Nik A. Melchior

Particle RRT for Path Planning with Uncertainty

This paper describes a new extension to the rapidly-exploring random tree (RRT) path planning algorithm. The particle RRT algorithm explicitly considers uncertainty in its domain, similar to the operation of a particle filter. Each extension to the search tree is treated as a stochastic process and is simulated multiple times. The behavior of the robot can be characterized based on the specified uncertainty in the environment, and guarantees can be made as to the performance under this uncertainty. Extensions to the search tree, and therefore entire paths, may be chosen based on the expected probability of successful execution. The benefit of this algorithm is demonstrated in the simulation of a rover operating in rough terrain with unknown coefficients of friction

Socially Distributed Perception: GRACE plays social tag at AAAI 2005

This paper presents a robot search task (social tag) that uses social interaction, in the form of asking for help, as an integral component of task completion. Socially distributed perception is defined as a robots ability to augment its limited sensory capacities through social interaction. We describe the task of social tag and its implementation on the robot GRACE for the AAAI 2005 Mobile Robot Competition & Exhibition. We then discuss our observations and analyses of GRACEs performance as a situated interaction with conference participants. Our results suggest we were successful in promoting a form of social interaction that allowed people to help the robot achieve its goal. Furthermore, we found that different social uses of the physical space had an effect on the nature of the interaction. Finally, we discuss the implications of this design approach for effective and compelling human-robot interaction, considering its relationship to concepts such as dependency, mixed initiative, and socially distributed cognition.

Socially distributed perception

This paper presents a robot search task (social tag) that uses social interaction, in the form of asking for help, as an integral component of task completion. We define socially distributed perception as a robots ability to augment its limited sensory capacities through social interaction.

Graph-based trajectory planning through programming by demonstration

As robots are utilized in a growing number of applications, the ability to teach them to perform tasks safely and accurately becomes ever more critical. Programming by demonstration offers an expressive means for teaching while being accessible to domain experts who may be novices in robotics. This work investigates a programming by demon- stration approach to learning motion trajectories for robotic manipulator tasks. Using a graph constructed to determine correspondences between multiple imperfect demonstrations, the robot learner plans novel trajectories that safely and smoothly generalize the teachers behavior, while attenuating those imperfections. The learner also actively detects instances of diverging strategy between examples, requesting advice for resolving these ambiguities. We demonstrate our approach in example domains with a 7 degree-of-freedom manipulator.

Overcoming sensor noise for low-tolerance autonomous assembly

The capability to assemble structures is fundamental to the use of robotics in precursor missions in orbit and on planetary surfaces. We have performed autonomous assembly in neutral buoyancy of elements of a space truss whose mating components require positioning tolerances of the same order of magnitude as the noise in the sensor systems used for the docking. Numerous trade-offs, design decisions, and innovations were made during the development of the assembly system in order to both reduce and compensate for the sensor noise. By using relative positioning, decoupling sensing and manipulation, caching high-quality position estimates, and developing a new waypoint-completion metric, we were able to reduce sensor noise to the sub-millimeter level and autonomously assemble components with millimeter tolerances. In this paper, we discuss our approaches to the problem and report the results of a series of autonomous assembly operations.