Whether they are asked to polish or assemble parts, clean the house or open doors, the future generation of robots will have to cope with contact tasks under uncertainty in a stable and safe manner. Obtaining a controlled contact motion under uncertainty is still a major challenge for the robotics community. At present most research groups focus on one of the subcomponents (i.e., modeling, planning, estimation or control) of the system, and no overall system is developed yet. This paper presents a literature survey of the state-of-the-art of the subcomponents and points to the need for effective integration of those components.

Active compliant motion: a survey

The artificial potential field (APF) method is widely used for autonomous mobile robot path planning due to its simplicity and mathematical elegance. However, most researches are focused on solving the path-planning problem in a stationary environment, where both targets and obstacles are stationary. This paper proposes a new APF method for path planning of mobile robots in a dynamic environment where the target and obstacles are moving. Firstly, the new force function and the relative threat coefficient function are defined. Then, a new APF path-planning algorithm based on the relative threat coefficient is presented. Finally, computer simulation and experiment are used to demonstrate the effectiveness of the dynamic path-planning scheme.

An Evolutionary Artificial Potential Field Algorithm for Dynamic Path Planning of Mobile Robot

Acoustic robot navigation using distributed microphone arrays

We present the first practical, implemented configuration-space computation algorithm for a curved, planar object translating and rotating amidst stationary obstacles. The bodies are rigid, compact, regular, and bounded by a finite number of rational parametric curve segments. The algorithm represents the three-dimensional configu ration space as two-dimensional slices in which the moving object has a fixed orientation. It discretizes the configuration space into in tervals of equivalent slices separated by critical slices. The output is topologically correct and accurate to within a specified toler ance. We have implemented the algorithm for objects bounded by line segments and circular arcs, which is an important class for applications. The program is simple, fast, and robust. The slice representation is a natural and efficient abstract data type for geo metric computations in robotics and engineering.

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Sliced configuration spaces for curved planar bodies

Artificial potential fields, which are widely used in robotics for path planning and collision avoidance, are normally beset by difficulties arising from the existence of local minima. This article proposes a solution that involves an asymptotically stable point-mass system governed by differential equations. The system represents a planar point robot moving from its initial position to the desired goal whilst avoiding a static obstacle. Because the system is asymptotically stable, its Lyapunov function, which produces artificial potential fields around the goal and the obstacle, has no local minima other than the goal configuration in the pathwise-connected proper subset of free space which contains the goal configuration. As an application, we consider the point stabilization of a planar mobile car-like robot moving in the presence of a static obstacle.

An asymptotically stable collision-avoidance system

This paper presents a path-planning algorithm for an articulated planar robot with a static obstacle. The algorithm selects a robot part, finds a path to its goal configuration by systematic configuration space search, drags the entire robot along the path using compliant motion, and repeats the cycle until every robot part reaches its goal. The planner is tested on 11 000 random problems, which span dozens of robot/obstacle geometries with up to 43 moving parts and with narrow channels. It solves every problem in seconds, whereas randomized algorithms appear to fail on all of them.

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Path planning for planar articulated robots using configuration spaces and compliant motion

We present a path planning algorithm for a polyhedral robot with six degrees of freedom (6DOF) and a static obstacle. The planner consists of a dual-tree RRT algorithm that uses a novel local planner. A local planner tests if two robot configurations can be connected by a simple path. Ours searches a 3DOF subspace of the robot/obstacle configuration space, whereas prior planners search the line segment that connects the two configurations. Empirical evidence suggests that the benefit of the 3DOF search outweighs the cost. Our planner outperforms prior planners on problems with narrow channels and performs comparably (shorter paths, similar running times) on other problems

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RRT path planner with 3DOF local planner

We describe a parametric synthesis algorithm for planar mechanical systems comprised of higher kinematic pairs in which each part translates along a fixed axis or rotates around a fixed point. Kinematic function is computed from the CAD models of the parts and is represented graphically as configuration spaces. The designer uses the mouse to request changes in the configuration spaces. The program computes parameter values that achieve the changes. The computation is iterative: the program repeatedly linearizes the mapping from design parameters to kinematics around the current values, pseudo-inverts the linear mapping, and performs a small parameter modification that moves the system toward the desired kinematics. At each iteration, the program matches the current kinematics against the initial kinematics. If it detects an unintended change, it backs up, adds kinematic constraints that prevent the change, and resumes iteration.

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Computer-aided synthesis of higher pairs via configuration space manipulation

We present an algorithm for dynamical simulation of rigid-body mechanical systems with changing contact topologies based on configuration spaces. The algorithm advances the state of the art in contact analysis, which is the main bottleneck in dynamical simulation. The task is to identify the touching parts and to compute the ensuing contact forces. Our algorithm computes the configuration spaces of all pairs of parts and uses them as contact models. It overcomes the limitations of mechanical systems simulators, which require precomputed contact models, and of general-body simulators, which perform contact analysis on the part models at every time step. Neither approach is practical for mechanisms with multiple contacts and complex contact geometry, such as clock escapements, chain gears, and part feeders. We describe a configuration space simulator for assemblies of planar parts with one degree of freedom apiece and demonstrate it on two mechanisms with many complex contacts.

Dynamical simulation of assemblies of planar, 1 DOF parts with changing contacts using configuration spaces

I present a deterministic path planning algorithm for an assembly of rigid planar parts connected by joints. The part boundaries are comprised of line segments and circular arcs. The algorithm is based on configuration space computation and search. It is complete for one moving part and is heuristic for multiple parts. It is the first complete algorithm that is practical for real-world applications. It is more reliable than randomized algorithms, which are inherently incomplete. It solves problems with many parts, crowded environments, tight part fits, and closed chains.

E. Sacks

Papers

Path planning for planar articulated robots using configuration spaces and compliant motion

RRT path planner with 3DOF local planner

Computer-aided synthesis of higher pairs via configuration space manipulation

Dynamical simulation of assemblies of planar, 1 DOF parts with changing contacts using configuration spaces

Deterministic path planning for planar assemblies