic constraints. The paper presents a complete path planning algorithm and describes the procedure for constructing a collision-free path for a mobile robot constrained by its rectangular shape and kinematics. Emphasis is made on the techniques of reversal transfers, which are used to compensate the limited manoeuvrability of a car-like robot. The approach works entirely in the workspace, as opposed to building a higher dimensional configuration space (C-space). It starts by constructing a visibility graph and finding the shortest path for a point robot and then detects areas where collision may occur by minimum distance calculations between obstacles and between the selected path and obstacles. Robot configurations are placed along the shortest path and lemmas are developed for ascertaining transfers from one robot configuration to another. The transfer techniques include direct, in...

Motion Planning with Reversal Manoeuvres for a Non-Holonomic Constrained Robot

A scheduling and compression strategy is presented for a multiple robot assembly workcell. Based on dynamic programming, the algorithm gives an initial assembly sequence for a two- or three-robot cell with a common resource or dedicated ones. The initial assembly sequence is computed efficiently, with computational complexity of being O (log n/k) where n is the number of elements in k resources. Then the initial sequence is further compressed towards the time-optimal assemblysequence. Precedence constraints in assembly are considered. The scheme is tested using computer simulations and some test results are presented. For the problems solved (typically involving 20 elements), the computational times were less than 5 seconds in an Apollo 300 workstation.

Scheduling and compression for a multiple robot assembly workcell

An assembly sequence planning scheme, giving the time optimal solution for a two-robot cell, is presented. The scheme is based on dynamic programming, and the time optimum assembly sequence is generated in two stages. In stage one, an initial candidate sequence is derived. The stage-one algorithm is computationally efficient, the complexity being O( log n k ) , where n is the number of elements in k groups. It also gives near-optimal results. Expression for the lower bounds for the total assembly time are derived in order to assess the departure from optimality of the stage-one sequence. In stage two, the initial candidate sequence is optimized using an iterative technique to yield the time optimal sequence. The scheme is extended to account for precedence constraints. It can also be extended for assembly cells with more than two robots. The scheme is tested using computer simulations, and some test results are presented. For the problems solved (typically involving 20 elements), the computational times were less than 5 sec in an Apollo 300 workstation.

Assembly scheduling for an integrated two-robot workcell

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