Srinivas Akella's Research

Srinivas with AdeptOne robot My current research focuses on algorithms for coordinating the collision-free motions of multiple robots. By designing algorithms that consider the complex dynamics of industrial robots, I can coordinate the motions of robots in automotive workcells. In a related effort, I am developing algorithms for coordinating microdroplets in lab-on-a-chip digital microfluidics systems so they can perform biochemical analyses. I am also developing algorithms for robotics systems that can automatically fold objects for packaging applications, as well for identifying protein folding pathways.

I am also interested in developing robotic systems that can automatically perform manipulation tasks. By designing efficient algorithms and planners that use the underlying task mechanics and geometry to generate solutions automatically, I have developed robots that are mechanically simple, yet very flexible. To demonstrate this approach, I have implemented robotic systems to feed and fold objects for flexible assembly and packaging. Since these systems do not require specialized effectors or sensors, they can be implemented quickly and inexpensively to shorten the time to market of new products and to reduce manufacturing costs.

Digital Microfluidic Systems
Multiple Robot Coordination
Proximity Queries
Articulated 3-D Structures
Protein Folding
Parts Feeding

Digital Microfluidic Systems

Multiple Robot Coordination

Car painting workcell When multiple robots execute tasks in a shared workspace, automatic planners to ensure that the robots do not collide with each other become essential. Optimized coordination of multiple robots can result in tremendous time, energy, and cost savings. I have developed mixed integer programming formulations to minimize task execution time and coordinate collision-free robot motions, given individual robot trajectories (or paths) that avoid collisions with stationary obstacles. We have explored a progression of problems, particularly for the case when the robots have dynamics constraints. This work is directly relevant to the design and virtual prototyping of automotive painting and welding workcells, and the coordination of wafer transport robots in semiconductor fabs. This is joint work with Jufeng Peng and Seth Hutchinson .

Proximity Queries between Convex Objects: An Interior Point Approach for Implicit Surfaces

Closest points for three objects We develop an interior point approach to exact distance computation between convex objects represented as intersections of implicit surfaces. Exact distance computation algorithms are particularly important for applications involving objects that make contact, such as in multibody dynamic simulations and haptic interactions. In contrast to geometric approaches developed for polyhedral objects, we formulate the distance computation problem as a convex optimization problem; this optimization formulation has been previously described for polyhedral objects. Example implicit surfaces include planes (polyhedra), quadrics, and generalizations of quadrics including superquadrics and hyperquadrics, as well as intersections of these surfaces. We use an interior point method to solve the optimization problem and demonstrate that for general convex objects represented as implicit surfaces, interior point approaches are globally convergent, and fast in practice. Further, they provide polynomial-time guarantees for implicit surface objects when the implicit surfaces have self-concordant barrier functions. We use a primal-dual interior point algorithm that solves the KKT conditions obtained from the convex programming formulation. For the case of polyhedra and quadrics, we establish a theoretical time complexity of O(n^{1.5}), where n is the number of constraints. We present implementation results for example implicit surface objects and demonstrate that distance computation rates of about 1 kHz can be achieved. Joint work with Nilanjan Chakraborty, Jufeng Peng, John Mitchell .

Dynamic Simulation of Multibody Systems with Intermittent Contact

Articulated 3-D Structures

folding Manipulating articulated 3-D structures is challenging since the shape of the object changes as it is manipulated and the number of degrees of freedom of the object can exceed those of the manipulating robot. I am developing techniques for the manipulation and motion planning of "pop-up" 3-D structures. This work is motivated by the task of folding cartons from blanks to package products such as telephones and two-way radios, which is typically performed by human operators or with fixed automation. Liang Lu and I developed a flexible method to fold cardboard cartons from blanks by using interchangeable fixtures to enable rapid product changeovers. We developed a motion planning algorithm that generates all folding sequences for a carton by modeling it as a robot manipulator with revolute joints and branching links. A fixture constrains the carton motion to paths consisting of line segments in its configuration space, and these paths are generated by the motion planner. To illustrate the method, we selected a folding sequence for an example carton, designed a fixture, and demonstrated folding of the carton from blanks with an AdeptOne robot.

Carton folding movie (YouTube)

Protein Folding Pathways

Folding pathways for 2GB1(16) Since the 3D folded shape of a protein determines its function, knowing the folding pathways can aid understanding of misfolding diseases (e.g., Alzheimer's disease) and guide drug design. We are building on sampling-based motion planning methods, which have been recently used to identify feasible folding pathways for proteins with known structure by modeling proteins as articulated robots. Our focus is on generating sample configurations using a hidden Markov model of protein structures from the Protein Data Bank. By using energy-minimized protein configurations derived from those present in nature, we believe we can obtain biologically plausible configurations and sample the configuration space more efficiently. We have preliminary folding pathway results for short proteins. Joint work with Chris Bystroff , Yogesh Girdhar, and Ted Carlson.

Parts Transfer

a parts transfer plan A parts transfer system must automatically identify actions to move parts from initial to goal configurations. I explored the use of graspless pushing operations, which can be used by robots to feed parts for assembly or by mobile robots to move furniture. I proved that any polygonal part can be moved from any known position and orientation to any other position and orientation in the obstacle-free plane by a sensorless sequence of pushes. I developed a linear programming formulation and implemented a polynomial-time planner to automatically generate sequences of pushes to perform such parts transfer. I demonstrated these plans using a Puma 560 robot.

A 1JOC plan A fundamental question is: How many degrees of freedom does a robot require to manipulate a part with three planar degrees of freedom? We developed a one-joint-over-conveyor (IJOC) system that uses the pushing motions of a single joint effector positioned over a conveyor belt and the conveyor drift to perform parts transfer. We showed that it is possible to manipulate all three degrees of freedom of any polygon to move it from any known initial configuration upstream of the effector to a specific goal configuration. I developed a nonlinear programming formulation to automatically generate plans for this 1JOC system and demonstrated these plans on a conveyor with an Adept 550 robot.

Sensorless 1JOC Sensorless 1JOC: We modified the 1JOC system to perform sensorless parts transfer on a conveyor. This system can perform a sequence of operations to bring all initially unknown positions and orientations of the part (upstream of the effector) to the same goal position and orientation without using sensors.

Parts Orienting

Sensor-based orienting A parts orienting system must identify a sequence of actions to bring a randomly oriented part to a goal orientation for assembly. Since sensorless systems can orient parts (e.g. sensorless 1JOC), characterizing the advantages of using sensors is important. To quantify the significant cycle time reduction when inexpensive sensors that provide partial information on orientation, such as photosensors to measure part width, are combined with actions, I proved bounds on the lengths of sensor-based plans. I also showed that a single sensor-based plan can orient and recognize different parts.

Tolerance model Toleranced parts: Since parts manufactured to tolerances have to be reliably oriented, I characterized the effect of part shape uncertainty on the orienting process. For the class of convex polygonal parts, I defined a shape tolerance model that permits the center of mass and the vertices to lie anywhere in disks centered at their nominal positions. I demonstrated that the variational class of parts defined by the tolerance model can be reliably oriented by both sensor-based and sensorless plans despite the resulting nondeterminism.

Reconfigurable Parts Feeder

Side view of Pachinko machine Front view of Pachinko machine

Jointly with Sebastien Blind, Chris McCullough, and Jean Ponce , I developed a reconfigurable parts orienting device that is modular and composed of simple electromechanical elements. This device, the "Pachinko machine," automatically catches and orients dropped parts of known shape using a grid of actuated pins on a vertical plate. We use a configuration space representation of the part and nest geometry to compute stable part configurations in the nests, their capture regions, and orienting plans.

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Srinivas Akella / sakella at uncc dot edu