this paper is as follows: in Section 2, we collect some mathematical preliminaries from the literature on controllability of nonlinear systems and on classification of free Lie algebras. These are drawn from classical references in control theory [4, 17, 18, 36, 40] and Lie algebras [15, 43]. In Section 3, using some outstanding results of Brockett on optimal steering of certain classes of systems as motivation [5], we discuss the use of sinusoidal inputs for steering systems of first order, i.e., systems where controllability is achieved after just one level of Lie brackets of the input vector fields. Section 4 attempts to expand the domain of applicability of these results to more complex systems, where several orders of Lie brackets are needed to obtain the full Lie algebra associated with the input distribution. The 4 MURRAY AND SASTRY

In manufacturing, it is often necessary to orient parts prior to packing or assembly. We say that a planar part is polygonal if its convex hull is a polygon. We consider the following problem: given a list of n vertices describing a polygonal part whose initial orientation is unknown, find the shortest sequence of mechanical gripper actions that is guaranteed to orient the part up to symmetry in its convex hull. We show that such a sequence exists for any polygonal part by giving an O#n log n# algorithm for finding the sequence. Since the gripper actions do not require feedback, this result implies that any polygonal part can be oriented without sensors.

What plans are like depends on how they're used. We contrast two views of plan use. On the plan-as-program view, plan use is the execution of an effective procedure. On the plan-as-communication view, plan use is like following natural language instructions. We have begun work on computational models of plans-as-communications, building on our previous work on improvised activity and on ideas from sociology.

This paper describes our current research into nonprehensile palm manipulation. The term “palm ” refers to the use of the entire device surface during manipulation, as opposed to use of the fingertips alone.

The existing industrial parts feeders move the parts through a sequence of mechanical filters that reject parts in unwanted orientations. In this paper we develop a new setup that uses a different vibratory mechanism to systematically manipulate parts, by actively orienting and localizing them. The idea is to generate and change dynamic modes for a plate by varying the applied frequency of oscillation. Depending on the node shapes of the plate for these frequencies, the position and orientation of the parts can be controlled. We develop an analysis of the underlying dynamics, and show that it can be used to predict the behavior of objects placed on the vibrating plate. Using this analysis, we propose that the applied frequencies can be automatically sequenced to obtain a "sensorless" strategy for manipulating a given object.

this paper we describe the first complete algorithm to design such sequences for a given convex polygonal part. The algorithm is complete in the sense that it is guaranteed to find a design if one exists and to terminate with a negative report otherwise. Based on an exact breadth-first search of the design space, the algorithm is also guaranteed to find the design requiring the fewest fences. We describe the algorithm and compare results with those previously reported. We conjecture that a fence design exists to orient any convex polygonal part.

This paper discusses issues in the design and implementation of metamorphic robotic systems. A metamorphic robotic system is a collection of independently controlled mechatronic modules, each of which has the ability to connect, disconnect, and climb over adjacent modules. A metamorphic system can dynamically reconfigure by the locomotion of modules over their neighbors. Thus they can be viewed as a collection of connected modular robots which act together to perform the given task. The planar metamorphic robots described in this paper consist of hexagonal or square modules. Because of their shape, the modules completely fill the plane without any gaps, their centers forming a regular lattice. Both the hexagonal and square modules are provided with electromechanical coupling mechanisms actuated by D.C. motors. These connectors help to couple and uncouple modules as they move around each other to form different configurations. The modules are currently controlled by an external processor

In (Donald, 1995), we described a manipulation task for cooperating mobile robots that can push large, heavy objects. There, we asked whether explicit local and global communication between the agents can be removed from a family of pushing protocols. In this paper, we answer in the affirmative. We do so by using the general methods of (Donald, 1995) analyzing information invariants. We discuss several measures for the information complexity of the task: (a) How much internal state should the robot retain? (b) How many cooperating agents are required, and how much communication between them is necessary? (c) How can the robot change (side-effect) the environment in order to record state or sensory information to perform a task? (d) How much information is provided by sensors? and (e) How much computation is required by the robot? To answer these questions, we develop a notion of information invariants. We develop a technique whereby one sensor can be constructed from others by adding...

During the last three decades motion planning has emerged as a crucial and productive research area in robotics. In the mid-80's the most advanced planners were barely able to compute collisionfree paths for objects crawling in planar workspaces. Today, planners e ciently deal with robots with many degrees of freedom in complex environments. Techniques also exist to generate quasioptimal trajectories, coordinate multiple robots, deal with dynamic and kinematic constraints, and handle dynamic environments. This paper describes some of these achievements, presents new problems that have recently emerged, discusses applications likely to motivate future research, and nally gives expectations for the coming years. It stresses the fact that non-robotics applications (e.g., graphic animation, surgical planning, computational biology) are growing in importance and are likely to shape future motion planning research more than robotics itself. 1

This paper describes the use of task primitives in robot learning from observation. A framework has been developed that uses observed data to initially learn a task and then the agent goes on to increase its performance through repeated task performance (learning from practice). Data that is collected while a human performs a task is parsed into small parts of the task called primitives. Modules are created for each primitive that encode the movements required during the performance of the primitive, and when and where the primitives are performed. The feasibility of this method is currently being tested with agents that learn to play a virtual and an actual air hockey game. 1